Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems

ISBN-13: 9781848215948 / Angielski / Twarda / 2013 / 176 str.

Mohamed Wahbi

Opis

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.

Spis treści

PREFACE ix

INTRODUCTION xiii

PART 1. BACKGROUND ON CENTRALIZED AND DISTRIBUTED CONSTRAINT REASONING 1

CHAPTER 1. CONSTRAINT SATISFACTION PROBLEMS 3

1.1. Centralized constraint satisfaction problems 3

1.3. Summary 28

CHAPTER 2. DISTRIBUTED CONSTRAINT SATISFACTION PROBLEMS 29

2.1. Distributed constraint satisfaction problems 29

2.2. Methods for solving DisCSPs 36

2.3. Summary 47

PART 2. SYNCHRONOUS SEARCH ALGORITHMS FOR DISCSPS 49

CHAPTER 3. NOGOOD–BASED ASYNCHRONOUS FORWARD CHECKING (AFC–NG) 51

3.1. Introduction 51

3.2. Nogood–based asynchronous forward checking 53

3.3. Correctness proofs 59

3.4. Experimental evaluation 60

3.5. Summary 68

CHAPTER 4. ASYNCHRONOUS FORWARD–CHECKING TREE (AFC–TREE) 69

4.1. Introduction 69

4.2. Pseudo–tree ordering 70

4.3. Distributed depth–first search tree construction 72

4.4. The AFC–tree algorithm 75

4.5. Correctness proofs 79

4.6. Experimental evaluation 79

4.7. Other related works 85

4.8. Summary 86

CHAPTER 5. MAINTAINING ARC CONSISTENCY ASYNCHRONOUSLY IN SYNCHRONOUS DISTRIBUTED SEARCH 87

5.1. Introduction 87

5.2. Maintaining arc consistency 88

5.3. Maintaining arc consistency asynchronously 89

5.4. Theoretical analysis 94

5.5. Experimental results 95

5.6. Summary 99

PART 3. ASYNCHRONOUS SEARCH ALGORITHMS AND ORDERING HEURISTICS FOR DISCSPS 101

CHAPTER 6. CORRIGENDUM TO MIN–DOMAIN RETROACTIVE ORDERING FOR ASYNCHRONOUS
BACKTRACKING 103

6.1. Introduction 103

6.2. Background 104

6.3. ABT—DO–Retro may not terminate 106

6.4. The right way to compare orders 108

6.5. Summary 110

CHAPTER 7. AGILE ASYNCHRONOUS BACKTRACKING (AGILE–ABT) 111

7.1. Introduction 111

7.2. Introductory material 113

7.3. The algorithm 117

7.4. Correctness and complexity 120

7.5. Experimental results 123

7.6. Related works 129

7.7. Summary 130

PART 4. DISCHOCO 2.0: A PLATFORM FOR DISTRIBUTED CONSTRAINT REASONING 131

CHAPTER 8. DISCHOCO 2.0 133

8.1. Introduction 133

8.2. Architecture 134

8.3. Using DisChoco 2.0 137

8.4. Experimentations 140

8.5. Conclusion 142

CONCLUSIONS 143

BIBLIOGRAPHY 147

INDEX 157

O autorze

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.

Blurb

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 of the problem, i.e. 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.