CLAIM : CLAIM : A Computational Language for A Computational Language for

Autonomous, Intelligent and Mobile agentsAutonomous, Intelligent and Mobile agents

Amal EL FALLAH-SEGHROUCHNI Alexandru SUNA

University of Paris 6University of Paris 6 University of Paris 9University of Paris 9

MotivationsMotivations Think and implement in the same

paradigm: agent

Meet the requirements of:– distribution– migration

Talk OutlineTalk Outline Programming distributed MAS

– Agent Oriented Languages– Ambient Calculus

CLAIM specifications– Agents– Agent’s Reasoning– Example

Implementation aspects– SyMPA– Mobility Protocol– Mobility Completeness

CLAIM Expressiveness Conclusion and perspectives

Agent Oriented LanguagesAgent Oriented Languages (1) (1)

1993, Y.Shoham agent oriented programming

Agents’ characteristics:Agents’ characteristics:

mentalmental state:• beliefs• goals (AgentSpeak, VIVA, 3APL, dMars)• obligations (Agent-0, Agent-K, PLACA)

reasoning mechanismsreasoning mechanisms

capabilities/servicescapabilities/servicesAgent-0, Agent-K, PLACA, AgentSpeak

languages : Agent-0, Agent-K, PLACA, AgentSpeak, VIVA, 3APL, dMars

planning:planning: PLACA, AgentSpeak, 3APL, dMars

communication:communication:

• agent reasoning, without communication :3APL, dMars

• message passing: Agent-0, Agent-K, PLACA, AgentSpeak,VIVA

concurrency:concurrency: AgentSpeak, 3APL, dMars

mobility:mobility: none

Agent Oriented Languages Agent Oriented Languages (2)(2)

Agents’ characteristics:Agents’ characteristics:

Ambient Calculus Ambient Calculus [Cardelli and Gordon, 98][Cardelli and Gordon, 98]

• Interest : improve the modeling of agents' mobilityAmbient :Ambient : • a bounded place

• a name, set of processes and sub-ambients

P,Q ::= processes M[P] ambient (n)P restriction 0 inactivity P | Q composition !P replication M.P capability action (x).P input action M output action

M ::= capabilities x variable n name in n enter into n out n exit out of n open n open n acid open from inside

mv in n move in n mv out n move out of n

+ Reduction rules+ Reduction rules

Ambient Calculus Ambient Calculus [Cardelli and Gordon, 98][Cardelli and Gordon, 98]

Reduction rules:

enter action: enter action: n[in m.P | Q] | m[R] m[n[P | Q] | R ]

exit action:exit action: m[n[out m.P | Q] | R] n[P | Q] | m[R]

replicationreplication: : !P !P | P

open action: open action: open n.P | n[Q] P | Q

other rules:other rules:mv in n.P | n[Q] n[ P | Q ] n[mv out n.P | Q ] P | n[Q]n[acid.P | Q ] P | Q

Communication: Communication: (x).P | M P { xM }

Our CLAIMOur CLAIM

An agent oriented programming language that homogeneously combines:

Intelligence, Autonomy and Mobility

Cognition, Interaction and Concurrence

Agent Languages Concurrent Languages

• goals• knowledge• capabilities• reasoning

• communication primitives

• mobility primitives

Agent DescriptionAgent Description

defineAgent agentName {parent = null | agentName ;knowledge = null | { knowledge;*} ;goals = null | { goal ;* } ;messages = null | { message ;* } ;capabilities = null | { capability ;* } ;processes = null | { process | * } ;agents = null | { agentName ;* } ;

}

defineAgentClass className { ... }newAgent agentName ( className )

Agent’s ComponentsAgent’s Components

knowledgeknowledge

knowledge = agentName (capabilityS,message,effect ) | proposition

goalsgoals

goal = proposition

parentparent

hierarchical structure ; Ambient-Calculus like

VariablesVariablesvariable : variable : ?x , where x could be: • agentName

• capabilitySignature• message• goal• effect

Examples:

forAllKnowledge(?Ag(cap1,?mess,?effect)) { process(?Ag) }

?Ag - all the agents in the knowledge base that have the capacity cap1

forAllAgents(?Ag : className) { process(?Ag) } ?Ag - all the sub-agents of the current agent that belong to the class className

Agents’ CommunicationAgents’ Communicationsend ( receiver, message [, c, [t] ] )

receiver:receiver: • agentName• ?Ag• all (broadcast )• this• ?Ag:className (multicast)

message:message:• proposition• messages concerning the knowledge

tell ( knowledge )askAllCapabilities ( agentName, agentName )askIfCapabiliy ( agentName,agentName,capabilityS )achieveCapability ( agentName,agentName,capabilityS )removeCapability (agentName, capabilityS )

• mobility messages

Messages concerning knowledgeMessages concerning knowledge

A.send(B,tell(knowledge))

the knowledge is added in the knowledge base

A.send(B,askAllCapabilities(A,B))

B.send(A,tell(B(capabilityS,message,effect )))

A.send(B,askIfCapabiliy(A,B,capabilityS))

B.send(A,tell(B(capabilityS,message,effect )))

A.send(B,achieveCapabiliy(A,B,capabilityS))

the capability is performed

A.send(B,removeCapability(A,capabilityS))

the knowledge about this capability is removed

Mobility messagesMobility messagesopenBy(Ag)

- ask open permission

openOK(Ag) ; openNotOK(Ag)- the agent Ag accepts / doesn’t accept to be open

wantOut(Ag)- ask exit permission

outOK(Ag) ; outNotOK(Ag) - the agent Ag gives / doesn’t give the permission

wantIn(Ag)- ask enter permission

inOK(Ag) ; inNotOK(Ag)- the agent Ag gives / doesn’t give the permission

Add permissions to

ambient-calculus primitives

CapabilitiesCapabilitiescapabilities :capabilities :

capability = capabilitySignature { message = null | message ; conditions = null | condition ; do { process }; effects = null | { proposition ;*}

}

condition = function(args*) | agentName.effect | ( condition ) | not condition | condition and condition | condition or condition

ProcessesProcesses

P ::= P.PpropositioninstructionfunctionName([arguments*])newAgent agentName( agentClass )in ( arg,agentName )out ( arg,agentName )moveTo( arg,agentName )open ( agentName )acidsend ( receiver, message [,c [,t]] )

processes :processes :forAllKnowledge (knowledge){ P }

forAllAgents (agentName){ P }

arg = this | clone | process

Agent’s ReasoningAgent’s Reasoning

Forward reasoning::

• choose a messages from the queue of messages• find the capabilities that have this activation message • verify the conditions of the chosen capabilities• execute the corresponding processes

Backward reasoning:

• choose a goal form the goal list• find the capabilities that allow to achieve the goal• verify the conditions of the chosen capabilities update the goals, ask for capabilities• execute the corresponding processes

ExampleExamplee-commerce

Company agent

• knows the names of some Buyer agents• can create Seller agents

Seller agent class

• can migrate• can negotiate with Buyer agents

Buyer agent class

• can negotiate with Seller agents

two solutionsforward reasoning

backward reasoning

Agent definitions Agent definitions (forward - 1)(forward - 1)

defineAgent Company { parent=null ; knowledge= { B1(Buy,buy(),null); B2(Buy,buy(),null); } goals=null; messages=null ; capabilities={

sendSeller { message=sendSeller() ; condition=null; do { newAgent S1(Seller).forAllKnowledge(?Ag(Buy,?mess?eff)) { send(S1,tell(?Ag(Buy,?mess,?eff))) }. send(S1,go()) } effects=null;}useData { message=arriveSeller(?Ag); condition=null; do { computeData() } effects=null;}

} processes= send(this,sendSeller()); agents=null ;}

Agent definitions Agent definitions (forward - 2)(forward - 2)defineAgentClass Seller {

parent=null ;knowledge= null;goals=null;messages=null ;capabilities={

goToBuyer {message=go();condition=null;do { forAllKnowledge(?B(Buy,mess,?eff)){

moveTo(this,?B).negotiate(?B) }.send(this,goToCompany()) }

effects=null;}goToCompany {

message = goToCompany() ; condition=null;do { moveTo(this,Company).send(Company,arriveSeller(this)) }effects=null;

}}processes= null ;agents=null ;

}

Run steps Run steps (forward)(forward)

CompanyCompany S1 : SellerS1 : Seller

send(this,sendSeller)

find capabilities

execute capability

sendSeller()

verify conditions:OK

find, verify, execute goToBuyer()

send(this,goToCompany())

find, verify, execute goToCompany

send(Company,arriveSeller(S1))

Find, verify, execute useData()

send(S1,go())

Agent definitions Agent definitions (backward - 1)(backward - 1)

defineAgent Company { parent=null ; knowledge= null; goals=haveData(); messages=null ; capabilities={

useData { message=arriveSeller(?Ag); condition= ?Ag:Seller.arriveToCompany(); do { computeData(); } effects=haveData();}

} processes= null; agents= { S1; }}

Agent definitions Agent definitions (backward - 2)(backward - 2)

defineAgentClass Seller {parent=Company ;knowledge={ B1(Buy,buy(),null); B2(Buy,buy(),null); }goals=null;messages=null ;capabilities={

goToBuyer {message=go(); condition=null;do { forAllKnowledge(?B(Buy,mess,?eff)){

moveTo(this,?B).negotiate(?B) }.send(this,goToCompany()) }

effects=endNegotiation();}goToCompany {

message = goToCompany() ; condition=this.endNegotiation();do { moveTo(this,Company).send(Company,arriveSeller(this)) }

effects=arriveToCompany();}

}processes= null ;agents=null ;

}

Run steps Run steps (backward)(backward)

CompanyCompany

find capabilities

useData(), effect=haveData()

verify conditions

goal=haveData()

?Ag:Seller.arriveToCompany()

S1 : SellerS1 : Seller

find capabilities

goHome(), effect=arriveHome()

verify conditions

this.endNegotiation()

find capabilities

verify conditions:null

execute capability

goToBuyer(), effect=endNegotiation()

SyMPA ArchitectureSyMPA Architecture(MASIF compliant)(MASIF compliant)

Agent System

Agent

Agent …

I/O

I/O

I/O

Agent System

Agent

Agent …

I/O

I/O

I/O

Central System

I/O

Agent System LevelAgent System Level

Interface + Editor

PSystemDefinitions Base

MASStructure

Interpret

Create agents

PAgent PAgent. . .

Agent LevelAgent Level

PAgent

agentfile

name.agd

Interface

waitmessages

runprocesses

verifygoals

selectcapabilities

selectcapabilities

visualisemodify

update update

Mobility ProtocolMobility Protocol

Agent A

in(this,B)

PSystem A

Agent B

PSystem B

Central System

getAgentIP(B)IP,port(System(B))

wantToSend(B)

IP,port(B)

wantIn(this,A)

inOK(this,B)

Save agent’s state

inAgent(A,B,agent) Restore agent

Update SMA

Update SMA

Verify authority

Mobility CompletenessMobility Completenessalgorithm MobilityOperationInput : agent, SMA

while (not SMA.structureCondition()) do wait(t1)if (SMA.structureCondition()) then

agent.saveState()agent.suspendAllProcesses()agent.askPermission()while (not agent.receivePermission() ) do wait(t2)if (agent.receivePermission()) then

SMA.update()while (not SMA.endUpdating()) do wait(t3)agent.restoreState()agent.resumeAllProcesses()

end ifelse

agent.removeProcess(this)agent.restoreState()agent.resumeAllProcesses()

end elseend if

Language ExpressivenessLanguage ExpressivenessFIPA Contract Net Protocol

Agents Definitions Agents Definitions (FIPA - 1)(FIPA - 1)

defineAgent Initiator {parent=null ;knowledge= null;goals=null;messages=null ;capabilities={ calForProposals {

message=callForProposals();condition=null;do { send(?Ag:Participant,cfp(this) ) }effects=null;

} rejectProposal {

message= propsose(?PAg);condition= reject() ;do { send(?PAg,rejectProposal(this)) }effects=null;

}

acceptProposal {message= propsose(?PAg) ;condition= accept() ;do { send(?PAg,acceptProposal(this)) }effects=null;

}}processes= send(this,callForProposals()) ;agents=null ;

}

Agents Definitions Agents Definitions (FIPA - 2)(FIPA - 2)

Agents Definitions Agents Definitions (FIPA - 3)(FIPA - 3)

defineAgentClass Participant {parent=null ;knowledge= null;goals=null;messages=null ;capabilities={ refuzeCFP {

message=cfp(?IAg) ;condition=notAccept();do { send(?IAg,refuse(this) ) }effects=null;

} notUnderstood {

message= cfp(?IAg); condition=notUnderstood() ;do { send(?IAg,notUnderstood(this) )}effects=null;

} acceptCFP {

message=cfp(?IAg); condition=accept();do { send(?IAg,propose(this) ) }effects=null;

}

Agents Definitions Agents Definitions (FIPA - 4)(FIPA - 4)

failure {message = acceptProposal(?IAg) ;

condition=failure();do { send(?IAg,failure(this) ) }effects=null;

} done {

message = acceptProposal(?IAg) ;condition=done();do { send(?IAg,informDone(this) ) }effects=null;

} ref {

message = acceptProposal(?IAg) ;condition=ref();do { send(?IAg,informRef(this) ) }effects=null;

}}processes= null ;agents=null ;

}

Conclusion: Main ContributionConclusion: Main ContributionCLAIM languageCLAIM language

• Goals, Knowledge, capacities• Backward reasoning: reactive behavior• Forward reasoning : goal driven behavior

• Communication primitives • Mobility primitives

SyMPA systemSyMPA system

• Easy design of distributed MAS • editing agents, interpret, agent interface

• Suitable platform for implementation• management, creation, execution, authentication, migration of agents• protocols for communication and mobility

Expressiveness

Completeness

PerspectivesPerspectives

Define an operational semantics of CLAIMDefine an operational semantics of CLAIM Enrich the languageEnrich the language

– add security primitives and data types

Extend de language possibilities

– develop libraries of agents

– endow agents with learning capacities

Improve SYMPA

– call functions/subroutines defined in other languages

– offer several mechanisms for the management of agents and agent systems

References References • Luca Cardelli, "Abstractions for Mobile Computation", in Secure Internet Programming: Security Issues for Mobile and Distributed Objects. Lecture Notes in Computer Science, Vol. 1603, Springer, pp. 51-94, 1999.

• Luca Cardelli, "Mobile Ambients Synchronisation", SRC Technical Note, 1997.

• Luca Cardelli, A.D. Gordon, "Mobile Ambients", in Foundations of Software Science and Computational Structures, Maurice Nivat (Ed.), Lecture Notes in Computer Science, Vol. 1378, Springer, pp. 140-155, 1998

• Winton H E Davies, Peter Edwards, "Agent-K: An Integration of AOP and KQLM", 1994.

• K.V.Hindriks, F.S.deBoer, W.van der Hoek, J.J.Ch.Meyer, "Agent Programming in 3APL", 1999

•M. d'Inverno, D. Kinny, M. Luck, M. Wooldridge, "A Formal Specification of dMARS", 1998.

• D. Milojicic, M. Breugst, I. Busse, J. Campbell, S. Covaci, B. Friedman, K. Kosaka, D. Lange, K. Ono, M. Oshima, C. Tham, S. Virdhagriswaran, J. White, "MASIF, The OMG Mobile Agent System Interoperability Facility", 1998.

• David Parks, "Agent-Oriented Programming: A Practical Evaluation", 1997.

• Yoav Shoham, "Agent Oriented Programming", Artificial Intelligence (60), pp.51-92, 1993.

• Christian F. Tschudin, "Mobile Agent Security", in Intelligent Information Agents - Agent based information discovery and management on the Internet, Springer, pp. 431-445, 1999.

• Gerd Wagner, "VIVA Knowledge-Based Agent Programming", 1996.

• D.Weerasooriya, Anand S. Rao, K. Ramamohanarao, "Design of a Concurrent Agent-Oriented Language", 1994.

References References