Multi-Agent Oriented Programming Introduction The JaCaMo Platform - - PowerPoint PPT Presentation

Multi-Agent Oriented Programming

– Introduction –

The JaCaMo Platform

• O. Boissier1

R.H. Bordini2 J.F. Hübner3

• A. Ricci4
• 1. Ecole Nationale Supérieure des Mines (ENSMSE), Saint Etienne, France

2 Pontificia Universidade Catolica do Rio Grande do Sul (PUCRS), Porto Alegre, Brazil

• 3. Federal University of Santa Catarina (UFSC), Florianópolis, Brazil
• 4. University of Bologna (UNIBO), Bologna, Italy

September 2015

Introduction MAOP JaCaMo Experiences Conclusion

In collaboration with

J.S. Sichman, Universidade de São Paulo - LTI-PCS, São Paulo, Brazil (jaime.sichman@poli.usp.br)

• G. Picard, ENS Mines St-Etienne, France (gauthier.picard@emse.fr)
• M. Hannoun, B. Gâteau, G. Danoy, R. Kitio, C. Persson, R. Yaich,

ENS Mines St-Etienne, France, L. Coutinho Brazil

• M. Piunti, A. Santi, Università degli studi di Bologna - DEIS, Bologna,

Italy (a.ricci@unibo.it)

• A. Ciortea, A. Sorici, Politehnica University of Bucharest, Romania

MAOP 2 / 74

Outline

1

Introduction

2

Multi-Agent Oriented Programming (MAOP)

3

MAOP Perspective: the JaCaMo Platform

4

MAOP Experiences

5

Conclusions and Perspectives

Introduction MAOP JaCaMo Experiences Conclusion

MAS Conceptual framework / Dimensions

BELIEFS GOALS PLANS INTERNAL EVENTS ACTIONS PERCEPTIONS

AGENTS

MISSIONS ROLES DEONTIC RELATIONS GROUPS NORMS SANCTIONS REWARDS

ORGANISATIONS

RESOURCES SERVICES OBJECTS

ENVIRONMENTS

COMMUNICATION LANGUAGES INTERACTION PROCOLS SPEECH ACTS

INTERACTIONS

TOPOLOGY TOOLS

• cf. VOWELS [Demazeau, 1995,

Demazeau, 1997] Agents: abstractions for the definition of the decision/reasoning entities architectures Environment: abstractions for structuring resources, processing entities shared among the agents Interaction: abstractions for structuring interactions among entities Organisation: abstractions for structuring and ruling the sets of entities within the MAS ❀ A rich set of abstractions for capturing applications complexity!

MAOP 4 / 74

Introduction MAOP JaCaMo Experiences Conclusion

MAS Conceptual framework / Dynamics

BELIEFS GOALS PLANS INTERNAL EVENTS ACTIONS PERCEPTIONS

AGENTS

MISSIONS ROLES DEONTIC RELATIONS GROUPS NORMS SANCTIONS REWARDS

ORGANISATIONS

RESOURCES SERVICES OBJECTS

ENVIRONMENTS

COMMUNICATION LANGUAGES INTERACTION PROCOLS SPEECH ACTS

INTERACTIONS

TOPOLOGY TOOLS

Each dimension has its own dynamics Dynamics may be interlaced into bottom-up / top-down global cycles Coordination of these dynamics may be programmed into one or several dimensions [Boissier, 2003] ❀ A rich palette of possible dynamics & coordination!!

MAOP 5 / 74

Introduction MAOP JaCaMo Experiences Conclusion

MAS Programming

AOP EOP IOP OOP

BELIEFS GOALS PLANS INTERNAL EVENTS ACTIONS PERCEPTIONS

AGENTS

MISSIONS ROLES DEONTIC RELATIONS GROUPS NORMS SANCTIONS REWARDS

ORGANISATIONS

RESOURCES SERVICES OBJECTS

ENVIRONMENTS

COMMUNICATION LANGUAGES INTERACTION PROCOLS SPEECH ACTS

INTERACTIONS

TOPOLOGY TOOLS

Agent Oriented Programming [Shoham, 1993] Environment Oriented Programming [Ricci et al., 2011] Interaction Oriented Programming [Huhns, 2001] Organisation Oriented Programming [Pynadath et al., 1999] In these approaches, some dimensions lose their control & visibility! Integrating the dimensions into one programming platform is not so easy! Examples of Multi-Agent Oriented Programming Platforms: Volcano platform [Ricordel and Demazeau, 2002], MASK platform [Occello et al., 2004], MASQ [Stratulat et al., 2009], extending AGRE and AGREEN, Situated E-Institutions [Campos et al., 2009], ...

MAOP 6 / 74

Introduction MAOP JaCaMo Experiences Conclusion

MAS Programming

AOP EOP IOP OOP

BELIEFS GOALS PLANS INTERNAL EVENTS ACTIONS PERCEPTIONS

AGENTS

MISSIONS ROLES DEONTIC RELATIONS GROUPS NORMS SANCTIONS REWARDS

ORGANISATIONS

RESOURCES SERVICES OBJECTS

ENVIRONMENTS

COMMUNICATION LANGUAGES INTERACTION PROCOLS SPEECH ACTS

INTERACTIONS

TOPOLOGY TOOLS

Agent Oriented Programming [Shoham, 1993] Environment Oriented Programming [Ricci et al., 2011] Interaction Oriented Programming [Huhns, 2001] Organisation Oriented Programming [Pynadath et al., 1999]

Challenge

Shifting from an A/E/I/O oriented approaches to a Multi-Agent Oriented approach keeping alive the concepts, dynamics and coordinations of the A, E, I and O dimensions

MAOP 6 / 74

Outline

1

Introduction

2

Multi-Agent Oriented Programming (MAOP) MAOP Meta-Model Focus on Agent meta-model Focus on Environment meta-model Focus on Organisation meta-model Synthesis

3

MAOP Perspective: the JaCaMo Platform

4

MAOP Experiences

5

Conclusions and Perspectives

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Seamless Integration of A & E & I & O

Artifact Operation Agent Workspace Environment Manual has use generate update create dispose link, unlink consult create join quit Belief Goal Plan External Action Internal Action create delete adopt leave create delete commit leave focus, unfocus primitive operations composition association dependency concept mapping Trigger event Observable Property dimension border Action Observable Event achieve Environment Dimension Agent Dimension Organisation Dimension

Cardinalities are not represented

Content Message SpeechAct Interaction Dimension send receive focus, unfocus Mission Role Group Social Scheme Norm Goal Link Organisation

JaCaMo Meta-model [Boissier et al., 2011], based on Cartago [Ricci et al., 2009b], Jason [Bordini et al., 2007], M OISE [Hübner et al., 2009a] meta-models

MAOP 8 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Agent meta-model

Agent Belief Goal Plan External Action Internal Action agent's actions composition association dependency concept mapping Trigger event dimension border Action Agent Dimension Cardinalities are not represented

Based on Jason meta-models [Bordini et al., 2007]

MAOP 9 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Agent example I

Example (Giacomo Agent Code)

!have_a_house. // Initial Goal /* Plan */ +!have_a_house <- !contract; !execute.

Example (companyX Agent Code)

my_price(300). // initial belief /* plans for contracting phase */ // there is a new value for current bid +currentBid(V) : not i_am_winning(Art) & // I am not the current winner my_price(P) & P < V // I can offer a better bid <- .bid( P ). // place my bid offering a cheaper service

MAOP 10 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Agent & Agent Interaction meta-model

Agent Belief Goal Plan External Action Internal Action Trigger event Action Agent Dimension Content Message SpeechAct Interaction Dimension MAOP 11 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Agent’s dynamics

SI

Events External Event Selected

S

E

Beliefs to Add and Delete Relevant Plans New Plan Push Intention Updated

O

S

Applicable Plans Means Intended Events External

Plan Library Events

Internal Events

3

checkMail Intentions

Execute Intention

...

New New 9

Belief Base

New Intention Percepts

act

Selected Intention Intentions Action Percepts

1 2

BUF

10

Events Context Check Event Unify

BRF

Beliefs

Agent

sendMsg

Beliefs

8

Messages Plans

perceive

7 5 6

Actions Beliefs

Suspended Intentions

(Actions and Msgs)

...

.send

SocAcc

4

Messages Messages

S

M

MAOP 12 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Environment meta-model

Artifact Operation Workspace Environment Manual has generate update Observable Property Observable Event

Based on A&A meta-model [Omicini et al., 2008]

MAOP 13 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Auction Artifact

Example

public class AuctionArt extends Artifact { @OPERATION void init(String taskDs, int maxValue) { defineObsProperty("task”,taskDs); // task description defineObsProperty("maxValue”, maxValue); // max. value // current best bid (lower service price) defineObsProperty("currentBid”, maxValue); // current winning agent ID defineObsProperty("currentWinner”, "no_winner"); } // places a new bid for doing the service for price p // (used by company agents to bid in a given auction) @OPERATION void bid(double bidValue) { ObsProperty opCurrentValue = getObsProperty("currentBid"); ObsProperty opCurrentWinner = getObsProperty("currentWinner"); if (bidValue < opCurrentValue.intValue()) {

• pCurrentValue.updateValue(bidValue);
• pCurrentWinner.updateValue(getOpUserName());

} } }

MAOP 14 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

A & E Interaction meta-model

Artifact Operation Agent Workspace Environment Manual has use generate update create dispose link, unlink consult create join quit Belief Goal Plan External Action Internal Action focus, unfocus Trigger event Observable Property Action Observable Event Environment Dimension Agent Dimension focus, unfocus MAOP 15 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Giacomo Agent Code I

Example

!have_a_house. // Initial Goal /* Plans */ +!have_a_house <- !contract; !execute. +!contract <- !create_auction_artifacts; !wait_for_bids. +!create_auction_artifacts <- !create_auction_artifact("SitePreparation", 2000); !create_auction_artifact("Floors", 1000); !create_auction_artifact("Walls", 1000); !create_auction_artifact("Roof", 2000); !create_auction_artifact("WindowsDoors", 2500); !create_auction_artifact("Plumbing", 500); !create_auction_artifact("ElectricalSystem", 500); !create_auction_artifact("Painting", 1200).

MAOP 16 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Giacomo Agent Code II

Example

+!create_auction_artifact(Task,MaxPrice) <- .concat("auction_for_",Task,ArtName); makeArtifact(ArtName, "tools.AuctionArt", [Task, MaxPrice], ArtId); focus(ArtId).

• !create_auction_artifact(Task,MaxPrice)[error_code(Code)]

<- .print("Error creating artifact ", Code). +!wait_for_bids <- println("Waiting the bids for 5 seconds..."); .wait(5000); // use intern deadline of 5 sec to close auctions !show_winners. +!show_winners <- for ( currentWinner(Ag)[artifact_id(ArtId)] ) { ?currentBid(Price)[artifact_id(ArtId)]; // check current bid ?task(Task)[artifact_id(ArtId)]; // and task it is for println("Winner of task ", Task," is ", Ag, " for ", Price) }.

MAOP 17 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

companyA Agent Code I

Example

my_price(1500). // initial belief !discover_art("auction_for_Plumbing"). // initial goal i_am_winning(Art) :- .my_name(Me) & currentWinner(Me)[artifact_id(Art)]. /* plans for contracting phase */ +!discover_art(ToolName) <- joinWorkspace("HouseBuildingWsp"); lookupArtifact(ToolName,ToolId); focus(ToolId). // there is a new value for current bid +currentBid(V)[artifact_id(Art)] : not i_am_winning(Art) & // I am not the current winner my_price(P) & P < V // I can offer a better bid <- bid(math.max(V-150, P))[artifact_id(Art)]. /* plans for execution phase */ ...

MAOP 18 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Environment’s dynamics

Artifact life-cycle Creation/Deletion Activation/Execution/Fail or Success/Deactivation of an Operation Linking / Unlinking Workspace life-cycle Creation/Deletion of a workspace Creation/Deletion of Artifacts Creation/Deletion & Entry/Exit of Agents

MAOP 19 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Outcomes of A & E Integration

Agents with dynamic action repertoire, extended/reshaped by agents themselves Uniform implementation of any mechanisms (e.g. coordination mechanism) in terms of actions/percepts

No need to extend agents with special purpose primitives

Exploiting a new type of agent modularity, based on externalization [Ricci et al., 2009a]

MAOP 20 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Organisation meta-model

Mission Role Group Norm Goal Link Organisation Social Scheme

Simplified M OISE meta-model [Hübner et al., 2009a]

MAOP 21 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Example: Organisation Structural Specification

Graphical representation of M OISE Struct. Spec.

MAOP 22 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Example: Organisation Functional Specification

Graphical representation of M OISE Func. Spec.

MAOP 23 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Example: Organisation Normative Specification

norm modality role mission / goals n1 Obl house_owner house built n2 Obl site_prep_contractor site prepared n3 Obl bricklayer floors laid, walls built n4 Obl roofer roof built n5 Obl window_fitter windows fitted n6 Obl door_fitter doors fitted n7 Obl plumber plumbing installed n8 Obl electrician electrical system installed n9 Obl painter interior painted, exterior painted Simplified representation of M OISE Norm. Spec.

MAOP 24 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

A & E & O Interaction meta-model

Artifact Operation Agent Workspace Environment Manual has use generate update create dispose link, unlink consult create join quit Belief Goal Plan External Action Internal Action create delete adopt leave create delete commit leave focus, unfocus primitive operations composition association dependency concept mapping Trigger event Observable Property dimension border Action Observable Event achieve Environment Dimension Agent Dimension Organisation Dimension

Cardinalities are not represented

Content Message SpeechAct Interaction Dimension send receive focus, unfocus Mission Role Group Social Scheme Norm Goal Link Organisation

Based on Cartago [Ricci et al., 2009b], Jason [Bordini et al., 2007], M OISE [Hübner et al., 2009a] meta-models

MAOP 25 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

A & O Integration

Instrumenting Organisation Management by dedicated Organisational Artifacts

Mapping of the organisational state onto artifacts computational state Encapsulation of organisational functionalities by suitably designed artifacts providing organisational operations

❀ Reification of organisation management actions/perceptions by actions/percepts on the artifacts Extensible set of organisational artifacts:

Openness Management Artifact [Kitio, 2011] Reorganisation Artifact [Sorici, 2011] Evaluation Artifact (kind-of reputation artifact) [Hübner et al., 2009b] Communication management Artifact [Ciortea, 2011]

MAOP 26 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

A & O Integration (2)

role mission scheme group

Belief Base Intentions Org. Reasoning Mechanisms Plan Library

• p2
• p1
• p2
• p1
• p2
• p1

Org. Artifacts Env. Artifacts

Exploit the uniform access to artifacts ❀ Agents may be aware of the Organisation by the way of:

• rganisational events
• rganisational actions

❀ Agents can reason on the

• rganisation:

to achieve organisational goals by developing organisational plans

MAOP 27 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Example

Example (Adoption of Role) ... +!discover_art(ToolName) <- joinWorkspace("HouseBuildingWsp"); lookupArtifact(ToolName,ToolId); focus(ToolId). +!contract("SitePreparation",GroupBoardId) <- adoptRole(site_prep_contractor) focus(GroupBoardId). +!site_prepared <- ... // actions to prepare the site..

MAOP 28 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

E & O Integration

role mission scheme group

• p2
• p1
• Org. Artifacts

Env. Artifacts

count-as count-as

• p2
• p1
• p2
• p1

enact

• Env. Artifacts provide operations
• n shared resources
• Org. Artifacts provide
• rganisational operations

Both artifacts bound by count-as, enact constitutive rules [Piunti et al., 2009, de Brito et al., 2012] ❀ Org-agnostic agents may indirectly act on the organisation ❀ Environment can act on the

• rganisation

❀ Organisation is embodied, situated in the environment

MAOP 29 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Count-as rules [de Brito et al., 2012]

Example

/* If an auction "Art" is finished, its winner ("Winner") plays a role "Role", if it doesn’t adopted it yet */ *auctionStatus(closed)[source(Art)] count-as play(Winner,Role,hsh_group)[source(hsh_group)] in currentWinner(Winner)[source(Art)] & not(Winner==no_winner) & auction_role(Art,Role). /* The occurrence of the event "prepareSite" means the achievement of organisational goal "site_prepared" */ + prepareSite[agent_name(Ag),artifact_name(housegui)] count-as goalState(bhsch,site_prepared,Ag,Ag,satisfied)[source(bhsch)].

MAOP 30 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Organisation’s dynamics (triggered by Agents, Environment)

Organisation life-cycle Entrance/Exit of an agent Creation/Deletion of an Organisation entity Change of Organisation specification Structural Organisation life-cycle Creation/Deletion of a group Adoption/Release of a role Functional Organisation life-cycle Creation/End of a schema Commitment/Release of a mission Change of a global goal state Normative Organisation life-cycle Activation/De-activation of obligation Fulfilment/Violation/Sanction

MAOP 31 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Outcomes of A & E & O Integration

Normative deliberative agents

possibility to define mechanisms for agents to evolve within an

• rganisation/several organisations

possibility to define proper mechanisms for deliberating on the internalisation/adoption/violation of norms

Reorganisation, adaptation of the organisation

possibility to define proper mechanisms for diagnosing/evaluating/refining/defining organisations

“Deliberative” Organisations

possibility to define dedicated organisational strategies for the regulation/adaptation of the organisation behaviour (organisational agents)

“Embodied” Organisation / Organisation Aware Environment

possibility to connect organisation to environment

MAOP 32 / 74

Introduction MAOP JaCaMo Experiences Conclusion MAOP Meta-Model A E O Synthesis

Synthesis: MAOP meta-model

Artifact Operation Agent Workspace Environment Manual has use generate update create dispose link, unlink consult create join quit Belief Goal Plan External Action Internal Action create delete adopt leave create delete commit leave focus, unfocus primitive operations composition association dependency concept mapping Trigger event Observable Property dimension border Action Observable Event achieve Environment Dimension Agent Dimension Organisation Dimension

Cardinalities are not represented

Content Message SpeechAct Interaction Dimension send receive focus, unfocus Mission Role Group Social Scheme Norm Goal Link Organisation

JaCaMo Meta-model [Boissier et al., 2011], based on Cartago [Ricci et al., 2009b], Jason [Bordini et al., 2007], M OISE [Hübner et al., 2009a] meta-models

MAOP 33 / 74

1

Introduction

2

Multi-Agent Oriented Programming (MAOP)

3

MAOP Perspective: the JaCaMo Platform Overview Project definition Development Tools Technologies

4

MAOP Experiences

5

Conclusions and Perspectives

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

JaCaMo Platform http://jacamo.sourceforge.net

Java Platform CArtAgO, Jason, NOPL engine Operating System

artifact(SB,SchemeBoard,ID1) artifact(CONS,Console,ID2) ... WorkspaceArtifact linkArtifacts lookupArtifact (make/dispose)Artifact quitWorkspace workspace(WspName,ID) ... NodeArtifact createWorkspace joinWorkspace joinRemoteWorkspace shutdownNode Specification Groups Players Goals Obbligations SchemeBoard commintMission leaveMission setGoalAchieved Console print println Specification Schemes Goals GroupBoard leaveRole addScheme removeScheme adoptRole Agent Plan

... ... Agent dimension Artifact Operations ... ... Environment dimension Organisation dimension Mission Goal ... ... JaCaMo workspace Platform level Execution level

Conceptual level

MAOP 35 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Execution Platform

Agent execution and communication management infrastructures can be: Centralised: all agents in the same machine,

• ne thread by agent, very fast

Centralised (pool): all agents in the same machine, fixed number of thread, allows thousands of agents Distributed (jade): distributed agents, use of FIPA-ACL using the Jade agent execution and communication platform .... others defined by the user (e.g. AgentScape) Environment execution can be: Centralised: one centralised environment shared by the agents, is automatically included in case of no other specification Distributed: multiple environments shared by the agents – specified by cartago("infrastructure")

MAOP 36 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

MAS Configuration & Deployment Language

Simple way of defining a multi-agent system within the JaCaMo Platform Example (Building House Definition)

mas house_building { agent giacomo // the agent that wants to build a house agent companyA // builder agents (see their code for details) agent companyB agent companyC { instances: 5 } agent companyD { instances: 13 } agent companyE asl-path: src/agt, src/agt/inc }

MAOP 37 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Eclipse JaCaMo plugin

MAOP 38 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Agent’s Mind inspector

MAOP 39 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Organization Structure inspector

MAOP 40 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Organization Structure inspector

MAOP 41 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Organization Functioning inspector

MAOP 42 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Organization Functioning inspector

MAOP 43 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Integration of Multi-Agent technologies

Agent: Jason agents [Bordini et al., 2007] Environment: CArtAgO platform [Ricci et al., 2009b] Organisation: M OISE framework with the extended/refactored version of the M OISE OMI: ORA4MAS [Hübner et al., 2009a] Interaction: based on tight integration between Jason and KQML

• r ACL/FIPA

Dimensions are integrated with dedicated bridges: A–E (c4Jason, c4Jadex [Ricci et al., 2009b]) E–O (count-as/enact rules [Piunti et al., 2009]) A–O is for free (thanks to ORA4MAS). Strategies and reasoning capabilities from J -M OISE+ [Hübner et al., 2007] can be reused. Open to integrate other Multi-Agent Technologies

MAOP 44 / 74

Introduction MAOP JaCaMo Experiences Conclusion Overview Project definition Development Tools Technologies

Integration with other technologies

Web 2.0

implementing Web 2.0 applications http://jaca-web.sourceforge.net

Android Platforms

implementing mobile computing applications on top of the Android platform http://jaca-android.sourceforge.net

Web Services

building SOA/Web Services applications http://cartagows.sourceforge.net

Arduino Platforms

building “Web of Things” Applications http://jacamo.sourceforge.net

Semantic Technologies

JaSA: Semantically Aware Agents http://cartago.sourceforge.net

MAOP 45 / 74

Outline

1

Introduction

2

Multi-Agent Oriented Programming (MAOP)

3

MAOP Perspective: the JaCaMo Platform

4

MAOP Experiences MAOP Case: Agile Governance of M2M Infrastructure Sharing data, Knowledge Privacy & Trust

5

Conclusions and Perspectives

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Infrastructure for Smart Cities (ETSI view)

European Telecommunications Standards Institute (ETSI) view on M2M infrastructure

Device Domain: smart devices (sensors and actuators) for collecting data and controling the environment Network Domain: shared communication infrastructure (platforms and gateways) to connect applications to devices Application Domain: applications providing ubiquitous & added value services to citizens

MAOP 47 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

SensCity: Urban M2M Infrastructure

http://www.senscity-grenoble.com

In the context of this industrial project, our objective is to define an agile governance of the Urban M2M Infrastructure This is an ongoing research project in collaboration with OrangeLabs, France

MAOP 48 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Agile Governance Requirements

To get a urban M2M infrastructure for smart city: where costs and resources can be shared between several applications (e.g. Parking Management, Garbage Collection, Smart Metering, etc)

❀ Shifting from “vertical” to “horizontal” M2M infrastructures

where new Stakeholders (i.e. application/sensors/actuators) can be added/suppressed during the lifetime of the system

❀ Openness

and reacting to the changes of environmental conditions (e.g. increase in the number of collected data, number of messages)

❀ Adaptation

❀ Definition of an agile and decentralized governance layer on top of the M2M Infrastructure [Persson et al., 2012]

MAOP 49 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Legacy System

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

legend

SensCity platform composed of 47 types of components supporting access to physical devices and shared by several heterogenous Applications

MAOP 50 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

MA Governance Layer: Governance Artifacts

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1

legend

Monitoring and controling tools that Compute direct / interpreted / aggregated status of the SensCity Platform’s components. Provide a uniform access of this status to the agents by

• bservable properties or signals

Offer the agents the possibility to act on the functioning of the M2M infrastructure by a repertoire of

• perations (Threshold definition,

LoadBalancing, (De)activate, ...) Structured according to the ETSI domains

MAOP 51 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

MA Governance Layer: Governance Agents

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1

legend

Take local autonomous decisions given the prescriptions of the

• rganisation and their own local

strategies Monitor the M2M infrastructure by focusing on artifacts (e.g. Failures, Overloads) updating their beliefs, goals Apply their governance policies and local strategies (goals, beliefs, plans) to control M2M infrastructure by using their actions (❀ artifacts operations) Interact with the other agents Adapt the global governance strategy (❀ may modify the

• rganisation)

MAOP 52 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

MA Governance Layer: Governance Organisations

Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Expressed in terms of structure (groups, roles), functionning (missions, goals, plans) and norms, and reasoned on by the agents and monitored by the

• rganisation management

infrastructure Horizontal Organisation: defines the nominal global functioning based on ETSI standards (Domains, Service Capabilities, Capability functionalities, ...)

MAOP 53 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

MA Governance Layer: Governance Organisations

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Expressed in terms of structure (groups, roles), functionning (missions, goals, plans) and norms, and reasoned on by the agents and monitored by the

• rganisation management

infrastructure Horizontal Organisation: defines the nominal global functioning based on ETSI standards (Domains, Service Capabilities, Capability functionalities, ...) Vertical Organisations: based on each application SLA deployed

• n the Urban M2M Infrastructure

❀ agents participate to multiple

• rganisations

MAOP 53 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Agile Governance Example

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

SLA Definition Service Level Agreement: Translation of Application subscription to Devices in terms of Group, Roles, Missions, Norms Validation: If judged feasible, role adopted Else Rejected or New proposal

MAOP 54 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Agile Governance Example

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Contract Execution Social Scheme activation: when request is received, new scheme instance started Execution Monitoring: validation of application requests, monitoring of devices’ activity

MAOP 55 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Agile Governance Example

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Problem Detection Detection of possible norm violation, i.e. failure to comply with the SLA Platform Monitoring: find the source of the problem with the help of the artifacts

MAOP 56 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Agile Governance Example

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Infrastructure Adaptation Fix the problem by acting on the platform via the artifacts under their responsibility and their governance policies Coordinate with each other

MAOP 57 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

M2M Agile Governance Example

SLA Normative Functional

Structural translated into Normative Functional Structural M2M System Application Network Devices Application Application Enabler App Security Mngr History Mngr Compensation Broker Transaction Mngr Net Security Mngr Remote Entity Mngr Interworking Proxy Communication Enabler Gateway Proxy Gateway M2M Area Device Sensor Actuator plugged-in Application-specific organization Agile gouvernance organization platform agents device agents network agents Application Workspace

• p2
• p1
• p2
• p1

AppCNX AppConf Network Workspace

• p2
• p1

NetworkInventory Devices WorkSpace

• p2
• p1
• p2
• p1

DeviceCNX Store

• p2
• p1

Forward Organization Workspace

• p2
• p1
• p2
• p1

OrgBoard SchemeBoard

• p2
• p1

GroupBoard SLA Application SLA

Organization Agents Environment SensCity Real World

• p2
• p1
• p2
• p1
• p2
• p1

• p2
• p1

legend

Governance Strategy Adaptation Problem with the SLA: SLA might be too greedy, infrastructure adaptation not sufficient ❀ SLA redefinition (eg. decrease message frequency, device subscription redefined)

MAOP 58 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Synthesis

Monitoring and governance of the M2M infrastructure take place at different levels embracing an increasing broader view: Artifacts < Agents & Interactions < Organisations ❀ Modularity / Lisibility of the Governance Layer Coordination mechanisms installing Top-Down - Bottom-up loops (Synergie between Macro/Micro levels) Agents are in charge of the governance but also of the reorganisation process Current experiments:

Installing complex governance processes Refactoring the Agents layer by making explicit dedicated coordination strategies expressed into coordination artifacts Distributing and better managing the deployement

MAOP 59 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Sharing Data and Knowledge

Smart Places

Smart places where nomadic users participate to adhoc virtual communities (in collaboration with LaHC/UJM, LT2C/UJM-TSE))

MAOP 60 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Privacias [Ciortea et al., 2012]

Privacy preservation in open and decentralized communities by the definition of Privacy Enforcing Agent:

Privacy Enforcement Norms checked by the agent Privacy Enforcement Layer Appropriateness laws (A-Laws) used by the agent Privacy violation detection layer

MAOP 61 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Decentralized Trust Management

f A D C G E B F H Frank George Elise Carl Alice Dave Bob Helen

Open Innovation Communities where groups of individuals share common interests or objectives interact and share resources (documents, ideas, etc) Management of Individual and Collective Trust Policies on behalf of the users [Yaich et al., 2012]

MAOP 62 / 74

Introduction MAOP JaCaMo Experiences Conclusion Case K-Sharing Trust & Privacy

Decentralized Trust Management

I F G B C A Adhesion Association

Interactions

Community Role Collective Policies A Assistant Agent Individual Policies ASC-TMA Private Resource Public Resource T T T T T T T

Environment Agents Organisation

Interaction Control Operation Negotiation

Multi-Agent Architecture

MAOP 63 / 74

Outline

1

Introduction

2

Multi-Agent Oriented Programming (MAOP)

3

MAOP Perspective: the JaCaMo Platform

4

MAOP Experiences

5

Conclusions and Perspectives

Introduction MAOP JaCaMo Experiences Conclusion

Conclusions

MAOP proposes a seamless integration of different abstractions that brings interesting features to Intelligent Environments: ❀ separation of concerns

using the best abstraction level and tools to tackle the specific dimensions, avoiding design pitfalls, such as using agents to implement either non-autonomous entities (e.g., a blackboard agent) or a collection of autonomous entities (group agent)

❀ openness and heterogeneity

E.g., heterogeneous agents working in the same organisation, heterogeneous agents working in the same environment, the same agent working in different and heterogeneous organisations, the same agent working in different heterogeneous environments

❀ programming features:

Each of the dimension can be addressed explicitly Modularity, extensibility, reusability is possible Extensible set of actions and tools provided to Agents (Reorganization Artifact, Organization Management Artifacts, ...) ... code is cleaner and more understandable ...

MAOP 65 / 74

Introduction MAOP JaCaMo Experiences Conclusion

MAOP Open Issues & Perspectives

❀ Coordination

Integration of Bottom-up AND Top-Down functioning within MAS ❀ integration of emergence AND Normative dynamics Management of Open Organisations, Multiple Organisations, Organisation of Organisations Management of Situated Organisations (Interactions between E and O dimensions) ❀ Shift from MAS to MAOS (Multi-AgentOrganization Systems)

❀ Engineering

Debugging, Performance, ... Life cycle of MAS (from requirement to maintenance) ❀ software engineering tools and methods Shift from Agent-Oriented Sofware Engineering to Multi-Agent Oriented Software Engineering where all the dimensions A, E, I, O may guide each step of the process Evaluation & Verification of MAO programmed applications, Integrating with other technologies Handle Scalability, Robustness

MAOP 66 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Multi-Agent Oriented Programming

– Introduction –

The JaCaMo Platform

• O. Boissier1

R.H. Bordini2 J.F. Hübner3

• A. Ricci4
• 1. Ecole Nationale Supérieure des Mines (ENSMSE), Saint Etienne, France

2 Pontificia Universidade Catolica do Rio Grande do Sul (PUCRS), Porto Alegre, Brazil

• 3. Federal University of Santa Catarina (UFSC), Florianópolis, Brazil
• 4. University of Bologna (UNIBO), Bologna, Italy

September 2015

MAOP 67 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography I

Boissier, O. (2003). Contrôle et coordination orientés multi-agents. Habilitation à diriger des recherches, ENS Mines Saint-Etienne et Université Jean Monnet. Boissier, O., Bordini, R. H., Hübner, J. F., Ricci, A., and Santi, A. (2011). Multi-agent oriented programming with jacamo. Science of Computer Programming, pages –. Bordini, R. H., Hübner, J. F., and Wooldrige, M. (2007). Programming Multi-Agent Systems in AgentSpeak using Jason. Wiley Series in Agent Technology. John Wiley & Sons. Campos, J., López-Sánchez, M., Rodriguez-Aguilar, J. A., and Esteva, M. (2009). Formalising situatedness and adaptation in electronic institutions. In Coordination, Organizations, Institutions and Norms in Agent Systems IV, volume 5428/2009 of LNCS. Springer Berlin / Heidelberg. Ciortea, A. (2011). Modeling relationships for privacy preservation in virtual communities. Master’s thesis, University Politehnica of Bucharest.

MAOP 68 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography II

Ciortea, A., Krupa, Y., and Vercouter, L. (2012). Designing privacy-aware social networks: a multi-agent approach. In Burdescu, D. D., Akerkar, R., and Badica, C., editors, WIMS, page 8. ACM. de Brito, M., Hübner, J. F., and Bordini, R. H. (2012). Programming institutional facts in multi-agent systems. In COIN-12, Proceedings. Demazeau, Y. (1995). From interactions to collective behaviour in agent-based systems. In Proc. of the 1st European Conf. on Cognitive Science. Saint-Malo, pages 117–132. Demazeau, Y. (1997). Steps towards multi-agent oriented programming. (slides Workshop) 1st International Workshop on Multi-Agent Systems, IWMAS’97, Boston.

MAOP 69 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography III

Hübner, J. F ., Boissier, O., Kitio, R., and Ricci, A. (2009a). Instrumenting Multi-Agent Organisations with Organisational Artifacts and Agents. Journal of Autonomous Agents and Multi-Agent Systems. Hübner, J. F ., Sichman, J. S., and Boissier, O. (2007). Developing Organised Multi-Agent Systems Using the MOISE+ Model: Programming Issues at the System and Agent Levels. Agent-Oriented Software Engineering, 1(3/4):370–395. Hübner, J. F ., Vercouter, L., and Boissier, O. (2009b). Instrumenting Multi-Agent Organisations with reputation artifacts. In Hubner, J. F ., Matson, E., Boissier, O., and Dignum, V., editors, Coordination, Organizations, Institutions, and Norms in Agent Systems IV, volume 5428 of LNAI, pages 96–110. Springer. Huhns, M. N. (2001). Interaction-oriented programming. In First international workshop, AOSE 2000 on Agent-oriented software engineering, pages 29–44, Secaucus, NJ, USA. Springer-Verlag New York, Inc.

MAOP 70 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography IV

Kitio, R. (2011). Gestion de l’ouverture au sein d’organisations multi-agents. Une approche basée sur des artefacts organisationnels. PhD thesis, ENS Mines Saint-Etienne. Occello, M., Baeijs, C., Demazeau, Y., and Koning, J.-L. (2004). MASK: An AEIO toolbox to design and build multi-agent systems. In et al., C., editor, Knowledge Engineering and Agent Technology, IOS Series on Frontiers in AI and Applications. IOS press, Amsterdam. Omicini, A., Ricci, A., and Viroli, M. (2008). Artifacts in the A&A meta-model for multi-agent systems. Autonomous Agents and Multi-Agent Systems, 17(3):432–456. Persson, C., Picard, G., Ramparany, F., and Boissier, O. (2012). A jacamo-based governance of machine-to-machine systems. In Demazeau, Y., Müller, J. P ., Rodríguez, J. M. C., and Pérez, J. B., editors, Advances on Practical Applications of Agents and Multiagent Systems, Proc. of the 10th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 12), volume 155 of Advances in Soft Computing Series, pages 161–168. Springer.

MAOP 71 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography V

Piunti, M., Ricci, A., Boissier, O., and Hubner, J. (2009). Embodying organisations in multi-agent work environments. In IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2009), Milan, Italy. Pynadath, D. V., Tambe, M., Chauvat, N., and Cavedon, L. (1999). Toward team-oriented programming. In Jennings, N. R. and Lespérance, Y., editors, ATAL, volume 1757 of LNCS, pages 233–247. Springer. Ricci, A., Piunti, M., and Viroli, M. (2009a). Externalisation and internalization: A new perspective on agent modularisation in multi-agent system programming. In Dastani, M., Fallah-Seghrouchni, A. E., Leite, J., and Torroni, P ., editors, LADS, volume 6039 of Lecture Notes in Computer Science, pages 35–54. Springer. Ricci, A., Piunti, M., and Viroli, M. (2011). Environment programming in multi-agent systems: an artifact-based perspective. Autonomous Agents and Multi-Agent Systems, 23:158–192.

MAOP 72 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography VI

Ricci, A., Piunti, M., Viroli, M., and Omicini, A. (2009b). Environment programming in CArtAgO. In Multi-Agent Programming: Languages,Platforms and Applications,Vol.2. Springer. Ricordel, P . and Demazeau, Y. (2002). VOLCANO: a vowels-oriented multi-agent platform. In Dunin-Keplicz and Nawarecki, editors, Proceedings of the International Conference of Central Eastern Europe on Multi-Agent Systems (CEEMAS’01), volume 2296 of LNAI, pages 252–262. Springer Verlag. Shoham, Y. (1993). Agent-oriented programming.

• Artif. Intell., 60(1):51–92.

Sorici, A. (2011). Agile governance in an ambient intelligence environment. Master’s thesis, University Politehnica of Bucharest.

MAOP 73 / 74

Introduction MAOP JaCaMo Experiences Conclusion

Bibliography VII

Stratulat, T., Ferber, J., and Tranier, J. (2009). MASQ: towards an integral approach to interaction. In AAMAS (2), pages 813–820. Yaich, R., Boissier, O., Jaillon, P ., and Picard, G. (2012). An agent based trust management system for multi-agent based virtual communities. In Demazeau, Y., Müller, J. P ., Rodríguez, J. M. C., and Pérez, J. B., editors, Advances on Practical Applications of Agents and Multiagent Systems, Proc. of the 10th International Conference on Practical Applications of Agents and Multi-Agent Systems (PAAMS 12), volume 155 of Advances in Soft Computing Series, pages 217–223. Springer.

MAOP 74 / 74