Bringing discrete event simulation concepts into multi agent systems ppt97__20080331

The 10th International Computer Modelling and Simulation Conference, EUROSIM-UKSim08
April 1st – 3rd, Cambridge, UK, 2008 1
Bringing Discrete Event Simulation
Concepts into Multi-Agent Systems
Daniele Gianni
Dept. of Computer Science
University of Rome TorVergata,
Rome, Italy
gianni@info.uniroma2.it

2
Outline
 Agent-based Modelling (ABM) Paradigm
 Modelling Discrete Event Simulation (DES)
System with ABM
 Brief overview of JADE
 Design of SimJADE
 Example application
April 1st – 3rd, Cambridge, UK, 2008

3
Agent-based Modelling Paradigm
 Based on the concept of agent
 Agent:
• Autonomous, social, reactive
• Possibly intelligent (intelligent agent):
 Adaptation, reasoning and learning abilities
 Multi-Agent System (MAS):
• A society of agents
• Agents collaborate for a common goal, and compete
for individual goals
• Agents share a semantic base for the communication

4
Agent-based Modelling Paradigm in Simulation
The incorporation of agents technology in
simulation systems origins from:
 Need of modelling adaptation, reasoning and
learning abilities to increase the realism of
human behaviour
 Reflection of real systems structure, which is
based on autonomous, interacting and possibly
intelligent entities

5
DES Process Interaction (PI) Paradigm
 PI paradigm is based on:
Independent Logical Processes (LPs) that perform
internal computation and exchange events according
to properties of causality and reproducibility.
 LPs are typically:
• Simulation entities, which incorporates simulation logic
• Simulation engine, which coordinates the entities
 Other more decentralised structures are possible
(e.g. as in parallel simulation)

6
ABM of DES PI System
DES PI System as MAS:
 LPs: autonomous, interacting
 Common goal: to carry out the simulation
according to the properties of causality and
reproducibility
 Individual goal: to use the physical resources to
carry out the simulation of their part of model
 LPs share semantic of simulation time and
simulation services (e.g. send event or time
notification)

7
JADE
 Is a Java-based framework for the development
of MAS
 FIPA Compliant
 Defines:
• Agents (state)
• Behaviours (dynamic)
• Communications
 Message (Sender, Recipient, Performative Act, Content,
Ontology, Language)
 Basic Ontology (Concepts, Actions)

8
SimJADE
 Java framework for Agent-based M&S
 JADE-based, thus FIPA compliant
 Defined through:
• Simulation Ontology
• Simulation Agent Society
• Simulation Behaviours
• Simulation Event Handlers

9
DES-Ontology
 Concepts:
• Absolute Simulation Time
• Relative Simulation Time
 Actions:
• Simulation Life Cycle Management (e.g. Register
Agent, Simulation End, or Registration Successful)
• Simulation Services (e.g. Send/Notify Event, Notify
Time, or Wait Event)

10
Simulation Agent Society
 Currently, the agent society is composed by:
• A Simulation Engine Agent, which orchestrates the
simulation agent society
• One or more Simulation Entity Agents, which
incorporate simulation logic

11
Life Cycle of Simulation Engine Agent
Waiting for Registration requests
Waiting for Simulation requests
Processing an internal event
Society Complete
Confirm RegistrationSuccessful
RegisterAgent
Agent running == 0
ConditionalHold / Hold /
WaitEvent / SendEvent /
RemoveAgent /
Register Agent
Simulation End Notification
Simulation End
Phase 1
Phase 2
Phase 3
Processing next internal event

12
Life Cycle of Simulation Entity Agents
Running
Hold WaitEvent HoldUnlessIncomingEvent
Hold
WaitEvent
ConditionalHold
Waiting for Registration Acknowledge
RegisterAgent
RegistrationSuccessful
NotifyTime or
SimulationEvent NotifyEvent or
SimulationEnd
NotifyTime,
NotifyEvent or
SimulationEnd
SimulationEvent

13
Simulation Behaviours
Behaviours can be of three types:
• Simulation Service Behaviours – implement
simulation services
• Simulation Life Cycle Behaviours – regulate
simulation agents’ life cycle
• Model Behaviours – “empty” behaviours to
plug conventional JADE behaviours in
SimJADE

14
Example Application
 Manufacturing Simulation
 Workers move around a factory and use the
machines
 They compete for the use of physical resources
and machines
 The space model is defined by nodes (possible
positions) and edges (space of movements)
 Each worker is autonomous and decides where
to go and which machines to use
 We shall not consider interactions among agents

15
Example Application
Civilian Civilian 2 ResourceManager
Arrived at (node i, time t2)
Arrived at
(node i, time t1)
Wall-clock
time
Authorized to Move (time t1)
Finished Movement (time t3)
Authorized toMove (time t3)
... ... ...
Sim-time
0
Sim-time
0
Sim-time
0
Sim-time
t1
Wait Event
Wait Event
Sim-time
t3
Sim-time
t1
Sim-time t3
Wait Event
Wait Event
Wait Event
Worker1 Worker2
Civilian Civilian 2 ResourceManagerWall-clock
time
... ... ...
Register Agent
SimulationEngine
Register AgentRegister Agent
Registration
Successful
Registration
Successful
Registration
Successful
...
Sim Time = 0
Sim Time = 0
Sim Time = 0
Worker1 Worker2

16
Conclusion
 Agent-technologies have been incorporated in
simulation systems to increase realism and to
ease the modelling of real systems
 We presented an agent-based formulation of
DES systems through the design of a software
framework named SimJADE
 SimJADE introduces concepts and behaviours
that can contain standard JADE component, and
thus makes the simulator development
transparent to MAS developers

Bringing discrete event simulation concepts into multi agent systems ppt97__20080331

More Related Content

Similar to Bringing discrete event simulation concepts into multi agent systems ppt97__20080331

More from Daniele Gianni

Recently uploaded

Bringing discrete event simulation concepts into multi agent systems ppt97__20080331