Multi-Agent Systems - Architecture Craig Thompson Object Services - - PowerPoint PPT Presentation

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Multi-Agent Systems - Architecture

Craig Thompson Object Services and Consulting, Inc. (OBJS)

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OUTLINE

• Vision
• Agent Reference Architecture
• Agent Services
• Applications
• Contributions & Directions

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I see a tank! Need fuel!

• bservations &

recommendations

• rders &

subscriptions Any threats?

VISION – EVERYTHING IS ALIVE

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AGENT REFERENCE ARCHITECTURE

What is a Reference Architecture

– a meta-architectural blueprint for a family of concrete architectures that may appear in implemented systems, providing architectural views, a collection of the component parts

• f the architecture, how they can fit together, and any constraints on how they fit.

– a litmus test for a good reference architecture is that it covers actual systems and provides a way to reason about missing pieces, sub-architectures that make sense, interdependencies of parts, and how the architecture relates to other nearby architectures.

What should an Agent Reference Architecture do?

– help people understand the scope and value-added of agent systems so they can realize their potential more quickly (agents for the masses) – explain

• how agent architectures solve application domain problems
• how agent systems complement OMA, HLA, Web, DBMS
• how to insure systemic properties of agent systems – scalability, survivability, …

– identify

• principle components of agent systems, their interfaces and their interactions
• missing components
• what parts of the architecture already exist in COTS and GOTS, what parts are already prototyped,

and what parts are still needed.

• candidate standards and a roadmap for adoption
• research issues (e.g., agent control, agent interoperability)

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OBJS Adaptive Adaptive

to uncertainty and change

Agents are goal directed and act on their

• wn performing

tasks on your behalf Agents coordinate and negotiate to achieve common goals Agents move to where they are needed Autonomous Autonomous

proactive

Mobile Mobile Interoperate Interoperate Agents interoperate with humans, other, legacy systems, and information sources Agents dynamically adapt to and learn about their environment Cooperative Cooperative

self-organizing delegation social personality social personality

Characteristics of Agents

Intelligent Agents Information Agents

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What are people saying about agents?

• software that acts on a human’s behalf to provide some service or function in an

intelligent manner

• modular software that exhibits some of these properties: autonomy, mobility,

intelligence

• bjects with an attitude -- component software constructed according to certain

principles and/or mechanisms, e.g., objects that use an ACL to communicate, objects that make use of a planner, …

• networked society where every software artifact, information source, and device is

connected and running in parallel. Connect the $40B worth of DoD equipment that currently only interoperates with one or two other components, permitting better knowledge sharing. A process improvement in factory 1 is broadcast immediately to factories 2 .. N

• intelligent automation-- application connectivity where networks of agents self-organize

at run-time. Reduce the 60% of time in command and control systems spent manipulating stovepipes; incrementally replace stovepipes.

• humans and agents connect to the agent grid anytime from anywhere and get the

information and capability they need. Enable teams led by humans and staffed by agents.

• agent-enable object and web applications to reconfigure as new data and function is

added to the system. Add capability modularly. Stable, scaleable, evolvable, reliable, secure, survivable, ...

• Scale to millions of agents so agents are pervasive and information and

computation is not restricted to machine or organization boundaries.

• Survivable so if one agent goes down, another takes its place;

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• speech acts, conversations/dialogs
• ontologies
• KBMS
• distributed AI
• architecture description languages
• patterns and protocols
• OO middleware service architectures (OMA/ORB)
• web architectures
• workflow
• dynamic DBMS
• simulation
• network management, QoS
• planning & case-based reasoning
• learning
• game theory
• economic markets
• ...

* = Architecture WG in Pittsburg

Relevant Theories View

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Object  Component  Agent  ?

• state
• behavior
• encapsulation
• inheritance
• reflection
• packaging
• serialization
• repository
• TBD

deconstructionist view: agents augment objects with additional capabilities

• agent comm. language
• process inside
• mobility
• goals, planning, rules
• autonomous
• ontologies
• collaborative/teams

What is an Agent?

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FIPA Abstract Architecture

• Agent Abstract Architecture  goal is interoperability

– Agent API via Agent Communication Language (ACL)

• addressing
• publish & subscribe
• content language semantics

– Agent Services

• Encoding/Parsing Service – how messages are encoded
• Message Transport Service – how messages are sent, guarantees, survivability
• Directory Service – register agent description, discover agents
• Borrows from other areas

– User Interface(s) – optional – GUI, natural language, … – Security services – Directory services – Distributed communications – asynchronous, intermittent – Platform & comm. – host abstract machine, environment

• Candidates not yet in current abstract architecture

– Agent lifecycle – Mobility – Domains – Conversational policies – Ontologies – representation of state

Foundation for Intelligent Physical Agents -- http://www.fipa.org/specs/fipa00001

components & interfaces

Interfaces insulate components. We should be able to add or change a component.

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agent properties & kinds

• communication

capability

• computation capability
• by role in system
• information agent
• data sources
• interface agent
• NL
• fisheye view
• task agent
• web agent
• middleware agent
• mobile agent, itinerary
• social, personality,

motivation, forgetting

• intelligent agent

distribution messaging svcs* agent life cycle* - start, stop, checkpoint, name service** event monitoring leasing, compensation catalog services*, registry/repository* register*,

• ffer/accept/decline

publish*, subscribe* trading*, matchmaking, advertising*, negotiating*, brokering*, yellow pages* security** authenticate* encrypt access control lists* firewall* CIA model agent suspects transactions persistence* query, profile (of metadata)* data fusion replication* groups multicast (scarce) resource mgmt*, allocate*, deallocate*, monitor*, local, global optimization, load balancing*, negotiation for resources* scheduling time, geo-location rules, constraints planning* property list versioning, config

(aka Functional/Compositional View)

speech acts*: ACL* - KQML, FIPA ACL, OAA ICL planning*

• reactive*
• goal interactions*
• discrete vs continuous*
• constraints
• iterative, revision
• workflow

systemic grid features common services AGENT SYSTEM

• single vs. multi-agent

ensembles

• # of agents*
• teams, peers,

contracting,

• org. responsibility
• roles, capabilities,
• mutual beliefs
• hierarchy*
• conversational

policies* scalability* policy*, management

• resource dial

survivability evolvability reliable* licensing & cost QoS*

• accuracy
• priorities

GRID time-constrained* control*, coordination*, multi-agent synchronization

• cooperation, competition

adaptation, evolution* via market model, ... federates infrastructure primitives

• reflection
• serialization
• threads
• interceptors
• proxies
• filters
• multicast
• wrappers
• legacy sys
• data sources

ONTOLOGY**

• ontolingua, OKBC
• metadata representations
• interests, locations,

availability, capability, price/cost

• XML and web object models

I*3 BADD AICE IA EDCS Quorum OMG JTF Jini ALP, HLA, IA Architecture Principle: separation of concerns deconstructionist view - what can you take away and still have an agent system secure*, trust societies

• closed vs. open,

communities of interest learning

• by example
• ...

mobility** heterogeneous*

• computing environ.
• agent systems
• ACLs
• content languages
• ontologies
• policies
• services
• open world

assumption autonomous decentralized* * = Architecture WG in Pittsburg * = Control WG in Pittsburg * = Interoperability WG in Pittsburg red = Sun Jini green = other DARPA programs content languages

• KIF, FOL, IDL,

RDF missing

• views
• MOP

More common services instrumenting, logging caching queuing routing, rerouting pedigree, drill down translation* ... DDB

Agent Ontology View

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AGENT SERVICES

Piggyback agent service on standard widely deployed infrastructure for pervasive agent deployment … agents for the masses.

• WebTrader – Use search engines as yellow pages to locate agent services.

Anyone on the Web can advertise a resource (e.g., agent, service, data source) that anyone else can discover.

• MBNLI – Use web pages to store semantic grammars. Humans can query agents

across the web using constrained natural language.

• eGents – Use email as agent transport supporting disconnected operations.

Anyone with email can create an agent service that anyone else can use.

• MsgLog – Provide several message transports and select among them using policy.

Messaging is survivable (robust, secure, scalable).

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Problem Impact Approach

• If grid applications are to be assembled when needed,

the parts must be found somewhere and probably not all will come from the local environment.

• How can we find building block resources (e.g.,

agents, services, channels, components, data sources) when we need them?

• Today, traders (matchmakers) are used for this

purpose but these traders generally know only about closed worlds of resources of limited types (e.g., IDL).

• Anyone on the Web can advertise a resource

(e.g., agent, service, data source) that anyone else can discover.

• Advertised resources can be located at runtime to

dynamically extend the knowledge and/or capabilities of the client, as well as enable intelligent on-the-fly assembly and reconfiguration

• f distributed systems.
• WebTrader is a matchmaking service that locates

XML-based advertisements for resources embedded in web pages indexed by industrial-strength search engines.

• WebTrader supports type-specific matcher algorithms,

trader federation, and can access multiple search engines.

WebTrader: Scalable Agent Discovery

Open Agent Architecture (SRI) WebTrader Agent Ariadne (ISI)

Agent World Web World

Search Engine

page

AD

page

AD

page page

AD

page

AD

page

AD

page page

AD

page

AD

page page

AD GeoCoder White Pages

Services / Datasources

1 2 3 5 6 7

Agent Grid

4

WebTrader was used in the NEO TIE to locate evacuees and to find a geocoder.

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Web Search Engine(s) Web Trader Engine Matching Query (Client Advertisement)

Indexed by Locates and returns candidate pages Trading advertisements may be distributed across some part of the Web 4 9 7 3 10 12 8 6 5

WebTrader

11 14 13 WebTrader matches and returns candidate advertisements

Web Page Trader Advertisement

2 1

Response

WebTrader Architecture

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WebTrader Query Tool

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Problem Impact Approach

• Dynamic military situations will require people to task

and query agents using complex commands.

• Unconstrained natural language is still not tractable in

many situations.

• Humans can task and query agents using

complex but understandable commands in constrained natural language.

• This technology can mix pervasively into all

applications, both on the desktop and the Web.

• Thesis: Natural language-enhanced user-to-agent

communication will simplify basic human-agent interactions while making it possible for humans to formulate complex agent requests.

• Approach: Agents communicate with people and
• ther agents using restricted languages for stating

complex queries and commands

• How: MBNLI extends agents with natural language

middleware wrappers, dynamically loads grammars, and uses menu-based natural language to query and task agents. Works over the web with many users, can auto-generate NLI interfaces to DBMS, works with speech, and is on the CoABS grid.

MBNLI: Menu-based Natural Language I/F

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MBNLI Example

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eGents: Agents communicating via Email

• Thesis: Integration of agent technology with pervasive

Web-ORB-Email backplanes is a route to making agent technology open, pervasive and robust.

• eGents are agents which communicate over email.

eGents leverages pervasive, robust email infrastructure, inherits support for disconnected operations, message queuing, mobile users, firewalls, filtering, logging, and

• security. eGents use FIPA or KQML Agent

Communication Language (ACL) encoded in XML - no ACL parser needed. Status: Prototype, gridified via proxy and as comm. layer, on wireless Palm. NEO, MIATA, CoAX, JBI TIEs. Spec submitted to FIPA.

Problem Impact Approach

• Dynamic military situations are often disconnected

and asynchronous. Need a scalable way to deliver agent messages to 1000’s of (wireless) platforms.

• Agent systems are often closed and require a lot of

specialized agent technology. Email is a common denominator in coalition situations.

• Anyone with email can create an agent service

that anyone else can use. New eGent apps can be downloaded to the field as situations change.

• Imagine eGents attached to sensors, actuators,

people, equipment, and locations as pervasive

• bservers & actors

In these eGents applications, each evacuees/troops/animals have a Personal Status Monitor, which measures location, vital signs, etc. The PSM contains an eGent which intermittently communicates to subscribing entities using email protocols. Liaison Command Post Family Member Medevac Evacuees/ Troops/ Wildlife/ Etc. eGents Inside

Theme: Everything is alive

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eGents Example

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eGents Architecture

eGents interoperating with each other and with an eGent-grid proxy

Machine 1 installed on soldier, evacuee, vehicle, weapon

PSM server eGent eGents platform**

• ther

eGents

Machine 2 perhaps installed at command post

eGent grid agent proxy

• ther

eGents

Machine 3 perhaps installed at medevac unit

PSM client eGent eGents platform

• ther

eGents Grid PSM client grid agent Email Server

All eGents can share one Email server or they can each have their own

• r anything in between

* Java-based ** KVM-based - runs on Palm

uses J2ME CLDC 1.0 FCS (KVM), that is, Java for devices runs on a "wireless" palm over the CDPD digital cellular network

Might be on machine 2 or anywhere on LAN

• r on grid-connected LAN

eGents platform*

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MsgLog: Agent Messaging Service

Policy Mgmt Compression Encryption Recovery / timeout / Retry Adaptive Messaging

Local Messaging Other Messaging sockets, JMS, …

Agent Mail servers (store & forward)

Periodic Connection Agent (Palm) Firewalled Agent

Info servers (situation updates/ Logs)

Overwhelmed Agent (only get latest update - not intermediate)

Mask Traffic Patterns

RMI Messaging White Noise Email Messaging NNTP Messaging

Adaptive & Survivable

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The Basic Idea

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APPLICATIONS

• DARPA CoABS Coalition Agent Experiment
• DARPA CoABS-AFRL Joint Battlespace Infosphere
• AFRL Small Unit Operations Communicator

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Coalition Agent Experiment (CoAX)

Are the Safari Park elephants in danger?

• eGents monitor and transmit positions
• f the two elephant herds
• menu-based natural language queries

determine the elephants are migrating

• ut of the firestorm area

Elephant herd migrations

• ver the last 40 months

Current position of herd 17.0N/ 34.4E - 2012/09/01 14:20

Theme: Everythin g is alive

OBJS role in CoAX TIE

Safari Park

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Safari Park Vignette

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OBJS So elephants were here at beginning

• f the month.

Where are they now?

MBNLI

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subscribe inform

eGents

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Agent-based SUO* Communicator

HQ Platoon-01-Leader Squad-03-Leader Ranger-14 Unknown World Sensor-03 Sensor-05 Vehicle-02

Develop a reconfigurable handheld computer capability, tailorable to the user role and mission for mission planning and execution, and extensible to new small unit applications.

Complement Radio

– Many people can “speak” at once – Auto-create and handle messages – Memory & Listening Aid - Store information

• ver time

– Accuracy of Geo-location references – Support for disconnected opertions – Assured delivery – Stealth – After action analysis * Small Unit Operations (SUO)

• military, police, NGOs, …,
• leaders, soldiers, medics, …,
• robots, vehicles, weapons, sensors, …

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Scenario – Terrorists at the Airport

Soldier Tasks

Squad 1 – Monitor activity at terminals 1, 2, and 4 – Secure parked aircraft – Receive information on vehicles or people approaching terminals – Receive information from deployed sensors in AOI Squad 3 – Secure area around POLs – Receive information on buildings in area of POLs – Receive information on vehicles or people approaching area – Receive information from deployed sensors in AOI Squads 2 and 4 – Secure perimeter of terminal 3 – Report any observations of terrorist behavior – Receive information on vehicles or people approaching area – Receive information from deployed sensors in AOI

Command Center (Airport Fire & Rescue Station) Squads 2 & 4 Terminal 3 Squad3 POLs Squad 1 Terminals 1, 2, 4

1. Agents configured to role 2. HQ sends maps / grid setup 3. Filters distributed to agents 4. HQ receives USMTF weather 5. Squad 3 moves from CP to AOI 6. Sensors placed 7. Sensor trips & alerts subscribers 8. Ranger resets sensor 9. Sensor trips again

• 10. Activity near airport entrance
• 11. Activity near POL sensors
• 12. Ranger ordered to investigate
• 13. Ranger sends report

Scenario Actions

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The U.S. Army is on a routine peace keeping mission in Sol del Naro, a small country considered friendly to U.S. interests. One challenge to the peace-keeping forces is the frequent harassment by the anti-U.S. forces in neighboring Sumania. On September 26, 2005, at 10:00 a.m. the Food Distribution and Medical Care Center located in MOUT City is attacked, probably sponsored by Sumanian patriots. The attack has pinned civilians, medical personnel and soldiers in the building, and attempted to damage a support helicopter. The number of killed or wounded is not known.

Scenario – Hostage Rescue at the MOUT

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SUO eGents and Ontology

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Messaging XML DTD

<?xml version='1.0' encoding='UTF-8'?> <!ELEMENT MSG (TIME, FROM, TO, CC?, BCC?, SUBJECT, BODY, ATTACHMENTS?, ACK)> <!ELEMENT TIME (#PCDATA)> <!ELEMENT FROM (#PCDATA)> <!ELEMENT TO (#PCDATA)> <!ELEMENT CC (#PCDATA)> <!ELEMENT BCC (#PCDATA)> <!ELEMENT SUBJECT (#PCDATA)> <!-- for the human, not really used by the system --> <!ELEMENT BODY (TEXTMSG | INFORM | REQUEST | SUBSCRIBE | SUSPEND | RESUME | CANCEL)> <!ELEMENT ATTACHMENTS (#PCDATA)> <!ELEMENT ACK (#PCDATA)> <!ELEMENT TEXTMSG (#PCDATA)> <!-- for the human, others are handled by the RAV02 system --> <!ELEMENT INFORM (CONTENTS)> <!ELEMENT REQUEST (CONTENTS)> <!ELEMENT SUBSCRIBE (SUBSCRIPTIONID, TIMECONSTRAINTS?, DELTA?, CONTENTS)> <!ELEMENT SUSPEND (SUBSCRIPTIONID)> <!ELEMENT RESUME (SUBSCRIPTIONID)> <!ELEMENT CANCEL (SUBSCRIPTIONID)> <!ELEMENT SUBSCRIPTIONID (#PCDATA)> <!ELEMENT TIMECONSTRAINTS (TIMEPERIOD?, REFRESHRATE?)> <!ELEMENT TIMEPERIOD (STARTDTG?, ENDDTG?)> <!ELEMENT STARTDTG (#PCDATA)> <!ELEMENT ENDDTG (#PCDATA)> <!ELEMENT REFRESHRATE (#PCDATA)> <!--in milliseconds -->

Message level Subscriptions ACL level

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Messaging XML DTD (cont)

<!ELEMENT CONTENTS (STATUS | ACTION | ORDER | METHOD1 | METHOD2 | COMMENT)+> <!ELEMENT STATUS (#PCDATA)> <!ELEMENT ACTION (#PCDATA)> <!ELEMENT ORDER (#PCDATA)> <!ELEMENT COMMENT (#PCDATA)> <!ELEMENT METHOD1 (RANGER | UNKNOWN | SENSOR | ADDRBOOK | MAP | CLOCK)> <!ELEMENT RANGER (RANGERGET | RANGERSET)> <!ELEMENT RANGERGET (#PCDATA)> <!-- list containing one or more of LOC PULSE BODYTEMP --> <!ELEMENT RANGERSET (LOC | PULSE | BODYTEMP | AIRTEMP | WINDDIRECTION)*> <!ELEMENT LOC (#PCDATA)> <!ELEMENT PULSE (#PCDATA)> <!ELEMENT BODYTEMP (#PCDATA)> <!ELEMENT AIRTEMP (#PCDATA)> <!ELEMENT WINDDIRECTION (#PCDATA)> <!ELEMENT SENSOR (SENSORGET | SENSORSET)> <!ELEMENT SENSORGET (#PCDATA)> <!-- list containing one or more of LOC SENSORDIRECTION READING --> <!ELEMENT SENSORSET (LOC | DIRECTION | SETTING | READING)*> <!ELEMENT DIRECTION (#PCDATA)> <!ELEMENT SETTING (#PCDATA)> <!-- set | triggered --> <!ELEMENT READING (#PCDATA)> <!ELEMENT ADDRBOOK (ADDRBOOKADD)> <!ELEMENT ADDRBOOKADD (ADDRENTRY+)> <!ELEMENT ADDRENTRY (ADDRALIAS, ADDR+)> <!ELEMENT ADDRALIAS (#PCDATA)> <!ELEMENT ADDR (#PCDATA)> …

Kinds of Messages Specific Message Types

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Message Log

• Can be used to author

scenarios

• Can be used to run

scenarios, providing a common operational picture

• Can be used for after

action reporting and analysis

• Records messages via

Bcc

• View messages an

eGent can send and/or receive

• Select subset of the

log to study subset of the eGents e.g., medical, logistics

aka Scenario Authoring Capability aka Simulation Driver Capability

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Under the Hood of SUO Communicator

Sending Agent Apply Filters Trigger Event Email Server Parse Message Apply Filters Invoke Method

• Resolve Location
• Update GUI
• …

Receiving Agent Construct XML Resolve address Send Message (email) Receive Message (email)

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Message Filter Example

10 20 30 40 50 60 70 80 90 1st Qtr 3rd Qtr East West North

• <FILTER>

<NAME>Near Airport Terminal or Area 7</NAME> <CLASS>LocationFilter</CLASS> <TYPE>USMTF</TYPE>

• <CONDITION>

<FIELD>GM_OperExer</FIELD> <STRING>Quick Recovery</STRING> </CONDITION> <OPERATOR>AND</OPERATOR> <OPERATOR>(</OPERATOR>

• <CONDITION>

<FIELD>GM_Location</FIELD> <LOCATION>AREANM:AREA 7</LOCATION> <RANGE>SEC:000230N0000530W</RANGE> </CONDITION> <OPERATOR>OR</OPERATOR>

• <CONDITION>

<FIELD>GM_Location</FIELD> <LOCATION>SEC:351234N12810W</LOCATION> <RANGE>SEC:001000N0010000W</RANGE> </CONDITION> <OPERATOR>)</OPERATOR>

• </FILTER>

Type / Class identify messages to apply filter to and Java class with filter- specific “evaluate” method. Conditions identify message fields to evaluate, value(s) and range criteria. Operators identify boolean relations between multiple conditions.

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REQUEST INFORM ACK RESUME CANCEL SUSPEND INFORM ACK

Y-JBI sends, eGents receives – eGents sends, Y_JBI receives

SUBSCRIBE

Agent Conversation

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Example

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Example

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OBJS Wired, Secure Wireless, or mixed LAN or WAN

You can run one or several ASIV egents on one or many machines. For standalone demos, we use the Apache James email server running on one of the ASIV

• platforms. But you can use any email server and/or multiple mix-and-match email servers.

ASIV egent email server email server ASIV egent ASIV egent ASIV egent ASIV egent any email client

Machine boundaries process boundaries LAN or WAN

Scalable Architecture

Distributed Wireless ASIV eGents

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Hand Held Trade Study

Xybernaut Tallacomm Fujitsu Panasonic # Requirement / Goal Weight MA-V S Tacter31 S LifeBook P1000 S Toughbook 07 S 1 Runs ASIV Applications: Full Java VM PC Arch w/ 233 MHz min 128 MB RAM min 10

+ +

20

+ +

20

+ +

20

+ +

20 2 Runs & connects to standard COTS database 10

+ +

20

+ +

20

+ +

20

+ +

20 3 Small / Wearable 10

+ +

20

+ +

20

+ +

20

+ +

20 4 Field useable display size - 2" x 3" min 10

+ +

20

+ +

20

+ +

20

+ +

20 5 Wireless Network for battlefield 10

+ +

20

+ +

20

+ +

20

+ +

20 6 Soldier positioning via GPS 10

+ +

20

+ +

20

+ +

20

+ +

20 7 Integral camera 3

• -
• 6
• -
• 6
• -
• 6
• -
• 6

8 Targeting device - use w/GPS 2

• -
• 4

+ +

4

• -
• 4
• -
• 4

Integral / Interface to sensors: 9 Soldier health telemetry 3 10 Weather 1 11 Soldier motion 3 12 Soldier resource telemetry 3 13 Ruggedized 5

+ +

10

+ +

10

• 5

+ +

10 14 Wearable / weight bearing harness 3

+ +

6

+ +

6

+

3

+ +

6 15 Extended operation > 8 hours 3

+

3

+

3

+ +

6 16 Fast initialization (< 5 sec.) 1

• -
• 2
• -
• 2
• -
• 2
• -
• 2

17 Power saving modes 2

+

2

+

2 18 Field-tested - Acceptance 2

+

2

Total Trade Score > 127 137 114 126

Estimated Price: $5832 w/o GPS around $10K $1338 w/o GPS $6146 w/o GPS

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CONCLUSIONS

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Contributions

• Strawman agent reference architecture influenced

– DARPA CoABS Agent Grid – OMG Agent Architecture ** – FIPA Abstract Agent Architecture **

• Agent Grid Services developed for DARPA CoABS Program

– WebTrader * – AgentGram * – eGents agent system – Generic XML2Java mapping *

• FIPA adopted

– Representing agent communication language messages in XML ** – Email message transport **

• SUO artifacts

– SUO Communicator requirements – SUO Ontology – coverage issues – SUO Message XML DTD – Explicit representation for scenarios as collections of messages

• Useful for simulation and after action analysis

– SUO Communicator Prototype

• Cougaar uses our adaptive, survivable message service

* Patent Application ** Standard

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Directions

• Architectural modularity - separating the core system, application, and scenario

– Addin for planning – Addin for MBNLI - Semantic web and web object model

• MBNLI I/F descriptor (e.g., grammar) as wrappers for any entity (agent, web page, info source, internet resource, …)
• MBNLI wrapper composition so you can talk to collections of heterogeneous entities
• Web-enabled MBNLI accessible from any web page – grammars on web pages
• Ontology coverage extensions

– Demo realism - through additional message types, image and video exchange – Ontology editor to define and edit eGents, address books, missions, roles, maps, grids, icons, subscriptions, filters, message types, scenarios (sequences of message instances), data sources, panels and .jars – Mission doctrine coverage – Interoperability with other messaging systems, data sources, C4ISR systems, simulations – Framework for adding new data sources – Interoperability among ASIV Communicators used by different kinds of teams, e.g., rangers and police – Enable end users to extend system by integration of ontology with GUI/eGents

• Semantic extensions

– allowing agents to come and go from scenario – enclaves, mobility – Incomplete info - due to missing or out-of-date messaging due to intermittent connections or being too busy to respond – Aggregate periodic field reports

• Borg Collective

– P2P XML and SQL query and evaluating distributed queries

• Agent Management

– Adaptability – esp. Policy Management Infrastructure for agents – Survivability, security, reliability, scalability, assurance testing – Assuring safety – Basic performance – Garbage collecting servers – Gathering statistics on communications behavior & predicting expected future behavior – Amplify capability of log file to support After Action Review

• Field testing

– Can mission planners use the system to create new scenarios quickly – Port to small footprint platform and field test at MOUT – Can ASIV communicator users use system in field exercises – Scalability - automated deployment to new platforms, download eGent apps to the field as situations change -- currently eGents requires manual installation limiting fast fanout of new eGent applications. - ASIV applet for training

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QUESTIONS

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BACKUP

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Acronyms

• OMG

Object Management Group (Agent SIG)

• FIPA

Foundation for Intelligent Physical Agents

• CoABS

DARPA Control of Agent-based Systems

• CoAX

Coalition Agent Experiment

• JBI

AFRL Joint Battlespace Infosphere

• UltraLog

DARPA UltraLog Program (Survivable Agents for Logistics)

• ALP

DARPA Advanced Logistics Planner

• Cougaar

DARPA Cognitive Agent Architecture

• Msg*Log

OBJS Agent Messaging Service

• MBNLI

Menu-based Natural Language Interface

• ACL

Agent Communication Language

• LAN

Local Area Network

• WAN

Wide Area Network

• RPC

Remote Procedure Call

• Java RMI

Java Remote Method Invocation

• SMTP

Simple Mail Transfer Protocol

• POP3

Post Office Protocol

• NNTP

Network News Transport Protocol

• XML

Extensible Markup Language

• TIE

Technology Integration Experiment

SLIDE 47

Agents - 47

OBJS

Small Unit Operations TIE

• Headquarters in Bosnia gets mole report of enemy shadowing US
• platoons. [1]
• Rome Y-JBI Outlook agent system received email alerts from info sources it is monitoring.
• Commander zooms map to the affected area and subscribes to platoon-

level status reports. [2, 3, 4]

• OBJS eGents representing platoons receive these subscriptions by (wireless) email.
• Feeds from troops are aggregated in platoon level reports which are sent

to subscribers, including the commander. [5]

• Platoon level eGents aggregate troop level reports and begin to send back platoon level

reports to subscribers, including the commander.

• Map changes to show changing platoon locations.
• As the scenario plays, fuselets notice two platoons are under attack, one

via conventional weapons, the other via chemical attack. [6]

• As simulation plays, map changes to show platoons in trouble. This is discovered by Y-JBI

fuselets that look for specific patterns in the communication. In this case, one soldier is killed and another wounded in one platoon and another suffers a chemical attack.

Joint Battlespace Infosphere (JBI)

SLIDE 48

Agents - 48

OBJS

JBI TIE Scenario

1 5 4 6 2 3

SLIDE 49

Agents - 49

OBJS

Simulation Control (World) HQ Platoon Leader Squad Leader Ranger-14 Sensor-5 USMTF proxy MsgLog USMTF Messaging System proxy Other External Data Source

USMTF slash message format

• ther message format

sends ADVANCE CLOCK messages to step thru demo

• or alternatively -

user can use ASIV egent GUI to create a stream of messages Bcc log of messages provides an explicit scenario representation that can be replayed or analyzed for after action reporting

• ASIV eGents use XML message format; eGents proxies handle foreign message formats
• ASIV eGents automatically handle most messages
• aliasing allowed in addresses, e.g., TO: All Platoon Leaders Bcc: MsgLog
• subscriptions are used to auto-send updates periodically
• filters are used to block sending and receiving unwanted messages

Two modes: use GUI point-and-tap to send messages –or– use scenario message log to drive simulation

SUO eGents send messages to each other