Dynamic Backtracking for Distributed Constraint Optimization

We propose a new algorithm for solving Distributed Constraint Optimization Problems (DCOPs). Our algorithm, called DyBop, is based on branch and bound search with dynamic ordering of agents. A distinctive feature of this algorithm is that it uses the concept of valued nogood. Combining lower bounds on inferred valued nogoods computed cooperatively helps pruning dynamically unfeasible sub-problems and speeds up the search. DyBop requires a polynomial space at each agent. Experiments show that DyBop has significantly better performance than other DCOP algorithms.

• Type: Conference
• Year: 2008
• Where: ECAI
• Authors: Redouane Ezzahir, Christian Bessiere, Imade Benelallam, Houssine Bouyakhf, Mustapha Belaïssaoui
• Keywords: Algorithm, Artificial Intelligence, Distinctive Feature, Distributed Constraint Optimization, ECAI 2008