Coordination Artifacts in Multi-Agent Systems April 19, 2005 IEEE KIMAS 2005 Sarah Siracuse, John...

Coordination Artifacts in Coordination Artifacts in Multi-Agent SystemsMulti-Agent Systems

April 19, 2005

IEEE KIMAS 2005

Sarah Siracuse, John Zinky, Richard Shapiro

[email protected], [email protected], [email protected]

2

AgendaAgenda

• Motivation for Coordination Artifacts in MAS• Coordination Artifacts: Designs & Benefits• Separation of Function: Coordination logic vs.

Domain logic• Implementation of Coordination Artifacts using

Cougaar• Works well in Tightly-coupled Systems• Performance Analysis: QoS Opportunity• Conclusions

3

Motivation for Coordination ArtifactsMotivation for Coordination Artifactsin MASin MAS

• Coordination observations– MAS application

• Cougaar agent architecture• ~1000+ agents on ~100 hosts

– Many different kinds of implicit coordination in heterogeneous systems

– Coordination implementation• Mixed in with domain logic• Spans lots of places in the code

• Coordination Artifact– Separates coordination

implementation from domain logic

– Distinguishes between various kinds of coordinations

– Has state

Controller

Manager

Peer

Sensor

TranslateCollect

DisseminateSynchronize

AggregateSummarize

Typical Agent Control Society

4

CAs Separate Coordination ActivityCAs Separate Coordination Activityfrom Domain Processingfrom Domain Processing

• Objective Coordination (Outside Agent)– Coordination encapsulated

• Outside domain logic– Environment-based– Mediated communication– e.g. Ant trails

• Subjective Coordination (Inside Agent)– Coordination mixed in with domain logic– Dialog-based– Direct Messaging– e.g. TCP/IP, Instant Messaging,FIPA Agent

Communication Language

Agent

AgentAgent

Agent

Agent

Agent

AgentAgent

Agent

Agent

CAs

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Agent Agent

CAs are First Class EntitiesCAs are First Class Entitiesthat coordinate Interaction between Agentsthat coordinate Interaction between Agents

CoordinationArtifact(CA)

Agent

Defines rolesDefines roles

Agent

• Coordination Artifacts: CAs – Are first-class entities in MAS– Define explicit roles for role-players– Offer shared state between the role-player & the CA– Coordinate behavior among role-players– Have distributed implementation

Role-playersRole-playersShared stateShared state

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ServerCA

ClientCA

SensorCoordination

Inter-AgentCoordination

CAs Unify Agent-to-Agent andCAs Unify Agent-to-Agent andAgent-to-Environment Communication Agent-to-Environment Communication

Agent

PhysicalEnvironment

Non-Agent Systems

OtherAgents

Persisted Storage

7

AgendaAgenda

• Motivation for Coordination Artifacts in MAS• Coordination Artifacts: Designs & Benefits• Separation of Function: Coordination logic vs.

Domain logic

• Implementation of Coordination Artifacts using Cougaar

• Works well in Tightly-coupled Systems• Performance Analysis: QoS Opportunity• Conclusions

8

Agent

Cougaar Components ImplementCougaar Components ImplementAd-hoc CoordinationAd-hoc Coordination

AgentDomainLogic

SensorPlugin

SensorComp

AgentBlackboard

Inter-agentMessaging

Components

Net

ClientLibraries

ServerLibraries

ClientPlugin

ServerPlugin

PhysicalEnvironment

CommPlugin

Non-Agent Systems

RemoteAgents

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Agent BAgent A

Rule Engine

Fact BaseFact

ReceptacleFacet

Black-board

Relay

LogicProvider

MessageTransport

Rule Engine

Fact BaseFact

ReceptacleFacet

Black-board

Relay

LogicProvider

MessageTransportRMI

Host A Host B

Distributed Coordination ArtifactsDistributed Coordination ArtifactsLayered Over Cougaar ComponentsLayered Over Cougaar Components

CA

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Coordination Artifacts work bestCoordination Artifacts work bestin Tightly-Coupled Systemsin Tightly-Coupled Systems

• Tightly coupled (Ideal CA applications):• Long Term Relationships• Group relationships• Push meta-data in

anticipation of need• E.g. Cougaar with

Coordination Artifacts

•Loosely coupled (Bad fit for CAs):•Transient Relationships•Pair relationships•Pull meta-data when needed•E.g. Web-Services

Controller

Manager

Peer

Sensor

TranslateCollect

DisseminateSynchronize

AggregateSummarize

Typical Agent Control Society

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Coordination Performance Depends onCoordination Performance Depends onUnderlying Topology and ResourcesUnderlying Topology and Resources

Coordination Task

Tick SyncCoordination

M

S S S S…

12


Coordination Task


M

S S S S…

Distant master (31 hosts)

Distant slave (31 hosts)

Dual processors [email protected]

Single processor 2.8GHzSingleProcessor

DualProcesor

DualProcessors

M WAN

SWAN

Res

ou

rces

& R

ole

s

13


Coordination Task


M

S S S S…





DualProcesor

DualProcessors

M WAN

SWAN

Res

ou

rces

& R

ole

s

Flat Tree Chain

Topology

MT T

S SS S

M

S S S SS S

STTTTTM

Flat

Tree

Chain

14



S

Coordination TaskM

S S S…





DualProcesor

DualProcessors

M WAN

SWAN

Res

ou

rces

& R

ole

s

27 25 17

35 22 13

6.1 2.5 0.8

0.6 2.5 0.8

Performance(ticks/second)

Flat Tree Chain

Topology

MT T

S SS S

M

S S S SS S

STTTTTM

Flat

Tree

Chain

15


Coordination Task


M

S S S S…





DualProcesor

DualProcessors

M WAN

SWAN

Res

ou

rces

& R

ole

s

27 25 17

35 22 13

6.1 2.5 0.8

0.6 2.5 0.8


Flat Tree Chain

Topology

MT T

S SS S

M

S S S SS S

STTTTTM

Flat

Tree

Chain

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CAs can dynamically change the topology as the network and/or the roles change.

QoS Adaptation via CAsQoS Adaptation via CAs





DualProcesor

DualProcessors

M WAN

SWAN

Res

ou

rces

& R

ole

s

27 25 17

35 22 13

6.1 2.5 0.8

0.6 2.5 0.8


Flat Tree Chain

Topology

MT T

S SS S

M

S S S SS S

STTTTTM

Flat

Tree

Chain

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ConclusionsConclusions

• CAs present a formal model for coordinated communication – Blackboard-based, not FIPA message-based

• Ease use of blackboard-based MAS– Unify Blackboard interfaces, including Web Services– Correlate multiple changes to blackboard objects– Partition the blackboard for domain and system reasons

• Separation of Coordination and Domain processing– Make the intermediary a first-class entity

• Place to add QoS-adaptation

• Future Work– Might facilitate reuse or composability of coordinations– Might examine them in off-line analysis– Might support code generation

Coordination Artifacts in Multi-Agent Systems April 19, 2005 IEEE KIMAS 2005 Sarah Siracuse, John...

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