CM30174 + CM50206 Intelligent Agents Marina De Vos, Julian Padget - - PowerPoint PPT Presentation

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CM30174 + CM50206 Intelligent Agents Marina De Vos, Julian Padget - - PowerPoint PPT Presentation

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) CM30174 + CM50206 Intelligent Agents Marina De Vos, Julian Padget Communication and Ontologies / version 0.3 October 18,


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SLIDE 1

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

CM30174 + CM50206 Intelligent Agents

Marina De Vos, Julian Padget

Communication and Ontologies / version 0.3

October 18, 2011

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 1 / 56

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SLIDE 2

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Authors/Credits for this lecture

  • Chs. 6, 7, 8 of “An Introduction to Multiagent Systems”

[Wooldridge, 2009]. “Ontology Engineering” tutorial by Natalya Noy at the Semantic Web Working Symposium 2001. “Agents and the Semantic Web” tutorial by Terry Payne and Valentina Tamma at CEEMAS 2005. “RDF briefing” presentation by Frank van Harmelen. See http://ubp.l3s.uni-hannover.de/ubp. “A Semantic Web Primer” Grigoris Antoniou and Frank van

  • Harmelen. See

http://www.ics.forth.gr/isl/swprimer/

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 2 / 56

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SLIDE 3

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Authors/Credits for this lecture

  • Chs. 6, 7, 8 of “An Introduction to Multiagent Systems”

[Wooldridge, 2009]. “Ontology Engineering” tutorial by Natalya Noy at the Semantic Web Working Symposium 2001. “Agents and the Semantic Web” tutorial by Terry Payne and Valentina Tamma at CEEMAS 2005. “RDF briefing” presentation by Frank van Harmelen. See http://ubp.l3s.uni-hannover.de/ubp. “A Semantic Web Primer” Grigoris Antoniou and Frank van

  • Harmelen. See

http://www.ics.forth.gr/isl/swprimer/

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 2 / 56

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SLIDE 4

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Authors/Credits for this lecture

  • Chs. 6, 7, 8 of “An Introduction to Multiagent Systems”

[Wooldridge, 2009]. “Ontology Engineering” tutorial by Natalya Noy at the Semantic Web Working Symposium 2001. “Agents and the Semantic Web” tutorial by Terry Payne and Valentina Tamma at CEEMAS 2005. “RDF briefing” presentation by Frank van Harmelen. See http://ubp.l3s.uni-hannover.de/ubp. “A Semantic Web Primer” Grigoris Antoniou and Frank van

  • Harmelen. See

http://www.ics.forth.gr/isl/swprimer/

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 2 / 56

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SLIDE 5

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Authors/Credits for this lecture

  • Chs. 6, 7, 8 of “An Introduction to Multiagent Systems”

[Wooldridge, 2009]. “Ontology Engineering” tutorial by Natalya Noy at the Semantic Web Working Symposium 2001. “Agents and the Semantic Web” tutorial by Terry Payne and Valentina Tamma at CEEMAS 2005. “RDF briefing” presentation by Frank van Harmelen. See http://ubp.l3s.uni-hannover.de/ubp. “A Semantic Web Primer” Grigoris Antoniou and Frank van

  • Harmelen. See

http://www.ics.forth.gr/isl/swprimer/

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 2 / 56

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SLIDE 6

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Authors/Credits for this lecture

  • Chs. 6, 7, 8 of “An Introduction to Multiagent Systems”

[Wooldridge, 2009]. “Ontology Engineering” tutorial by Natalya Noy at the Semantic Web Working Symposium 2001. “Agents and the Semantic Web” tutorial by Terry Payne and Valentina Tamma at CEEMAS 2005. “RDF briefing” presentation by Frank van Harmelen. See http://ubp.l3s.uni-hannover.de/ubp. “A Semantic Web Primer” Grigoris Antoniou and Frank van

  • Harmelen. See

http://www.ics.forth.gr/isl/swprimer/

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 2 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Content

1

Agent Communication

2

Agent Communication Languages

3

Ontology Engineering (Noy) The Ontology Engineering cycle Pizza exercise

4

Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 3 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Motivation

Agents and MAS emerged from Distributed AI

Distribute problem-solving across several processes or machines Coordination implies a need to:

Communicate Plan Coordinate actions

Agents emerged as self-contained, autonomous entities that could perform (multiple) services Open Agent Systems

MAS developed by different organizations should interoperate Only works when all the agents conform to the same MAS ... not so open architecture

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 4 / 56

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SLIDE 9

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Motivation

Agents and MAS emerged from Distributed AI

Distribute problem-solving across several processes or machines Coordination implies a need to:

Communicate Plan Coordinate actions

Agents emerged as self-contained, autonomous entities that could perform (multiple) services Open Agent Systems

MAS developed by different organizations should interoperate Only works when all the agents conform to the same MAS ... not so open architecture

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 4 / 56

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SLIDE 10

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Motivation

Agents and MAS emerged from Distributed AI

Distribute problem-solving across several processes or machines Coordination implies a need to:

Communicate Plan Coordinate actions

Agents emerged as self-contained, autonomous entities that could perform (multiple) services Open Agent Systems

MAS developed by different organizations should interoperate Only works when all the agents conform to the same MAS ... not so open architecture

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 4 / 56

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SLIDE 11

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Agent Communication

Focus here is on macro aspects of intelligent agent technology: those issues relating to the agent society, rather than the individual agent: communication: speech acts; KQML & KIF; FIPA ACL. reaching agreements: kinds of auctions, negotiation, task-oriented domains cooperation: what is cooperation, cooperative versus non-cooperative encounters, the contract net protocol

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 5 / 56

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SLIDE 12

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Agent Communication

Focus here is on macro aspects of intelligent agent technology: those issues relating to the agent society, rather than the individual agent: communication: speech acts; KQML & KIF; FIPA ACL. reaching agreements: kinds of auctions, negotiation, task-oriented domains cooperation: what is cooperation, cooperative versus non-cooperative encounters, the contract net protocol

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 5 / 56

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SLIDE 13

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Agent Communication

Focus here is on macro aspects of intelligent agent technology: those issues relating to the agent society, rather than the individual agent: communication: speech acts; KQML & KIF; FIPA ACL. reaching agreements: kinds of auctions, negotiation, task-oriented domains cooperation: what is cooperation, cooperative versus non-cooperative encounters, the contract net protocol

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 5 / 56

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SLIDE 14

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 1/5

Most treatments of communication in (multi-)agent systems take inspiration from speech act theory. Speech act theories are pragmatic theories of language, i.e., theories of language use: they attempt to account for how language is used by people every day to achieve their goals and intentions. The origin of speech act theories are usually traced to Austin’s 1962 book, How to Do Things with Words.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 6 / 56

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SLIDE 15

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 1/5

Most treatments of communication in (multi-)agent systems take inspiration from speech act theory. Speech act theories are pragmatic theories of language, i.e., theories of language use: they attempt to account for how language is used by people every day to achieve their goals and intentions. The origin of speech act theories are usually traced to Austin’s 1962 book, How to Do Things with Words.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 6 / 56

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SLIDE 16

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 1/5

Most treatments of communication in (multi-)agent systems take inspiration from speech act theory. Speech act theories are pragmatic theories of language, i.e., theories of language use: they attempt to account for how language is used by people every day to achieve their goals and intentions. The origin of speech act theories are usually traced to Austin’s 1962 book, How to Do Things with Words.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 6 / 56

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SLIDE 17

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 2/5

Austin noticed that some utterances are rather like ‘physical actions’ that appear to change the state of the world. Paradigm examples would be:

declaring war baptism ‘I now pronounce you man and wife’

In fact, everything is said with the intention of satisfying some goal or intention. Speech Act theory attempts to explain how utterances may achieve intentions.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 7 / 56

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SLIDE 18

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 2/5

Austin noticed that some utterances are rather like ‘physical actions’ that appear to change the state of the world. Paradigm examples would be:

declaring war baptism ‘I now pronounce you man and wife’

In fact, everything is said with the intention of satisfying some goal or intention. Speech Act theory attempts to explain how utterances may achieve intentions.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 7 / 56

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SLIDE 19

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 2/5

Austin noticed that some utterances are rather like ‘physical actions’ that appear to change the state of the world. Paradigm examples would be:

declaring war baptism ‘I now pronounce you man and wife’

In fact, everything is said with the intention of satisfying some goal or intention. Speech Act theory attempts to explain how utterances may achieve intentions.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 7 / 56

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SLIDE 20

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

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SLIDE 21

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

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SLIDE 22

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

slide-23
SLIDE 23

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

slide-24
SLIDE 24

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

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SLIDE 25

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

slide-26
SLIDE 26

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

slide-27
SLIDE 27

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

slide-28
SLIDE 28

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 3/5

Searle (1969) identified various different types of speech act: representatives: such as informing, e.g., ‘It is raining’ directives: attempts to get the hearer to do something e.g., ‘please make the tea’ commisives: which commit the speaker to doing something, e.g., ‘I promise to... ’ expressives: whereby a speaker expresses a mental state, e.g., ‘thank you!’ declarations: such as declaring war or baptism.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 8 / 56

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SLIDE 29

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 4/5

There is some debate about whether this (or any!) typology of speech acts is appropriate. In general, a speech act can be seen to have two components:

a performative verb: (e.g., request, inform, . . . ) propositional content: (e.g., “the door is closed”) constructed from

a (formal) language, defining syntactic structures an ontology, defining the concepts

These are the key observations as far as agent communication is concerned.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 9 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 5/5

Consider: performative = request content = “the door is closed” speech act = “please close the door” performative = inform content = “the door is closed” speech act = “the door is closed!” performative = inquire content = “the door is closed” speech act = “is the door closed?” to see how the same content combined with different performatives takes on different meanings.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 10 / 56

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SLIDE 31

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 5/5

Consider: performative = request content = “the door is closed” speech act = “please close the door” performative = inform content = “the door is closed” speech act = “the door is closed!” performative = inquire content = “the door is closed” speech act = “is the door closed?” to see how the same content combined with different performatives takes on different meanings.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 10 / 56

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SLIDE 32

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Speech Acts 5/5

Consider: performative = request content = “the door is closed” speech act = “please close the door” performative = inform content = “the door is closed” speech act = “the door is closed!” performative = inquire content = “the door is closed” speech act = “is the door closed?” to see how the same content combined with different performatives takes on different meanings.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 10 / 56

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SLIDE 33

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Plan-Based Semantics

Cohen & Perrault (1979) defined semantics of speech acts using the precondition/delete/add list formalism of planning

  • research. Example: request(s, h, φ)

preconditions

s believes h can do φ you don’t ask someone to do something unless you think they can do it s believes h believes h can do φ you don’t ask someone unless they believe they can do it s believes s wants φ you don’t ask someone unless you want it!

postconditions:

h believes s believes s want φ the effect is to make them aware of your desire

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 11 / 56

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SLIDE 34

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Plan-Based Semantics

Cohen & Perrault (1979) defined semantics of speech acts using the precondition/delete/add list formalism of planning

  • research. Example: request(s, h, φ)

preconditions

s believes h can do φ you don’t ask someone to do something unless you think they can do it s believes h believes h can do φ you don’t ask someone unless they believe they can do it s believes s wants φ you don’t ask someone unless you want it!

postconditions:

h believes s believes s want φ the effect is to make them aware of your desire

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 11 / 56

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SLIDE 35

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

BDI connection

Speech acts can be delivered as percepts — introduction to agent architectures AGENT see action next state ENVIRONMENT act sense Likewise percepts for practical reasoning agents (BDI) BDI agents are plan-driven — thus realizing Cohen-Perrault model

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 12 / 56

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SLIDE 36

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

BDI connection

Speech acts can be delivered as percepts — introduction to agent architectures AGENT see action next state ENVIRONMENT act sense Likewise percepts for practical reasoning agents (BDI) BDI agents are plan-driven — thus realizing Cohen-Perrault model

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 12 / 56

slide-37
SLIDE 37

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

BDI connection

Speech acts can be delivered as percepts — introduction to agent architectures AGENT see action next state ENVIRONMENT act sense Likewise percepts for practical reasoning agents (BDI) BDI agents are plan-driven — thus realizing Cohen-Perrault model

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 12 / 56

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SLIDE 38

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Content

1

Agent Communication

2

Agent Communication Languages

3

Ontology Engineering (Noy)

4

Semantic Web (Payne/Tamma/van Harmelen)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 13 / 56

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SLIDE 39

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-40
SLIDE 40

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-41
SLIDE 41

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-42
SLIDE 42

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-43
SLIDE 43

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-44
SLIDE 44

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

KQML and KIF

ACLs: standard formats for the exchange of messages. ARPA knowledge sharing initiative (1990-1994) KQML: knowledge query and manipulation language ‘outer’ language, that defines ‘communicative verbs’, or

  • performatives. Example performatives are:

ask-if (‘is it true that... ’) perform (‘please perform the following action... ’) tell (‘it is true that... ’) reply (‘the answer is ... ’)

KIF: knowledge interchange format ‘inner’ language for expressing message content.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 14 / 56

slide-45
SLIDE 45

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

FIPA ACL

FIPA: second generation, simpler (1998-2002) FIPA’s agent communication language is probably the most widely used now. Basic structure is quite similar to KQML:

performative: 20 performatives in FIPA. inform and request are the two basic performatives: the rest are macros housekeeping: e.g., sender, receiver etc. content: the actual content of the message.

Example:

1

(inform

2

:sender agent1

3

:receiver agent5

4

:content (price good200 150)

5

:language sl

6

:ontology hpl-auction

7

)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 15 / 56

slide-46
SLIDE 46

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

FIPA ACL

FIPA: second generation, simpler (1998-2002) FIPA’s agent communication language is probably the most widely used now. Basic structure is quite similar to KQML:

performative: 20 performatives in FIPA. inform and request are the two basic performatives: the rest are macros housekeeping: e.g., sender, receiver etc. content: the actual content of the message.

Example:

1

(inform

2

:sender agent1

3

:receiver agent5

4

:content (price good200 150)

5

:language sl

6

:ontology hpl-auction

7

)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 15 / 56

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SLIDE 47

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

FIPA ACL

FIPA: second generation, simpler (1998-2002) FIPA’s agent communication language is probably the most widely used now. Basic structure is quite similar to KQML:

performative: 20 performatives in FIPA. inform and request are the two basic performatives: the rest are macros housekeeping: e.g., sender, receiver etc. content: the actual content of the message.

Example:

1

(inform

2

:sender agent1

3

:receiver agent5

4

:content (price good200 150)

5

:language sl

6

:ontology hpl-auction

7

)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 15 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

FIPA ACL

FIPA: second generation, simpler (1998-2002) FIPA’s agent communication language is probably the most widely used now. Basic structure is quite similar to KQML:

performative: 20 performatives in FIPA. inform and request are the two basic performatives: the rest are macros housekeeping: e.g., sender, receiver etc. content: the actual content of the message.

Example:

1

(inform

2

:sender agent1

3

:receiver agent5

4

:content (price good200 150)

5

:language sl

6

:ontology hpl-auction

7

)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 15 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

The FIPA Performatives

performative passing requesting negotiation performing error information information actions handling accept-proposal x agree x cancel x x cfp x confirm x disconfirm x failure x inform x inform-if x inform-ref x not-understood x propose x query-if x query-ref x refuse x reject-proposal x request x request-when x request-whenever x subscribe x De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 16 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Inform and Request Semantics

Semantics defined in two parts:

pre-condition: what must be true for the speech act to

  • succeed. c.f. Cohen and Perrault.

“rational effect” what the sender of the message hopes to bring about.

“inform”: content is a statement, and sender:

Holds that the content is true Intends that the recipient believe the content Does not already believe that the recipient is aware of whether content is true or not.

“request”: content is an action, and sender:

Intends action content to be performed Believes recipient is capable of performing this action Does not believe that recipient already intends to perform action.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 17 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Inform and Request Semantics

Semantics defined in two parts:

pre-condition: what must be true for the speech act to

  • succeed. c.f. Cohen and Perrault.

“rational effect” what the sender of the message hopes to bring about.

“inform”: content is a statement, and sender:

Holds that the content is true Intends that the recipient believe the content Does not already believe that the recipient is aware of whether content is true or not.

“request”: content is an action, and sender:

Intends action content to be performed Believes recipient is capable of performing this action Does not believe that recipient already intends to perform action.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 17 / 56

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SLIDE 52

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Inform and Request Semantics

Semantics defined in two parts:

pre-condition: what must be true for the speech act to

  • succeed. c.f. Cohen and Perrault.

“rational effect” what the sender of the message hopes to bring about.

“inform”: content is a statement, and sender:

Holds that the content is true Intends that the recipient believe the content Does not already believe that the recipient is aware of whether content is true or not.

“request”: content is an action, and sender:

Intends action content to be performed Believes recipient is capable of performing this action Does not believe that recipient already intends to perform action.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 17 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Representing Messages

Agents use a combination of

agent communication language—defines message structure performative, e.g. inform, request (FIPA, KQML) content language—e.g. first order logic + concepts (ontology)

Why this structure?

Sender and receiver have been designed and built at different times by different people—yet they have to interoperate Sender and receiver must be protected from each other Communications may have to be verifiable by third-parties

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 18 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen)

Representing Messages

Agents use a combination of

agent communication language—defines message structure performative, e.g. inform, request (FIPA, KQML) content language—e.g. first order logic + concepts (ontology)

Why this structure?

Sender and receiver have been designed and built at different times by different people—yet they have to interoperate Sender and receiver must be protected from each other Communications may have to be verifiable by third-parties

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 18 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Content

1

Agent Communication

2

Agent Communication Languages

3

Ontology Engineering (Noy) The Ontology Engineering cycle Pizza exercise

4

Semantic Web (Payne/Tamma/van Harmelen)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 19 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Need for Ontologies

In order to be able to communicate, agents must have agreed a common set of terms. An ontology is a formal specification of a set of terms. Gr¨ uber (1993): “Formal, explicit specifications of a shared conceptualisation”

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 20 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Need for Ontologies

In order to be able to communicate, agents must have agreed a common set of terms. An ontology is a formal specification of a set of terms. Gr¨ uber (1993): “Formal, explicit specifications of a shared conceptualisation”

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 20 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What is an ontology?

Depends on subject and use, but common features are: A formal description of (the relevant parts) of a domain: “the nature of things, and the relationships between them” A set of classes (concepts) and their hierarchical relations A set of properties (slots or roles), defining arbitrary relations The same property may be ascribed to several independent classes Constraints — restrictions on properties (type, number) Individuals — some concrete instances of classes

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 21 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Example ontology

Wordnet is a live domain-neutral ontology: http://wordnetweb.princeton.edu/perl/webwn Words are nodes in a network of relationships, for example:

hyponym: more specialized concepts meronym: parts of this concept hypernym: generalized concept holonym: part of something larger etc.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 22 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Example ontology

Wordnet is a live domain-neutral ontology: http://wordnetweb.princeton.edu/perl/webwn Words are nodes in a network of relationships, for example:

hyponym: more specialized concepts meronym: parts of this concept hypernym: generalized concept holonym: part of something larger etc.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 22 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Kinds of ontology

Degrees of formality:

Controlled vocabularies Glossaries Thesauri Informal Is-a hierarchy Formal Is-a hierarchy Formal instances Frames Value restriction General logic constraints

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 23 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What Is “Ontology Engineering”?

Ontology Engineering: Defining terms in the domain and relations among them Defining concepts in the domain (classes) Arranging the concepts in a hierarchy (subclass-superclass hierarchy) Defining which attributes and properties (slots) classes can have and constraints on their values Defining individuals and filling in slot values

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 24 / 56

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SLIDE 68

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What Is “Ontology Engineering”?

Ontology Engineering: Defining terms in the domain and relations among them Defining concepts in the domain (classes) Arranging the concepts in a hierarchy (subclass-superclass hierarchy) Defining which attributes and properties (slots) classes can have and constraints on their values Defining individuals and filling in slot values

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 24 / 56

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SLIDE 69

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What Is “Ontology Engineering”?

Ontology Engineering: Defining terms in the domain and relations among them Defining concepts in the domain (classes) Arranging the concepts in a hierarchy (subclass-superclass hierarchy) Defining which attributes and properties (slots) classes can have and constraints on their values Defining individuals and filling in slot values

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 24 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

What Is “Ontology Engineering”?

Ontology Engineering: Defining terms in the domain and relations among them Defining concepts in the domain (classes) Arranging the concepts in a hierarchy (subclass-superclass hierarchy) Defining which attributes and properties (slots) classes can have and constraints on their values Defining individuals and filling in slot values

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 24 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

slide-73
SLIDE 73

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

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SLIDE 74

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

slide-75
SLIDE 75

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

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SLIDE 76

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

slide-77
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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Why use an ontology?

To share common understanding of the structure of information among people or software agents To enable reuse of domain knowledge To make domain assumptions explicit To separate domain knowledge from the operational knowledge To analyze domain knowledge (through ontology construction) However: Ontologies do not usually succeed in being application independent and often require adaptation for use in a new application.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 25 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology-Development Process

Ideally:

determine scope consider reuse enumerate terms define classes define properties define constraints create instances

In reality — an iterative process with feedback between succeeding phases.

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 26 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

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SLIDE 81

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

slide-83
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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Ontology Engineering versus Object-Oriented Modelling

An ontology: Reflects the structure of the world Is often about structure of concepts Actual physical representation is not an issue An OO class structure: Reflects the structure of the data and code Is usually about behaviour (methods) Describes the physical representation of data (long int, char, etc.)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 27 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Consider Reuse

Why reuse other ontologies? To save the effort To interact with the tools that use other ontologies To use ontologies that have been validated What to re-use?

Upper ontologies

IEEE Standard Upper Ontology (suo.ieee.org) Cyc (www.cyc.com)

General ontologies

DMOZ (www.dmoz.org) WordNet (www.cogsci.princeton.edu/˜wn/)

Taxonomies (special kind of ontology)

Yahoo categories GAMS: Guide to Available Mathematics

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 28 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Define Classes and the Class Hierarchy

A class is a concept in the domain

A class of cheese A class of cheese producers A class of blue cheeses

A class is a collection of elements with similar properties Instances of classes

Casheil (Irish blue cheese)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 29 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Define Classes and the Class Hierarchy

A class is a concept in the domain

A class of cheese A class of cheese producers A class of blue cheeses

A class is a collection of elements with similar properties Instances of classes

Casheil (Irish blue cheese)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 29 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Define Classes and the Class Hierarchy

A class is a concept in the domain

A class of cheese A class of cheese producers A class of blue cheeses

A class is a collection of elements with similar properties Instances of classes

Casheil (Irish blue cheese)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 29 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Slots and Properties

Slots in a class definition describe attributes of instances of the class and relations to other instances Each wine has colour, sugar content, producer, etc. Types of properties:

intrinsic properties: aroma and colour of cheese extrinsic properties: name and price of cheese parts: ingredients of a particular cheese

  • bjects: producer of cheese

Simple and complex properties:

simple properties (attributes): contain primitive values (strings, numbers) complex properties: contain (or point to) other objects (e.g., a manufacturer)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 30 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Slots and Properties

Slots in a class definition describe attributes of instances of the class and relations to other instances Each wine has colour, sugar content, producer, etc. Types of properties:

intrinsic properties: aroma and colour of cheese extrinsic properties: name and price of cheese parts: ingredients of a particular cheese

  • bjects: producer of cheese

Simple and complex properties:

simple properties (attributes): contain primitive values (strings, numbers) complex properties: contain (or point to) other objects (e.g., a manufacturer)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 30 / 56

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SLIDE 97

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Slots and Properties

Slots in a class definition describe attributes of instances of the class and relations to other instances Each wine has colour, sugar content, producer, etc. Types of properties:

intrinsic properties: aroma and colour of cheese extrinsic properties: name and price of cheese parts: ingredients of a particular cheese

  • bjects: producer of cheese

Simple and complex properties:

simple properties (attributes): contain primitive values (strings, numbers) complex properties: contain (or point to) other objects (e.g., a manufacturer)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 30 / 56

slide-98
SLIDE 98

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Slots and Properties

Slots in a class definition describe attributes of instances of the class and relations to other instances Each wine has colour, sugar content, producer, etc. Types of properties:

intrinsic properties: aroma and colour of cheese extrinsic properties: name and price of cheese parts: ingredients of a particular cheese

  • bjects: producer of cheese

Simple and complex properties:

simple properties (attributes): contain primitive values (strings, numbers) complex properties: contain (or point to) other objects (e.g., a manufacturer)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 30 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

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SLIDE 100

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

slide-101
SLIDE 101

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

slide-102
SLIDE 102

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

slide-103
SLIDE 103

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

slide-104
SLIDE 104

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Slot and Class Inheritance

A subclass inherits all the slots from the superclass

If a cheese has a name and characteristic, a blue cheese also has a name and characteristic

If a class has multiple superclasses, it inherits slots from all

  • f them

Roquefort is both a sheep cheese and a blue cheese. It inherits “milk source: sheep” from the former and “culture: penicillium” from the latter

Domain of a slot: the class (or classes) of instances that can have the slot Range of a slot: the class (or classes) to which slot values belong

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 31 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Property Constraints

Property constraints (facets) describe or limit the set of possible values for a slot

The name of a cheese is a string The cheese producer is an instance of Dairy A dairy has exactly one (physical) location

Common Facets

Slot cardinality: the number of values a slot has; exactly n, at least 1, at least 0 (= optional) Slot value type: the type of values a slot has; string, number, boolean, enumerated type, complex type (another class) Minimum and maximum value: a range of values for a numeric slot Default value: the value a slot has unless explicitly specified

  • therwise

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 32 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Property Constraints

Property constraints (facets) describe or limit the set of possible values for a slot

The name of a cheese is a string The cheese producer is an instance of Dairy A dairy has exactly one (physical) location

Common Facets

Slot cardinality: the number of values a slot has; exactly n, at least 1, at least 0 (= optional) Slot value type: the type of values a slot has; string, number, boolean, enumerated type, complex type (another class) Minimum and maximum value: a range of values for a numeric slot Default value: the value a slot has unless explicitly specified

  • therwise

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 32 / 56

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SLIDE 107

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Classes and a Class Hierarchy

There is no single correct class hierarchy But there are some guidelines... The question to ask is:

”Is each instance of the subclass an instance of its superclass?”

Multiple Inheritance

A class can have more than one superclass A subclass inherits slots and facet restrictions from all the parents Different systems resolve conflicts differently

Disjoint Classes

Classes are disjoint if they cannot have common instances Disjoint classes cannot have any common subclasses either

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 33 / 56

slide-108
SLIDE 108

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Classes and a Class Hierarchy

There is no single correct class hierarchy But there are some guidelines... The question to ask is:

”Is each instance of the subclass an instance of its superclass?”

Multiple Inheritance

A class can have more than one superclass A subclass inherits slots and facet restrictions from all the parents Different systems resolve conflicts differently

Disjoint Classes

Classes are disjoint if they cannot have common instances Disjoint classes cannot have any common subclasses either

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 33 / 56

slide-109
SLIDE 109

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Classes and a Class Hierarchy

There is no single correct class hierarchy But there are some guidelines... The question to ask is:

”Is each instance of the subclass an instance of its superclass?”

Multiple Inheritance

A class can have more than one superclass A subclass inherits slots and facet restrictions from all the parents Different systems resolve conflicts differently

Disjoint Classes

Classes are disjoint if they cannot have common instances Disjoint classes cannot have any common subclasses either

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 33 / 56

slide-110
SLIDE 110

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Classes and a Class Hierarchy

There is no single correct class hierarchy But there are some guidelines... The question to ask is:

”Is each instance of the subclass an instance of its superclass?”

Multiple Inheritance

A class can have more than one superclass A subclass inherits slots and facet restrictions from all the parents Different systems resolve conflicts differently

Disjoint Classes

Classes are disjoint if they cannot have common instances Disjoint classes cannot have any common subclasses either

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 33 / 56

slide-111
SLIDE 111

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Defining Classes and a Class Hierarchy

There is no single correct class hierarchy But there are some guidelines... The question to ask is:

”Is each instance of the subclass an instance of its superclass?”

Multiple Inheritance

A class can have more than one superclass A subclass inherits slots and facet restrictions from all the parents Different systems resolve conflicts differently

Disjoint Classes

Classes are disjoint if they cannot have common instances Disjoint classes cannot have any common subclasses either

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 33 / 56

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SLIDE 112

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

slide-113
SLIDE 113

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

slide-114
SLIDE 114

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

slide-115
SLIDE 115

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

slide-116
SLIDE 116

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

slide-117
SLIDE 117

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Inverse Slots

Example: Maker and Product are inverse slots Inverse slots contain redundant information, but Allow acquisition of the information in either direction Enable additional verification Allow presentation of information in both directions Actual implementation differs from system to system

Are both values stored? When are the inverse values filled in? What happens if we change the link to an inverse slot?

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 34 / 56

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SLIDE 118

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Limiting the Scope

An ontology should not contain all the possible information about the domain No need to specialize or generalize more than the application requires No need to include all possible properties of a class

Only the most salient properties Only the properties that the applications require

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 35 / 56

slide-119
SLIDE 119

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Limiting the Scope

An ontology should not contain all the possible information about the domain No need to specialize or generalize more than the application requires No need to include all possible properties of a class

Only the most salient properties Only the properties that the applications require

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 35 / 56

slide-120
SLIDE 120

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Limiting the Scope

An ontology should not contain all the possible information about the domain No need to specialize or generalize more than the application requires No need to include all possible properties of a class

Only the most salient properties Only the properties that the applications require

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 35 / 56

slide-121
SLIDE 121

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Exercise: the pizza ontology

Groups: 3–4 people Objective: to start the process of building an ontology to describe forms of pizza Plan: Decide whether to work top-down or bottom-up Apply methodology outlined on

slide 24 [10 mins]

Discussion [5 mins]

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 36 / 56

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SLIDE 122

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Exercise: the pizza ontology

Groups: 3–4 people Objective: to start the process of building an ontology to describe forms of pizza Plan: Decide whether to work top-down or bottom-up Apply methodology outlined on

slide 24 [10 mins]

Discussion [5 mins]

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 36 / 56

slide-123
SLIDE 123

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) The Ontology Engineering cycle Pizza exercise

Exercise: the pizza ontology

Groups: 3–4 people Objective: to start the process of building an ontology to describe forms of pizza Plan: Decide whether to work top-down or bottom-up Apply methodology outlined on

slide 24 [10 mins]

Discussion [5 mins]

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 36 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Content

1

Agent Communication

2

Agent Communication Languages

3

Ontology Engineering (Noy)

4

Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 37 / 56

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SLIDE 125

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Agents and the Web

Web content is mostly intended for human readers Mostly inaccessible to programs Keyword-based search engines have programmatic interfaces, but have limitations:

High recall, low precision Low or no recall Results are highly sensitive to vocabulary Results are single web pages Human involvement is necessary to interpret and combine results Results of web searches are not readily accessible by other software tools

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 38 / 56

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SLIDE 126

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Agents and the Web

Web content is mostly intended for human readers Mostly inaccessible to programs Keyword-based search engines have programmatic interfaces, but have limitations:

High recall, low precision Low or no recall Results are highly sensitive to vocabulary Results are single web pages Human involvement is necessary to interpret and combine results Results of web searches are not readily accessible by other software tools

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 38 / 56

slide-127
SLIDE 127

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Agents and the Web

Web content is mostly intended for human readers Mostly inaccessible to programs Keyword-based search engines have programmatic interfaces, but have limitations:

High recall, low precision Low or no recall Results are highly sensitive to vocabulary Results are single web pages Human involvement is necessary to interpret and combine results Results of web searches are not readily accessible by other software tools

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 38 / 56

slide-128
SLIDE 128

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From Web to Semantic Web

The meaning of web content is not machine accessible: lack of semantics It is simply difficult, for a machine, to distinguish between different meanings:

I am a lecturer of computer science. I am an assistant professor of computer science

Step 1: Represent web content in a form that is more easily machine-processable Step 2: Use intelligent techniques to take advantage of these representations The Semantic Web should gradually evolve from existing Web

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 39 / 56

slide-129
SLIDE 129

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From Web to Semantic Web

The meaning of web content is not machine accessible: lack of semantics It is simply difficult, for a machine, to distinguish between different meanings:

I am a lecturer of computer science. I am an assistant professor of computer science

Step 1: Represent web content in a form that is more easily machine-processable Step 2: Use intelligent techniques to take advantage of these representations The Semantic Web should gradually evolve from existing Web

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 39 / 56

slide-130
SLIDE 130

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From Web to Semantic Web

The meaning of web content is not machine accessible: lack of semantics It is simply difficult, for a machine, to distinguish between different meanings:

I am a lecturer of computer science. I am an assistant professor of computer science

Step 1: Represent web content in a form that is more easily machine-processable Step 2: Use intelligent techniques to take advantage of these representations The Semantic Web should gradually evolve from existing Web

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 39 / 56

slide-131
SLIDE 131

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From Web to Semantic Web

The meaning of web content is not machine accessible: lack of semantics It is simply difficult, for a machine, to distinguish between different meanings:

I am a lecturer of computer science. I am an assistant professor of computer science

Step 1: Represent web content in a form that is more easily machine-processable Step 2: Use intelligent techniques to take advantage of these representations The Semantic Web should gradually evolve from existing Web

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 39 / 56

slide-132
SLIDE 132

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From Web to Semantic Web

The meaning of web content is not machine accessible: lack of semantics It is simply difficult, for a machine, to distinguish between different meanings:

I am a lecturer of computer science. I am an assistant professor of computer science

Step 1: Represent web content in a form that is more easily machine-processable Step 2: Use intelligent techniques to take advantage of these representations The Semantic Web should gradually evolve from existing Web

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 39 / 56

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SLIDE 133

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Semantic Web Enabled Knowledge Management

Objectives:

Knowledge will be organized in conceptual spaces according to its meaning Automated tools for maintenance and knowledge discovery Semantic query answering over several documents

How?

Explicit metadata Ontologies Logic and inference Agents

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 40 / 56

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SLIDE 134

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Semantic Web Enabled Knowledge Management

Objectives:

Knowledge will be organized in conceptual spaces according to its meaning Automated tools for maintenance and knowledge discovery Semantic query answering over several documents

How?

Explicit metadata Ontologies Logic and inference Agents

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 40 / 56

slide-135
SLIDE 135

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From HTML to XML

Humans have little problem understanding HTML content Software agents do:

How distinguish the name of the course from the name of the lecturer? How determine the course aims? How to infer to follow the link to the lecturer’s home page to find the location of their office?

A better representation might be:

1

<department>

2

<courseOffered>CM30174</courseOffered>

3

<departmentName>Computer Science</departmentName>

4

<staff>

5

<lecturer>Marina De Vos</lecturer>

6

<lecturer>Julian Padget</lecturer>

7

<teachingAssistant>who?</teachingAssistant>

8

</staff>

9

</department>

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 41 / 56

slide-136
SLIDE 136

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From HTML to XML

Humans have little problem understanding HTML content Software agents do:

How distinguish the name of the course from the name of the lecturer? How determine the course aims? How to infer to follow the link to the lecturer’s home page to find the location of their office?

A better representation might be:

1

<department>

2

<courseOffered>CM30174</courseOffered>

3

<departmentName>Computer Science</departmentName>

4

<staff>

5

<lecturer>Marina De Vos</lecturer>

6

<lecturer>Julian Padget</lecturer>

7

<teachingAssistant>who?</teachingAssistant>

8

</staff>

9

</department>

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 41 / 56

slide-137
SLIDE 137

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

From HTML to XML

Humans have little problem understanding HTML content Software agents do:

How distinguish the name of the course from the name of the lecturer? How determine the course aims? How to infer to follow the link to the lecturer’s home page to find the location of their office?

A better representation might be:

1

<department>

2

<courseOffered>CM30174</courseOffered>

3

<departmentName>Computer Science</departmentName>

4

<staff>

5

<lecturer>Marina De Vos</lecturer>

6

<lecturer>Julian Padget</lecturer>

7

<teachingAssistant>who?</teachingAssistant>

8

</staff>

9

</department>

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 41 / 56

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Web Ontology Languages

RDF Schema:

RDF is a data model for objects and relations between them RDF Schema is a vocabulary description language (classes, slots, etc.) Describes properties and classes of RDF resources Provides semantics for generalization hierarchies of properties and classes

The Web Ontology Language (OWL):

A richer ontology language Relations between classes relations, e.g., disjointness Cardinality, e.g. “exactly one” Richer typing of properties Characteristics of properties (e.g., symmetry)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 42 / 56

slide-139
SLIDE 139

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Web Ontology Languages

RDF Schema:

RDF is a data model for objects and relations between them RDF Schema is a vocabulary description language (classes, slots, etc.) Describes properties and classes of RDF resources Provides semantics for generalization hierarchies of properties and classes

The Web Ontology Language (OWL):

A richer ontology language Relations between classes relations, e.g., disjointness Cardinality, e.g. “exactly one” Richer typing of properties Characteristics of properties (e.g., symmetry)

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 42 / 56

slide-140
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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Three Species of OWL

OWL Full:

All the OWL languages primitives Arbitrary combination with RDF and RDF Schema Fully upward-compatible with RDF Powerful but undecidable

OWL DL (Description Logic):

A sublanguage of OWL Full: may not apply constructors to constructors Efficient reasoning support: correspondance with description logic Not every RDF document is a valid OWL DL document

OWL Lite:

A subset of OLW DL ’s constructors: excludes enumerated classes, disjointness statements and arbitrary cardinality Easier to understand and to implement Expressivity significantly restricted

De Vos/Padget (Bath/CS) CM30174/Communication October 18, 2011 43 / 56

slide-141
SLIDE 141

Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Three Species of OWL

OWL Full:

All the OWL languages primitives Arbitrary combination with RDF and RDF Schema Fully upward-compatible with RDF Powerful but undecidable

OWL DL (Description Logic):

A sublanguage of OWL Full: may not apply constructors to constructors Efficient reasoning support: correspondance with description logic Not every RDF document is a valid OWL DL document

OWL Lite:

A subset of OLW DL ’s constructors: excludes enumerated classes, disjointness statements and arbitrary cardinality Easier to understand and to implement Expressivity significantly restricted

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Three Species of OWL

OWL Full:

All the OWL languages primitives Arbitrary combination with RDF and RDF Schema Fully upward-compatible with RDF Powerful but undecidable

OWL DL (Description Logic):

A sublanguage of OWL Full: may not apply constructors to constructors Efficient reasoning support: correspondance with description logic Not every RDF document is a valid OWL DL document

OWL Lite:

A subset of OLW DL ’s constructors: excludes enumerated classes, disjointness statements and arbitrary cardinality Easier to understand and to implement Expressivity significantly restricted

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Representing Ontologies: RDF 1/2

Resource Description Format (RDF), where terms take the form of triples

  • bject, attribute, value

XML syntax:

1

<rdf:Description rdf:about="#person-05">

2

<authorOf>ISBN...</authorOf>

3

</rdf:Description>

person-05 ISBN ... authorOf

Object denotes a web resource Value is another object

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Representing Ontologies: RDF 1/2

Resource Description Format (RDF), where terms take the form of triples

  • bject, attribute, value

XML syntax:

1

<rdf:Description rdf:about="#person-05">

2

<authorOf>ISBN...</authorOf>

3

</rdf:Description>

person-05 ISBN ... authorOf

Object denotes a web resource Value is another object

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Representing Ontologies: RDF 1/2

Resource Description Format (RDF), where terms take the form of triples

  • bject, attribute, value

XML syntax:

1

<rdf:Description rdf:about="#person-05">

2

<authorOf>ISBN...</authorOf>

3

</rdf:Description>

person-05 ISBN ... authorOf

Object denotes a web resource Value is another object

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Representing Ontologies: RDF 1/2

Resource Description Format (RDF), where terms take the form of triples

  • bject, attribute, value

XML syntax:

1

<rdf:Description rdf:about="#person-05">

2

<authorOf>ISBN...</authorOf>

3

</rdf:Description>

person-05 ISBN ... authorOf

Object denotes a web resource Value is another object

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Representing Ontologies: RDF 2/2

Triples can be linked Data model = graph

person-05 ISBN ... ISBN ... MIT Press authorOf authorOf publishedBy p u b l i s h e d B y

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Representing Ontologies: RDF 2/2

Triples can be linked Data model = graph

person-05 ISBN ... ISBN ... MIT Press authorOf authorOf publishedBy p u b l i s h e d B y

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RDF Schema

Defines vocabulary for RDF Organizes vocabulary in a typed hierarchy

Class, subClassOf, type Property, subPropertyOf domain, range

Person Author Reader communicatesTo Frank Lynda subClassOf s u b C l a s s O f domain range type type communicatesTo

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RDF Schema

Defines vocabulary for RDF Organizes vocabulary in a typed hierarchy

Class, subClassOf, type Property, subPropertyOf domain, range

Person Author Reader communicatesTo Frank Lynda subClassOf s u b C l a s s O f domain range type type communicatesTo

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RDF(S) Semantics

RDF(S) has a (very small) formal semantics:

X R Y + R domain T ⇒ X IsOfType T X R Y + R range T ⇒ Y IsOfType T T1 SubClassOf T2 + T2 SubClassOf T3 ⇒ T1 SubClassOf T3 X IsOfType T1 + T1 SubClassOf T2 ⇒ X IsOfType T2

Defines what other statements are implied by a given set

  • f RDF(S) statements

Described as simple entailments with acceptable practical complexity, for example:

Aspirin isOfType Painkiller + Painkiller subClassOf Drug ⇒ Aspirin isOfType Drug Aspirin alleviates Headache + alleviates range Symptom ⇒ Headache isOfType Symptom

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

RDF(S) Semantics

RDF(S) has a (very small) formal semantics:

X R Y + R domain T ⇒ X IsOfType T X R Y + R range T ⇒ Y IsOfType T T1 SubClassOf T2 + T2 SubClassOf T3 ⇒ T1 SubClassOf T3 X IsOfType T1 + T1 SubClassOf T2 ⇒ X IsOfType T2

Defines what other statements are implied by a given set

  • f RDF(S) statements

Described as simple entailments with acceptable practical complexity, for example:

Aspirin isOfType Painkiller + Painkiller subClassOf Drug ⇒ Aspirin isOfType Drug Aspirin alleviates Headache + alleviates range Symptom ⇒ Headache isOfType Symptom

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

RDF(S) Semantics

RDF(S) has a (very small) formal semantics:

X R Y + R domain T ⇒ X IsOfType T X R Y + R range T ⇒ Y IsOfType T T1 SubClassOf T2 + T2 SubClassOf T3 ⇒ T1 SubClassOf T3 X IsOfType T1 + T1 SubClassOf T2 ⇒ X IsOfType T2

Defines what other statements are implied by a given set

  • f RDF(S) statements

Described as simple entailments with acceptable practical complexity, for example:

Aspirin isOfType Painkiller + Painkiller subClassOf Drug ⇒ Aspirin isOfType Drug Aspirin alleviates Headache + alleviates range Symptom ⇒ Headache isOfType Symptom

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Why RDF and OWL are useful

RDF

uniform representation easily generated semantic annotation straightforward “solves” communication syntax problem

OWL(-S)

  • ntology construction

describe semantic properties of concepts describe semantic properties of (web/agent) services

inputs, outputs, preconditions, effects (IOPE) semantic matchmaking

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Agent Communication Agent Communication Languages Ontology Engineering (Noy) Semantic Web (Payne/Tamma/van Harmelen) Agents and the Web Web Ontology Languages

Why RDF and OWL are useful

RDF

uniform representation easily generated semantic annotation straightforward “solves” communication syntax problem

OWL(-S)

  • ntology construction

describe semantic properties of concepts describe semantic properties of (web/agent) services

inputs, outputs, preconditions, effects (IOPE) semantic matchmaking

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Summary

Agent Communication Agent Communication Languages Ontology Engineering The Semantic Web and Web Ontology Languages

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Summary

Agent Communication Agent Communication Languages Ontology Engineering The Semantic Web and Web Ontology Languages

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Summary

Agent Communication Agent Communication Languages Ontology Engineering The Semantic Web and Web Ontology Languages

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Summary

Agent Communication Agent Communication Languages Ontology Engineering The Semantic Web and Web Ontology Languages

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Background Reading (optional)

Chs 6, 7, 8 of [Wooldridge, 2009]. Wooldridge, M. (2009). An introduction to multiagent systems (second edition). Wiley. ISBN: 978-0-470-51946-2. Additional resources include:

Prot´ eg´ e: http://protege.stanford.edu/ OntoWeb: http://www.ontoweb.org/ The Semantic Web: http://www.w3.org/2001/sw/ The Co-ode project: http://www.co-ode.org

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