Autonomy Oriented Computing: From Problem Solving to Complex Systems Modeling

249 Pages·2004·6.928 MB·English

by  Jiming Liu, XiaoLong Jin, Kwok Ching Tsui

Autonomy Oriented
Computing
From Problem Solving to
Complex Systems Modeling
MULTIAGENT SYSTEMS,
ARTIFICIAL SOCIETIES, AND
SIMULATED ORGANIZATIONS
International Book Series
Series Editor: Gerhard Weiss, Technische Universität München
Editorial Board:
Kathleen M. Carley, Carnegie Mellon University, PA, USA
Yves Demazeau,CNRS Laboratoire LEIBNIZ, France
Ed Durfee, University of Michigan, USA
Les Gasser, University of Illinois at Urbana-Champaign, IL, USA
Nigel Gilbert, University of Surrey, United Kingdom
Michael Huhns, University of South Carolina, SC, USA
Nick Jennings, University of Southampton, UK
Victor Lesser, University of Massachusetts, MA, USA
Katia Sycara, Carnegie Mellon University, PA, USA
Michael Wooldridge, University of Liverpool, United Kingdom
Books in the Series:
CONFLICTING AGENTS: Conflict Management in Multi-Agent Systems, edited by
CatherineTessier, Laurent Chaudron and Heinz-JürgenMüller, ISBN: 0-7923-7210-7
SOCIAL ORDER IN MULTIAGENT SYSTEMS, edited by RosariaConte and Chrysanthos
Dellarocas, ISBN: 0-7923-7450-9
SOCIALLY INTELLIGENT AGENTS: Creating Relationships with Computers and
Robots, edited by Kerstin Dautenhahn, Alan H. Bond, Lola Cañamero and Bruce Edmonds,
ISBN: 1-4020-7057-8
CONCEPTUAL MODELLING OF MULTI-AGENT SYSTEMS: The CoMoMAS
Engineering Environment, by Norbert Glaser, ISBN: 1-4020-7061-6
GAME THEORY AND DECISION THEORY IN AGENT-BASED SYSTEMS, edited by
Simon Parsons, Piotr Gmytrasiewicz,Michael Wooldridge,ISBN: 1-4020-7115-9
REPUTATION IN ARTIFICIAL SOCIETIES: Social Beliefs for Social Order, by Rosaria
Conte, Mario Paolucci, ISBN: 1-4020-7186-8
AGENT AUTONOMY, edited by Henry Hexmoor, Cristiano Castelfranchi, Rino Falcone,
ISBN: 1-4020-7402-6
AGENT SUPPORTED COOPERATIVE WORK, edited by Yiming Ye, Elizabeth
Churchill, ISBN: 1-4020-7404-2
DISTRIBUTED SENSOR NETWORKS, edited by Victor Lesser, Charles L. Ortiz, Jr.,
Milind Tambe, ISBN: 1-4020-7499-9
AN APPLICATION SCIENCE FOR MULTI-AGENT SYSTEMS, edited by Thomas A.
Wagner, ISBN: 1-4020-7867-6
METHODOLOGIES AND SOFTWARE ENGINEERING FOR AGENT SYSTEMS: The
Agent-Oriented Software Engineering Handbook, edited by Federico Bergenti, Marie-Pierre
Gleizes, Franco Zambonelli
Autonomy Oriented
Computing
From Problem Solving to
Complex Systems Modeling
Jiming Liu
Xiaolong Jin
Kwok Ching Tsui
Hong Kong Baptist University
KLUWER ACADEMIC PUBLISHERS
NEW YORK,BOSTON, DORDRECHT, LONDON, MOSCOW
eBookISBN: 1-4020-8122-7
Print ISBN: 1-4020-8121-9
©2005 Springer Science + Business Media, Inc.
Print ©2005 Kluwer Academic Publishers
Boston
All rights reserved
No part of this eBook maybe reproducedor transmitted inanyform or byanymeans,electronic,
mechanical, recording, or otherwise, without written consent from the Publisher
Created in the United States of America
Visit Springer's eBookstore at: http://ebooks.springerlink.com
and the Springer Global Website Online at: http://www.springeronline.com
To my parents, my wife, Meilee,
and my two daughters, Isabella and Bernice,
who have given me life, love,
inspiration, and purpose.
Jiming Liu
To my wife, Zhen, and my parents,
for their continuous support and endless love.
Xiaolong Jin
To May and Abigail,
the source of unceasing love,
and God the Creator.
Kwok Ching Tsui
This page intentionally left blank
Contents
List of Figures xv
List of Tables xix
List of Algorithms xxi
Preface xxiii
Acknowledgments xxxi
Part I FUNDAMENTALS
1. From Autonomy to AOC 3
1.1 Introduction 3
1.1.1 Complex Multi-Entity Systems 3
1.1.2 Complex Systems Modeling 4
1.2 Basic Concepts and Taxonomies 5
1.2.1 Types of Behavior 5
1.2.2 Autonomy Defined 6
1.3 General AOC Approaches 7
1.4 AOC as a New Computing Paradigm 8
1.4.1 Basic Building Blocks 9
1.4.2 Computational Methodologies 10
1.5 Related Areas 11
1.6 Summary 12
Exercises 14
2. AOC at a Glance 15
2.1 Introduction 15
2.2 Autonomy Oriented Problem Solving 15
viii AUTONOMY ORIENTED COMPUTING
2.2.1 Autonomy Oriented Modeling 15
2.2.2 N-Queen Problem 16
2.3 Autonomy Oriented Search 17
2.3.1 Autonomy Oriented Modeling 17
2.3.2 Image Segmentation Problem 17
2.3.3 An Illustrative Example 19
2.3.4 Computational Steps 19
2.4 Autonomy Oriented Learning 21
2.4.1 World Modeling 21
2.4.2 Self-Organization 22
2.4.3 Adaptation 24
2.5 Summary 25
Exercises 26
3. Design and Engineering Issues 27
3.1 Introduction 27
3.2 Functional Modules in an Autonomous Entity 27
3.3 Major Phases in Developing AOC Systems 29
3.4 Engineering Issues 31
3.5 Features and Characteristics of AOC Systems 33
3.6 Performance Considerations 34
3.7 Simulation Environments 36
3.8 Summary 36
Exercises 38
4. A Formal Framework of AOC 39
4.1 Introduction 39
4.2 Elements of an AOC System 39
4.2.1 Environment 40
4.2.2 Autonomous Entities 40
4.2.3 System Objective Function 44
4.3 Interactions in an AOC System 44
4.3.1 Interactions between Entities and their
Environment 44
4.3.2 Interactions among Entities 45
4.4 Remarks on Homogeneity, Heterogeneity, and
Hierarchy of Entities 48
4.5 Self-Organization in AOC 48
Contents ix
4.5.1 What is Self-Organization? 48
4.5.2 How Does an AOC System Self-Organize? 49
4.6 Summary 52
Exercises 54
Part II AOC IN DEPTH
5. AOC in Constraint Satisfaction 57
5.1 Introduction 57
5.1.1 e-Learning 58
5.1.2 Objectives 60
5.2 Background 62
5.2.1 Conventional Methods 62
5.2.2 Self-Organization Based Methods 64
5.2.3 ERE vs. other Methods 65
5.3 ERE Model 66
5.3.1 General Ideas 68
5.3.2 Environment 70
5.3.3 ERE Entities 72
5.3.4 System Schedule 75
5.3.5 Computational Cost 76
5.3.5.1 Space Complexity 76
5.3.5.2 Time Complexity 78
5.4 An Illustrative Example 79
5.5 Experimentation 81
5.5.1 N-Queen Problems 81
5.5.2 Benchmark SAT Problems 82
5.5.2.1 Fair Measurement 83
5.5.2.2 Performance Evaluation 84
5.6 Discussions 86
5.6.1 Necessity of the Better-Move Behavior 86
5.6.2 Probability Setting 87
5.6.3 Variable Grouping 87
5.6.4 Characteristics of ERE 88
5.6.5 Comparisons with Existing Methods 88
5.6.5.1 Comparison with Min-Conflicts
Heuristics 88