A Colored Petri Net for a Multi-Agent Application

Aarhus, Denmark - August 27, 2002

MOCA ‘02

Danny Weyns & Tom HolvoetK.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 1 Agent 2

EnvironmentSyncModule

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

percept synchronization

percept calculation

reasoning

1 action cycle

sync module

agent 1

agent 2

consumption

percept update

reactions

environment

influences

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 tokenPerform placeConsume place

ENVIRONMENTSYNCT 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 tokenBelief token

Perform place

beliefbase

viewView 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

Basicagent 1

Basicagent 2

EnvironmentSyncModule

Communicationmodule

Communicationmodule

Postal Service

Extended model: Communication 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)

World view-size Kind of model COUNT % gain msgcount

basic 26 --2communication 18

314

basic 15 --

world-size = 5

nbAgents = 2

nbPackets = 5 3communication 14

72

basic 167 --3communication 129

2316

basic 110 --

world-size = 8

nbAgents = 2

nbPackets = 16 4communication 108

22

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 !http://www.cs.kuleuven.ac.be/~danny/home.html