A Colored Petri Net for a Multi-Agent Application Aarhus, Denmark - August 27, 2002 MOCA ‘02 Danny Weyns & Tom Holvoet K.U.Leuven - Belgium

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verifications Conclusions & future work

Situation of the paper General goal of our research: better understanding of sociality in multi-agent systems generic conceptual model of social agents situated in a multi-agent system which concepts does an agent need in order to acquire social abilities ? which infrastructure is necessary in the environment to support these abilities ?

Situation of the paper This paper: –realization of 2 basic models for Packet-World –first experiments Case application = Packet-World Our approach: combine experiments with conceptual modeling Conceptual Modeling: Colored Petri-Nets

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verification Conclusions & future work

The Packet-World Discrete world, agents act autonomously (parallel) Problem for the agents: clean up the world as efficiently as possible Agents have only limited view Interaction primitives –step, skip, pick up / put down packet –communication with other agents packet destination view of agent 2

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verification Conclusions & future work

Basic model for the Packet-World Agent with goals: - pick up packet - deliver packet Environment with: - agents - packets - destinations Synchronization Module: - synchronizes percepts and actions Approach: building up the multi-agent system by means of compositional modules

Basic model: Action cycle

Basic model: CPN for the Environment Place ENVIRONMENT –contains the objects in the world color Item = record name:Name * coord:Coordinate; color World = list Item with 1..(worldsize*worldsize); COUNT registers the invested energy so far SYNC transports synch tokens to synch module PRODUCE_PERCEPT updates percepts –when syncout contains a token –as long as PACKET_COUNT contains a token

Basic model: CPN for the Environment Reactions are modeled as transitions reaction Move token World token [ guard ] World token Agent token Perform place Consume place ENVIRONMENT SYNC T token Count T token

Basic model: CPN for an Agent Place ready contains initial Agent token –color Agent = record name:Name * coord:Coordinate * carry:Name; Agent gets view on the world from percept place –color View = list of Item with 1..viewsize * viewsize; Tokens enter the agent-net only after identification = compare Name token in identity place beliefbase contains Belief records –color Belief = record subj:BeliefSubj * item:Item; –color BeliefSubj = with pRec | dRec;

Basic model: CPN for an Agent Actions are modeled as transitions action Move token [ guard ] Agent token Belief token Perform place beliefbase view View token lookfor place

Basic model: CPN for the Sync module Goal = synchronization of perceptions and actions in a loop so that: –ensures that agents are treaded as acting simultaneously –the environment reacts only subsequently How: –collect synchronization tokens from environment –trigger environment as soon as the reactions for all agents are handled to produce new percepts

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verification Conclusions & future work

Extended model for the Packet-World Agents - communicate information - extended with communication module Environment: - extended with Postal Service Synchronization Module: - sending a message = first class action

Extended model: C ommunication module Messages –color Message = record from:Name * to:Name * perform:Performative * content:Item; –color Performative = with questP | answP | noanswP | questD …; Questions: –askfor when agent lacks information to handle –queue regulation limits number of messages Answers: –responce produces an answer –processanswer accepts an answer = updates belief base

Extended model: Postal Service 1 global inbox - 1 mailbox / agent addresses contains Mailbox address of each agent delivering a message produces a sync token msgcount and msglog for statistic information

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verification Conclusions & future work

Experiments Rounded averages for 5 jobs view-size increases = COUNT decreases Effect communication greatest for limited view-sizes Better founded conclusions = more tests (world- & view-size / nbAgents)

Verifications Standard report of Design/CPN tool –e.g, “Dead Transition Instances” indicates possible conflicts By means of Occurrence Graph tool –node for each reachable marking –arc for each occurring binding –2 verifications: deadlock free & correctly solved worlds

Verifications –Packet-World = free of deadlocks “there exists a path from each node in the graph to the node node that represents the final marking” (*proof 1*) –Job is correctly solved in a limited number of steps (1) “in each node except the leaf node, the sum of tokens for PACKETS_ON_GRID, CARRIED_PACKERTS and DELIVERED_PACKETS = nbPackets” (*proof 2*) (2) (*proof 1*)

Outline Situating the paper in our research The Packet-World Basic model for the Packet-World Extended model Experiments and verification Conclusions & future work

Conclusions –Contribution of this paper: practical realization of CPN for a multi-agent application solid basis for future research of agents’ social behavior –Remarks with regard to CPNs for modeling MASs CPNs have a strong graphical expressiveness –compositional modules –every aspect must unambiguously be modeled simulation of the model itself supports formal verification

Future work –Building modules for other kind of social skills e.g., cooperative agents that form a chain and passing packets; coordination to avoid future conflicts –tackle complexity by means of hierarchical CPNs –generalize insights deduced from Packet-World build abstract models for different levels of social skills aggregate of these models = well defined / easy to communicate formal model of social agents of a MAS

Thanks for your attention !