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Algorithms and Ordering Heuristics for Distributed Constraint Satisfaction Problems

FOCUS Series in Computer Science and Information Technology

Mohamed Wahbi, Ecole des Mines de Nantes, France

ISBN: 9781848215948

Publication Date: June 2013   Hardback   176 pp.

75.00 USD


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Description

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.

Contents

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.

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.

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