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Dynamic agent prioritisation with penalties in distributed local search.

Sambo-Magaji, Amina; Arana, Inés; Ahriz, Hatem

Authors

Amina Sambo-Magaji

Inés Arana

Hatem Ahriz



Contributors

Joaquim Filipe
Editor

Ana Fred
Editor

Abstract

Distributed Constraint Satisfaction Problems (DisCSPs) solving techniques solve problems which are distributed over a number of agents.The distribution of the problem is required due to privacy, security or cost issues and, therefore centralised problem solving is inappropriate. Distributed local search is a framework that solves large combinatorial and optimization problems. For large problems it is often faster than distributed systematic search methods. However, local search techniques are unable to detect unsolvability and have the propensity of getting stuck at local optima. Several strategies such as weights on constraints, penalties on values and probability have been used to escape local optima. In this paper, we present an approach for escaping local optima called Dynamic Agent Prioritisation and Penalties (DynAPP) which combines penalties on variable values and dynamic variable prioritisation for the resolution of distributed constraint satisfaction problems. Empirical evaluation with instances of random, meeting scheduling and graph colouring problems have shown that this approach solved more problems in less time at the phase transition when compared with some state of the art algorithms. Further evaluation of the DynAPP approach on iteration-bounded optimisation problems showed that DynAPP is competitive.

Start Date Feb 15, 2013
Publication Date Dec 31, 2013
Publisher Science and Technology Publications
Pages 276-281
ISBN 9789898565389
Institution Citation SAMBO-MAGAJI, A., ARANA, I. and AHRIZ, H. 2013. Dynamic agent prioritisation with penalties in distributed local search. In Filipe, J. and Fred, A. (eds.) Proceedings of the 5th International conference on agents and artificial intelligence (ICAART 2013), 15-18 February 2013, Barcelona, Spain. Setúbal: Science and Technology Publications [online], volume 1, pages 276-281. Available from: https://doi.org/10.5220/0004259202760281
DOI https://doi.org/10.5220/0004259202760281
Keywords Distributed problems solving; Local search; Distributed constraint satisfaction; Heuristics

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