Design and Applications of Intelligent Agents: Third Pacific Rim International Workshop on Multi-Agents, PRIMA 2000 Melbourne, Australia, August 28 – 29, 2000 Proceedings

191 Pages·2000·1.52 MB·English

by  K. S. Barber

Lecture Notes in Artificial Intelligence 1881
SubseriesofLectureNotesinComputerScience
EditedbyJ.G.CarbonellandJ.Siekmann
Lecture Notes in Computer Science
EditedbyG.Goos,J.HartmanisandJ.vanLeeuwen
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Berlin
Heidelberg
NewYork
Barcelona
HongKong
London
Milan
Paris
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Chengqi Zhang Von-Wun Soo (Eds.)
Design and
Applications of
Intelligent Agents
Third Pacific Rim International Workshop
on Multi-Agents, PRIMA 2000
Melbourne, Australia, August 28 - 29, 2000
Proceedings
1 3
SeriesEditors
JaimeG.Carbonell,CarnegieMellonUniversity,Pittsburgh,PA,USA
Jo¨rgSiekmann,UniversityofSaarland,Saarbru¨cken,Germany
VolumeEditors
ChengqiZhang
DeakinUniversity
SchoolofComputingandMathematics
Geelong,Victoria3217,Australia
E-mail:[email protected]
Von-WunSoo
DepartmentofComputerScience
NationalTsingHuaUniversity
Hsin-ChuCity,30043Taiwan
E-mail:[email protected]
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Designandapplicationsofintelligentagents:proceedings/Third
PacificRimInternationalWorkshoponMulti-Agents,PRIMA2000,
Melbourne,Australia,August28-29,2000.ChengqiZhang;Von-Wun
Soo(ed.).-Berlin;Heidelberg;NewYork;Barcelona;HongKong;
London;Milan;Paris;Singapore;Tokyo:Springer,2000
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Preface
PRIMA2000wasthethirdintheseriesofPaci(cid:12)cRimInternationalWorkshops
on Multi-Agents. It was held on August 28-29, 2000, in Melbourne, Australia in
conjunction with the Paci(cid:12)c Rim International Conference on Arti(cid:12)cial Intelli-
gence 2000. PRIMA is the main forum for the agent or multi-agent researchers
in paci(cid:12)c rim countries to exchange and discuss their research results.
This volume contains selected papers from PRIMA 2000. It covers theory,
design, and applications of intelligent agents. The speci(cid:12)c aspects include coor-
dination, negotiation, learning, architecture, speci(cid:12)cation, allocation, and appli-
cation of intelligent agents. All papers are of high quality because each of them
wasreviewedandrecommendedbyatleasttwointernationalrenownedprogram
committee members.
Manypeoplecontributedtothisvolume.Wewouldliketothankalltheaut-
hors who submitted papers to the workshop. Many thanks also to the members
of the program committee who diligently reviewed all the papers. Finally, we
thank the editorial sta(cid:11) of Springer-Verlag for publishing this volume in the
Lecture Notes in Arti(cid:12)cial Intelligence series.
For more information about PRIMA, please check the following web pages:
PRIMA Web page http://www.lab7.kuis.kyoto-u.ac.jp/prima/
PRIMA’99 Web page http://www.lab7.kuis.kyoto-u.ac.jp/prima99/
PRIMA 2000 Web page http://www.lab7.kuis.kyoto-u.ac.jp/prima2000/
June 2000 Chengqi Zhang
Von-Wun Soo
PRIMA 2000 Committee Members
General Chair
Michael George(cid:11)
Agentis International
Melbourne, Australia
george(cid:11)@agentis.com.au
Program Co-chairs
Chengqi Zhang
School of Computing and Mathematics
Deakin University
Geelong, Victoria 3217, Australia
[email protected]
Von-Wun Soo
Department of Computer Science
National Tsing Hua University
Hsin-Chu City, 30043, Taiwan
[email protected]
Publicity Chair
David Kinny
Department of Computer Science
University of Melbourne
Victoria 3010, Australia
Email: [email protected]
Workshop Web Master
Kosuke Nakatsuka
Kyoto University
606-8501 Kyoto, Japan
Email: [email protected]
VIII Organization
Makoto Amamiya Japan
Cristiano CastelfranchiItaly
Brahim Chaib-draa Canada
John Debenham Australia
Tharam Dillon China
Mark d’Inverno UK
Ed Durfee USA
Klaus Fisher Germany
Norbert Glaser Germany
Barbara Grosz USA
Jieh Hsiang Taiwan
Jane Hsu Taiwan
Michael Huhns USA
Toru Ishida Japan
Minkoo Kim Korea
David Kinny Australia
Yasuhiko Kitamura Japan
Kazuhiro Kuwabara Japan
Jaeho Lee Korea
Victor Lesser USA
Ho-fung Leung China
Jyi-shane Liu Taiwan
Jian Lu China
Michael Luck UK
Xudong Luo China
John Jules Meyer Nl
David Morley Australia
Joerg Mueller Germany
Hideyuki Nakashima Japan
Tim Norman UK
Ei-Ichi Osawa Japan
Ichiro Osawa Japan
Sascha Ossowski Spain
Van Parunak USA
Ramakoti Sadananda Thailand
Abdul Satter Australia
Sandip Sen USA
Zhongzhi Shi China
Leon Sterling Australia
Peter Stone USA
Toshiharu Sugawara Japan
Ron Sun USA
Lam Kwok Yan Singapore
Makoto Yokoo Japan
Xinhuo Yu Australia
Soe-Tsyr Yuan Taiwan
Minjie Zhang Australia
Table of Contents
Coordination, Negotiation, and Learning
Coordinating Distributed Decision Making Using Reusable Interaction
Speci(cid:12)cations:::::::::::::::::::::::::::::::::::::::::::::::::::::: 1
K.S. Barber, D.C. Han, and T.H. Liu
Dynamic Properties of Multiagents Based on a Mechanism of Loose
Coalition ::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 16
Takashi Katoh, Tetsuo Kinoshita, and Norio Shiratori
Agent Negotiation under Uncertainty and Risk :::::::::::::::::::::::: 31
Von-Wun Soo
Argumentation as a Social Computing Paradigm::::::::::::::::::::::: 46
Yuichi Umeda, Massashi Yamashita, Masanobu Inagaki, and
Hajime Sawamura
Rationality Assumptions and Optimality of Co-learning :::::::::::::::: 61
Ron Sun and Dehu Qi
Architecture, Speci(cid:12)cation, and Allocation
Experiences in the Development of an Agent Architecture :::::::::::::: 76
Geo(cid:11) Bush, Martin Purvis, and Stephen Crane(cid:12)eld
Building a Network Community Support System on the Multi-agent
Platform Shine::::::::::::::::::::::::::::::::::::::::::::::::::::: 88
Sen Yoshida, Koji Kamei, Takeshi Ohguro, Kazuhiro Kuwabara, and
Kaname Funakoshi
A Secure Route Structure for Information Gathering Agent ::::::::::::: 101
Tieyan Li, Chuk-Yang Seng, and Kwok-Yan Lam
An Approach to Specifying Coordinated Agent Behaviour :::::::::::::: 115
Kenichi Yoshimura, Ralph Ro¨nnquist, and Liz Sonenberg
Specifying Agent Behaviour with Use Cases ::::::::::::::::::::::::::: 128
Clinton Heinze, Michael Papasimeon, and Simon Goss
Market-Based Network Resource Allocation with Non-t^atonnement
Process ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 143
Kosuke Nakatsuka, Hirofumi Yamaki, and Toru Ishida
X Table of Contents
Applications
Autonomous Cooperative Factory Control::::::::::::::::::::::::::::: 156
Dave Vasko, Francisco Maturana, Angela Bowles,
and Stephen Vandenberg
Delegation of Responsibility in an Agent-Based Process Management
System ::::::::::::::::::::::::::::::::::::::::::::::::::::::::::: 170
John Debenham
Coordinating Distributed Decision Making
Using Reusable Interaction Speci(cid:12)cations
K.S. Barber, D.C. Han, and T.H. Liu
The University of Texas at Austin
Department of Electrical and Computer Engineering
24th and Speedway, ENS 240
[email protected]
Abstract. The organization structure of Multi-Agent Systems (MAS)
constrainsthemechanismsthatmaybeusedforcoordinatingtheagents’
decision-making process. As researchers develop MAS that allow agents
to dynamically re-organize how to interact with each other, the design
of the agents must provide the ability to operate under di(cid:11)erent orga-
nizations. This paper investigates the issues involved in increasing the
flexibility of agents’ coordination capabilities. Applying the concepts of
encapsulation and polymorphism, a representation of coordination stra-
tegies is presented as an abstraction that allows agents to easily switch
coordination mechanisms and that allows coordination mechanisms to
be applied to di(cid:11)erent domains.
1 Introduction
Agents can be generally described as independent entities equipped with some
amount of decision-making power. A Multi-Agent System (MAS) can be seen
as a group of entities interacting to achieve individual or collective goals. In the
past two decades, researchers have developed various designs for MAS architec-
tures; some of them are equipped with the ability to dynamically modify agent
organizational structures [2,13,14,24]). Equipping agents with such abilities is
motivated by the fact that one speci(cid:12)c organizational structure is not suitable
for all situations in dynamic environments [3]. Take Sensible Agents [6] for ex-
ample,theyareequippedwiththecapabilitytoreasonaboutandswitchamong
levelsofautonomy.Typicalautonomylevels(whichareassignedtogoalsinstead
ofagents)include:command-driven,master,consensus,andlocallyautonomous.
If the agent is at command-driven level, it does not make decisions and must
obey orders given by a master agent. If the agent is at consensus level, it works
as a team member, sharing decision-making tasks equally with other agents. If
the agent is at locally autonomous or master levels, it makes decisions alone.
Coordinationofthedecision-makingprocessesinsuchdynamicallyorganized
multi-agent systems must be flexible. The agents must have the ability to inter-
actunderanyorganizationthattheymay(cid:12)ndthemselvesin.Justasthereisno
best organization structure for all situations, there is no best coordination tech-
nique for all organizations. This paper describes our work in equipping agents
C.ZhangandV.-W.Soo(Eds.):PRIMA2000,LNAI1881,pp.1{15,2000.
(cid:13)c Springer-VerlagBerlinHeidelberg2000