Multi-agent systems: simulation and applications

541 Pages·2009·16.41 MB·English

by  Adelinde M. Uhrmacher

Multi-Agent
Systems
Simulation and Applications
© 2009 by Taylor and Francis Group, LLC
Computational Analysis, Synthesis,
and Design of Dynamic Models Series
Series Editor
Pieter Mosterman
The MathWorks
Natick, Massachusetts
Discrete-Event Modeling and Simulations: A Practitioner's Approach, Gabriel A. Wainer
Discrete-Event Modeling and Simulations: Theory and Applications, Gabriel A. Wainer
and Pieter J. Mosterman
Model-Based Design for Embedded Systems, Gabriela Nicolescu
Multi-Agent Systems: Simulation & Applications, edited by Adelinde M. Uhrmacher
and Danny Weyns
© 2009 by Taylor and Francis Group, LLC
Computational Analysis, Synthesis,
and Design of Dynamic Models Series
Multi-Agent
Systems
Simulation and Applications
Edited by
Adelinde M. Uhrmacher
Danny Weyns
Boca Raton London New York
CRC Press is an imprint of the
Taylor & Francis Group, an informa business
© 2009 by Taylor and Francis Group, LLC
CRC Press
Taylor & Francis Group
6000 Broken Sound Parkway NW, Suite 300
Boca Raton, FL 33487-2742
© 2009 by Taylor and Francis Group, LLC
CRC Press is an imprint of Taylor & Francis Group, an Informa business
No claim to original U.S. Government works
Printed in the United States of America on acid-free paper
10 9 8 7 6 5 4 3 2 1
International Standard Book Number: 978-1-4200-7023-1 (Hardback)
This book contains information obtained from authentic and highly regarded sources. Reasonable efforts have been
made to publish reliable data and information, but the author and publisher cannot assume responsibility for the valid-
ity of all materials or the consequences of their use. The authors and publishers have attempted to trace the copyright
holders of all material reproduced in this publication and apologize to copyright holders if permission to publish in this
form has not been obtained. If any copyright material has not been acknowledged please write and let us know so we may
rectify in any future reprint.
Except as permitted under U.S. Copyright Law, no part of this book may be reprinted, reproduced, transmitted, or uti-
lized in any form by any electronic, mechanical, or other means, now known or hereafter invented, including photocopy-
ing, microfilming, and recording, or in any information storage or retrieval system, without written permission from the
publishers.
For permission to photocopy or use material electronically from this work, please access www.copyright.com (http://
www.copyright.com/) or contact the Copyright Clearance Center, Inc. (CCC), 222 Rosewood Drive, Danvers, MA 01923,
978-750-8400. CCC is a not-for-profit organization that provides licenses and registration for a variety of users. For
organizations that have been granted a photocopy license by the CCC, a separate system of payment has been arranged.
Trademark Notice: Product or corporate names may be trademarks or registered trademarks, and are used only for
identification and explanation without intent to infringe.
Library of Congress Cataloging-in-Publication Data
Multi-agent systems : simulation and applications / Adelinde M. Uhrmacher and Danny Weyns.
p. cm. -- (Computational analysis, synthesis, and design of dynamic models series ; 4)
Includes bibliographical references and index.
ISBN 978-1-4200-7023-1 (alk. paper)
1. Intelligent agents (Computer software) 2. Distributed artificial intelligence. 3. Computer
simulation. 4. Application software--Development. I. Uhrmacher, Adelinde. II. Weyns, Danny. III.
Title. IV. Series.
QA76.76.I58M864 2009
006.3--dc22 2009016309
Visit the Taylor & Francis Web site at
http://www.taylorandfrancis.com
and the CRC Press Web site at
http://www.crcpress.com
© 2009 by Taylor and Francis Group, LLC
Contents
Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . vii
Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ix
About the Editors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xi
Contributors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xiii
Part I: Background
1 Multi-Agent Systems and Simulation: A Survey from the Agent Commu-
nity’s Perspective
Fabien Michel, Jacques Ferber, and Alexis Drogoul . . . . . . . . . . . . 3
2 Multi-Agent Systems and Simulation: A Survey from an Application
Perspective
Klaus G. Troitzsch . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53
3 Simulation Engines for Multi-Agent Systems
Georgios K. Theodoropoulos, Rob Minson, Roland Ewald, and Michael
Lees . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77
Part II: Simulation for MAS
4 Polyagents: Simulation for Supporting Agents’ Decision Making
H. Van Dyke Parunak and Sven A. Brueckner . . . . . . . . . . . . . . . 109
5 Combining Simulation and Formal Tools for Developing Self-Organizing
MAS
Luca Gardelli, Mirko Viroli, and Andrea Omicini . . . . . . . . . . . . . 133
6 On the Role of Software Architecture for Simulating Multi-Agent Systems
Alexander Helleboogh, Danny Weyns, and Tom Holvoet . . . . . . . . . 167
7 Replicator Dynamics in Discrete and Continuous Strategy Spaces
Karl Tuyls and Ronald Westra . . . . . . . . . . . . . . . . . . . . . . . . 215
8 Stigmergic Cues and Their Uses in Coordination: An Evolutionary
Approach
Luca Tummolini, Marco Mirolli, and Cristiano Castelfranchi . . . . . . 243
Part III: MAS for Simulation
9 Challenges of Country Modeling with Databases, Newsfeeds, and Expert
Surveys
Barry G. Silverman, Gnana K. Bharathy, and G. Jiyun Kim . . . . . . 271
10 Crowd Behavior Modeling: From Cellular Automata to Multi-Agent
Systems
Stefania Bandini, Sara Manzoni, and Giuseppe Vizzari . . . . . . . . . . 301
© 2009 by Taylor and Francis Group, LLC
vi
11 Agents for Traffic Simulation
Arne Kesting, Martin Treiber, and Dirk Helbing . . . . . . . . . . . . . . 325
12 An Agent-Based Generic Framework for Symbiotic Simulation Systems
Heiko Aydt, Stephen John Turner, Wentong Cai, and Malcolm Yoke Hean
Low . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 357
13 Agent-Based Modeling of Stem Cells
Mark d’Inverno, Paul Howells, Sara Montagna, Ingo Roeder, and Rob
Saunders . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 389
Part IV: Tools
14 RoboCup Rescue: Challenges and Lessons Learned
Tomoichi Takahashi . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 423
15 Agent-Based Simulation Using BDI Programming in Jason
Rafael H. Bordini and Jomi F. Hu¨bner . . . . . . . . . . . . . . . . . . . 451
16 SeSAm: Visual Programming and Participatory Simulation for Agent-
Based Models
Franziska Klu¨gl . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 477
17 JAMES II - Experiences and Interpretations
Jan Himmelspach and Mathias Ro¨hl . . . . . . . . . . . . . . . . . . . . . 509
Glossary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 535
© 2009 by Taylor and Francis Group, LLC
Preface
Motivation
Multi-agent systems (MAS) consist of multiple entities called agents that interact in a
shared environment aiming to achieve some individual or collective objective. Simulation
studies the modeling of the operation of a physical or conceptual system over time. For
more than two decades, the field of MAS and the field of simulation have been combined in
veryactivestrandsofresearch. Where, ontheonehand, agentshavebeenusedextensively
as a tool for designing modeling and simulation problems, on the other hand, simulation
has often been used for the design of MAS in a variety of application domains. Bringing
these research endeavors together promises valuable insight and benefits between the two
strands of research. This book aims to integrate and consolidate the acquired knowledge
and experiences, and outline promising directions for future research in this field.
Scope
The focus of this book is on the intersection of MAS, simulation, and application domains.
The book starts from the observation that simulation is being used for agents and agents
are being used for simulation in a variety of application domains.
Simulation is being used for agents. MAS are particularly useful in application domains
thatarecharacterizedbyaninherentdistributionofresourcesandhighlydynamicoperating
conditions. Examples are open electronic markets, traffic and transportation systems, and
supply chain management. Because of the highly dynamic conditions in the environment,
testing by simulation becomes imperative in the software development process of MAS.
Simulation, however, is also exploited for agents’ decision making. For example, software
agents in military systems are equipped with simulation capabilities to reason about the
future effects of their decisions enabling them to select the most suitable actions.
Agents are being used for simulation. A typical example where MAS models are used
in simulation is for simulating traffic situations. In microscopic simulation of traffic situa-
tions, drivers’ behavior can naturally be modeled as agents. Traffic simulations are used to
predict traffic flow, to study the effects of control measures, etc. Another example is the
domain of online simulations that are used to optimize industrial processes. Such systems
apply MAS to exploit their inherent adaptability to cope with the fast evolving distributed
business environment. A simulator gathers data from sensors that are connected to the
real world; it simulates possible future states, and adapts the system based on the outcome
of the simulations. Such systems have been built, for example, for online optimization of
semiconductor manufacturing where quick decision making is required in order to improve
the operational performance of a semiconductor wafer fabrication plant.
Key Aims
The objective of the book is twofold. The first aim is to provide a comprehensive overview
of the research in the intersection of MAS, simulation, and application domains, thereby
consolidating knowledge and experiences. The study of various aspects such as modeling
abstractions, methodological approaches, formal foundations, and platforms in different
© 2009 by Taylor and Francis Group, LLC
viii
domainswillyieldinsightstotheunderlyingprinciplesofMASandsimulation. Thesecond
aimofthebookistoinitiateavenuesforfutureresearch. Inparticular,theaimistooutline
how the obtained insights provide opportunities and enable future research in each of the
related areas: MAS, simulation, and different application domains.
Audience
This book serves different communities. The first audience is the multi-agent system com-
munity, including students in computer science and artificial intelligence, and researchers
and engineers in these fields. The book provides an overview of experiences with MAS
simulation and tools for exploiting simulation in MAS software development, and outlines
promising venues for using simulation in MAS engineering. The second audience is the
modeling and simulation community, including students in computer science, simulation,
mathematics, economics, etc., and researchers and engineers in these fields. The book
presentsmodelingandsimulationtechniquesandtoolsforapplyingMASinsimulationsys-
tems,andidentifiesopportunitiesforfutureresearchinthisarea. Finally,thethirdaudience
includes professionals from various application domains such as civil engineering, biological
systems, transportation and traffic, and factory scheduling and control. The book depicts
experienceswithMASsimulationinthesevariousapplicationdomains;itoffersarepertoire
of concepts and tools to enrich modeling and simulation practice.
Structure of the Book
The book is structured in four parts. Each part consists of a coherent set of chapters that
discuss aspects of MAS and simulation from a particular viewpoint and outline promising
directions for future research. Part I systematically introduces background and basic prin-
ciples. It gives an overview of the intersection and co-evolution of MAS and simulation
from two different perspectives, i.e., the agent community and social science. To illuminate
the richness of methodological developments, the area of simulation engines for MAS is
explored.
Part II discusses the use of simulation in MAS. It explains simulation support for agent
decision making, the use of simulation for the design of self-organizing systems, the role of
softwarearchitectureinsimulatingMAS,andtheuseofsimulationforstudyinglearningand
stigmergicinteractioninMAS.PartIIIzoomsinonMASforsimulation. Discussedsubjects
are an agent-based framework for symbiotic simulation, the use of country databases and
expertsystemsforagent-basedmodelingofsocialsystems,crowd-behaviormodeling,agent-
basedmodelingandsimulationofadultstemcells,andagentsfortrafficsimulation. Finally,
Part IV presents a number of state-of-the-art platforms and tools for MAS and simulation,
including Jason, JAMES II, SeSAm, and RoboCup Rescue.
© 2009 by Taylor and Francis Group, LLC
Acknowledgments
This book has been a joint effort and many people contributed to it. We would like to take
this opportunity to express our thanks.
• For making the book possible: all contributors of this book.
• For enthusiastic and lively discussions about the structure and direction of this
book: all contributors, but in particular Alexander Helleboogh and Jan Him-
melspach.
• For their work in compiling this book, which revealed the non-cooperativity of
diverse LaTeX packages: Nadja Schlungbaum and Jan Himmelspach
• For constructive and detailed reviews on the chapters: all contributors and
BikramjitBanerjee, PeterVrancx,AndreasTolk, LeventYilmaz, MichaelNorth,
David Hales, and Bruce Edmonds.
• For assistance and support: the editor of the series “Computational Analysis,
Synthesis, and Design of Dynamic Models,” Pieter Mosterman, and Taylor &
Francis Group employees Nora Konopka and Amy Blalock.
Adelinde M. Uhrmacher and Danny Weyns
Rostock and Leuven
© 2009 by Taylor and Francis Group, LLC
About the Editors
Adelinde M. Uhrmacher is head of the modeling and simulation group at the Institute
of Computer Science at the University of Rostock. She completed her Ph.D. in Computer
ScienceattheUniversityofKoblenzin1992. Afterwardshedidherpostdoctoralresearchat
theArizonaCenterforIntegrativeModelingandSimulationattheUniversityofArizonain
Tucson. ShewasseniorresearcherattheArtificialIntelligenceLabattheUniversityofUlm
from 1994 until 2000, when she joined the University of Rostock. Her research is aimed at
methodological developments referring to modeling formalisms, simulation methods, tools,
andapplications. TotheformerbelongextensionsoftheDevsformalismwhichaddressthe
agent’s need for dynamic interaction and composition patterns, and parallel discrete event
approaches for simulating multi-agent systems. Application areas span from agent-based
modelingofsocial,economicandcellbiologicalsystemstoexploitingsimulationasameans
in agent-oriented software engineering. The diverse needs of multi-agents applications led
to developing the plug-in based simulation system JAMES II (a JAva based Multipurpose
Environment for Simulation, aka a Java-based Agent Modeling Environment for Simula-
tion). Adelinde Uhrmacher has served on program committees and in the organizations of
various international conferences. She has been member of the editorial board of several
journals and editor-in-chief of the Simulation - Transactions of the SCS from 2000 until
2006.
Danny WeynsreceivedaMaster’sdegreeinElectronicsfromtheHogerInstituutKempen
in1980. HeworkedasalectorattheHogeschoolvoorWetenschapenKunstinBrussels. In
2001,DannyreceivedaMaster’sdegreeinInformaticsfromtheKatholiekeUniversiteitLeu-
ven;andin2006,hereceivedaPh.D.inComputerSciencefromthesameuniversityforwork
on multi-agent systems and software architecture. From 2004–2007, Danny participated in
ajointIWTprojectwithEgeminonthedevelopmentofadecentralizedcontrolarchitecture
for automated guided vehicles. The essential role of simulation in the architectural design
of this real-world multi-agent application is described in one of the chapters in this book.
After finishing his Ph.D. Danny started working as a senior researcher in DistriNet and
is now funded by the Research Foundation Flanders. His main research interests are in
software architecture, self-managing systems, multi-agent systems, and middleware for de-
centralized systems. Danny has published over 80 reviewed articles in these research areas.
Heisco-editoroffourbooksandseveralspecialissuesinjournals. Dannyco-organizedsev-
eral international workshops and special sessions at various international conferences. He
servedontheprogramcommitteeofvariousinternationalconferences,andhehasperformed
review work for several journals.
xi
© 2009 by Taylor and Francis Group, LLC