Algorithms and ordering heuristics for distributed constraint satisfaction problems

DisCSP (Distributed Constraint Satisfaction Problem) is a general framework for solving distributed problems arising in Distributed Artificial Intelligence.
A wide variety of problems in artificial intelligence are solved using the constraint satisfaction problem paradigm. However, there are several applications in multi-agent coordination that are of a distributed nature. In this type of application, the knowledge about the problem, that is, variables and constraints, may be logically or geographically distributed among physical distributed agents. This distribution is mainly due to privacy and/or security requirements. Therefore, a distributed model allowing a decentralized solving process is more adequate to model and solve such kinds of problem. The distributed constraint satisfaction problem has such properties.

Contents

Introduction
Part 1. Background on Centralized and Distributed Constraint Reasoning
1. Constraint Satisfaction Problems
2. Distributed Constraint Satisfaction Problems
Part 2. Synchronous Search Algorithms for DisCSPs
3. Nogood Based Asynchronous Forward Checking (AFC-ng)
4. Asynchronous Forward Checking Tree (AFC-tree)
5. Maintaining Arc Consistency Asynchronously in Synchronous Distributed Search
Part 3. Asynchronous Search Algorithms and Ordering Heuristics for DisCSPs
6. Corrigendum to "Min-domain Retroactive Ordering for Asynchronous Backtracking"
7. Agile Asynchronous BackTracking (Agile-ABT)
Part 4. DisChoco 2.0: A Platform for Distributed Constraint Reasoning
8. DisChoco 2.0
9. Conclusion

About the Authors

Mohamed Wahbi is currently an associate lecturer at Ecole des Mines de Nantes in France. He received his PhD degree in Computer Science from University Montpellier 2, France and Mohammed V University-Agdal, Morocco in 2012 and his research focused on Distributed Constraint Reasoning.

Author Notes

Mohamed Wahbi is currently an associate lecturer at Ecole des Mines de Nantes in France. He received his PhD degree in Computer Science from University Montpellier 2, France and Mohammed V University-Agdal, Moracco in 2012 and his research focused on distributed Constraint Reasoning.

Preface	p. ix
Introduction	p. xiii
Part 1 Background on Centralized and Distributed Constraint Reasoning	p. 1
Chapter 1 Constraint Satisfaction Problems	p. 3
1.1 Centralized constraint satisfaction problems	p. 3
1.1.1 Preliminaries	p. 4
1.1.2 Examples of CSPs	p. 5
1.2 Algorithms and techniques for solving centralized CSPs	p. 10
1.2.1 Algorithms for solving centralized CSPs	p. 10
1.2.2 Variable ordering heuristics for centralized CSPs	p. 23
1.3 Summary	p. 28
Chapter 2 Distributed Constraint Satisfaction Problems	p. 29
2.1 Distributed constraint satisfaction problems	p. 29
2.1.1 Preliminaries	p. 30
2.1.2 Examples of DisCSPs	p. 32
2.1.3 Distributed meeting scheduling problem (DisMSP)	p. 32
2.1.4 Distributed sensor network problem (SensorDCSP)	p. 34
2.2 Methods for solving DisCSPs	p. 36
2.2.1 Synchronous search algorithms on DisCSPs	p. 37
2.2.2 Asynchronous search algorithms on DisCSPs	p. 40
2.2.3 Dynamic ordering heuristics on DisCSPs	p. 44
2.2.4 Maintaining arc consistency on DisCSPs	p. 47
2.3 Summary	p. 47
Part 2 Synchronous Search Algorithms for DisCSPs	p. 49
Chapter 3 Nogood-Based Asynchronous Forward Checking (AFC-NG)	p. 51
3.1 Introduction	p. 51
3.2 Nogood-based asynchronous forward checking	p. 53
3.2.1 Description of the algorithm	p. 53
3.2.2 A simple example of the backtrack operation on AFC-like algorithms	p. 57
3.3 Correctness proofs	p. 59
3.4 Experimental evaluation	p. 60
3.4.1 Uniform binary random DisCSPs	p. 61
3.4.2 Distributed sensor-target problems	p. 62
3.4.3 Distributed meeting scheduling problems	p. 64
3.4.4 Discussion	p. 67
3.5 Summary	p. 68
Chapter 4 Asynchronous Forward-Checking Tree (AFC-TREE)	p. 69
4.1 Introduction	p. 69
4.2 Pseudo-tree ordering	p. 70
4.3 Distributed depth-first search tree construction	p. 72
4.4 The AFC-tree algorithm	p. 75
4.4.1 Description of the algorithm	p. 77
4.5 Correctness proofs	p. 79
4.6 Experimental evaluation	p. 79
4.6.1 Uniform binary random DisCSPs	p. 80
4.6.2 Distributed sensor-target problems	p. 82
4.6.3 Distributed meeting scheduling problems	p. 84
4.6.4 Discussion	p. 84
4.7 Other related works	p. 85
4.8 Summary	p. 86
Chapter 5 Maintaining Arc Consistency Asynchronously in Synchronous Distributed Search	p. 87
5.1 Introduction	p. 87
5.2 Maintaining arc consistency	p. 88
5.3 Maintaining arc consistency asynchronously	p. 89
5.3.1 Enforcing AC using del messages (MACA-del)	p. 90
5.3.2 Enforcing AC without additional kind of message (MACA-not)	p. 93
5.4 Theoretical analysis	p. 94
5.5 Experimental results	p. 95
5.5.1 Discussion	p. 99
5.6 Summary	p. 99
Part 3 Asynchronous Search Algorithms and Ordering Heuristics for DisCSPs	p. 101
Chapter 6 Corrigendum to "Min-Domain Retroactive Ordering for Asynchronous Backtracking"	p. 103
6.1 Introduction	p. 103
6.2 Background	p. 104
6.3 ABT_DO-Retro may not terminate	p. 106
6.4 The right way to compare orders	p. 108
6.5 Summary	p. 110
Chapter 7 Agile Asynchronous Backtracking (Agile-ABT)	p. 111
7.1 Introduction	p. 111
7.2 Introductory material	p. 113
7.2.1 Reordering details	p. 113
7.2.2 The backtracking target	p. 114
7.2.3 Decreasing termination values	p. 116
7.3 The algorithm	p. 117
7.4 Correctness and complexity	p. 120
7.5 Experimental results	p. 123
7.5.1 Uniform binary random DisCSPs	p. 124
7.5.2 Distributed sensor target problems	p. 125
7.5.3 Discussion	p. 128
7.6 Related works	p. 129
7.7 Summary	p. 130
Part 4 DisChoco 2.0: A Platform for Distributed Constraint Reasoning	p. 131
Chapter 8 DisChoco 2.0	p. 133
8.1 Introduction	p. 133
8.2 Architecture	p. 134
8.2.1 Communication system	p. 135
8.2.2 Event management	p. 136
8.2.3 Observers in layers	p. 137
8.3 Using DisChoco 2.0	p. 137
8.4 Experimentations	p. 140
8.5 Conclusion	p. 142
Conclusions	p. 143
Bibliography	p. 147
Index	p. 157

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