Distributed Constraint Satisfaction : Foundations of Cooperation to Multi-Agent Systems

By: Makoto Yokoo

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When multiple agents are in a shared environment, there usually exist con- straints among the possible actions of these agents. A distributed constraint satisfaction problem (distributed CSP) is a problem in which the goal is to find a consistent combination of actions that satisfies these inter-agent constraints. More specifically, a distributed CSP is a constraint satisfaction problem (CSP) in which multiple agents are involved. A constraint satisfaction problem is a problem in which the goal is to find a consistent assignment of values to variables. Even though the definition of a CSP is very simple, a surprisingly wide variety of artificial intelligence (AI) problems can be formalized as CSPs. Therefore, the research on CSPs has a long and distinguished history in AI (Mackworth 1992; Dechter 1992; Tsang 1993; Kumar 1992). A distributed CSP is a CSP in which variables and constraints are distributed among multiple autonomous agents. Various application problems in Multi-agent Systems (MAS) that are concerned with finding a consistent combination of agent actions can he formalized as dis- tributed CSPs. Therefore, we can consid( r distributed CSPs as a general framework for MAS, and algorithms for solving distributed CSPs as impor- tant infrastructures for cooperation in MAS. This book gives an overview of the research on distributed CSPs, as well as introductory material on CSPs. In Chapter 1. we show the problem defi- nition of normal, centralized CSPs and describe algorithms for solving CSPs.

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Non-Fiction Computing & I.T.Computer Science Artificial Intelligence Computer Networking & Communications Computer Programming & Software Development Algorithms & Data Structures Computer Hardware Network Hardware

Constraint Satisfaction Problem	p. 1
Introduction	p. 1
Problem De nition	p. 2
Algorithms for Solving CSPs	p. 7
Backtracking	p. 8
Iterative Improvement	p. 15
Consistency Algorithms	p. 16
Hybrid-Type Algorithm of Backtracking and Iterative Improvement	p. 20
Weak-Commitment Search Algorithm	p. 20
Example of Algorithm Execution	p. 22
Evaluations	p. 23
Algorithm Complexity	p. 27
Analyzing Landscape of CSPs	p. 28
Introduction	p. 28
Hill-Climbing Algorithm:	p. 30
Analyzing State-Space	p. 32
Discussions	p. 37
Partial Constraint Satisfaction Problem	p. 42
Introduction	p. 42
Formalization	p. 43
Algorithms	p. 43
Summary	p. 44
Distributed Constraint Satisfaction Problem	p. 47
Introduction	p. 47
Problem Formalization	p. 47
Application Problems	p. 49
Recognition Problem:	p. 49
Allocation Problem	p. 50
Multi-agent Truth Maintenance	p. 53
Time-Tabling/Scheduling Tasks	p. 53
Classi cation of Algorithms for Solving Distributed CSPs	p. 54
Summary	p. 54
Asynchronous Backtracking:	p. 55
Introduction	p. 55
Assumptions	p. 55
Simple Algorithms	p. 56
Centralized Method:	p. 56
Synchronous Backtracking	p. 57
Asynchronous Backtracking Algorithm	p. 58
Overview	p. 58
Characteristics of the Asynchronous Backtracking Algorithm	p. 60
Example of Algorithm Execution	p. 63
Algorithm Soundness and Completeness	p. 64
Evaluations	p. 66
Summary	p. 68
Asynchronous Weak-Commitment Search	p. 69
Introduction	p. 69
Basic Ideas	p. 70
Details of Algorithm	p. 71
Example of Algorithm Execution	p. 73
Algorithm Completeness	p. 74
Evaluations	p. 75
Summary	p. 78
Distributed Breakout	p. 81
Introduction	p. 81
Breakout Algorithm	p. 81
Basic Ideas	p. 82
Details of Algorithm	p. 84
Example of Algorithm Execution	p. 85
Evaluations	p. 87
Discussions	p. 92
Summary	p. 92
Distributed Consistency Algorithm	p. 93
Introduction	p. 93
Overview of Distributed ATMS:	p. 93
ATMS	p. 93
Distributed ATMS:	p. 94
Distributed Consistency Algorithm Using Distributed ATMS	p. 94
Example of Algorithm Execution	p. 96
Evaluations	p. 97
Summary	p. 100
Handling Multiple Local Variables 101
Introduction 101
Agent-Prioritization Approach 102
Asynchronous Weak-Commitment Search with Multiple Local Variables	p. 103
Basic Ideas	p. 103
Details of Algorithm	p. 104
Example of Algorithm Execution	p. 104
Evaluations	p. 107
Summary	p. 110
Handling Over-Constrained Situations	p. 113
Introduction	p. 113
Problem Formalization	p. 113
Distributed Maximal CSPs	p. 114
Problem Formalization	p. 114
Algorithms	p. 115
Evaluations	p. 120
Distributed Hierarchical CSPs	p. 123
Problem Formalization	p. 123
Asynchronous Incremental Relaxation	p. 124
Example of Algorithm Execution	p. 128
Algorithm Completeness	p. 129
Evaluations	p. 129
Summary	p. 132
Summary and Future Issues	p. 133
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Distributed Constraint Satisfaction : Foundations of Cooperation to Multi-Agent Systems

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