An Application of Causality for Representing and Providing Formal Explanations about the Behavior of the Threshold Accepting Algorithm

  • Authors:

  • Joaquín Pérez;Laura Cruz;Rodolfo Pazos;Vanesa Landero;Gerardo Reyes;Héctor Fraire;Juan Frausto

  • Affiliations:

  • Departamento de Ciencias Computacionales AP 5-164, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca, México 62490;División de Estudios de Posgrado e Investigación, Instituto Tecnológico de Ciudad Madero (ITCM), Cd. Madero, México;Departamento de Ciencias Computacionales AP 5-164, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca, México 62490;Departamento de Ciencias Computacionales AP 5-164, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca, México 62490;Departamento de Ciencias Computacionales AP 5-164, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca, México 62490;Departamento de Ciencias Computacionales AP 5-164, Centro Nacional de Investigación y Desarrollo Tecnológico (CENIDET), Cuernavaca, México 62490;Departamento de Ciencias Computacionales, Instituto Tecnológico de Estudios Superiores de Monterrey (ITESM), Cuernavaca, México 62589

  • Venue:
  • ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
  • Year:
  • 2006

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Abstract

The problem of algorithm selection for solving NP problems arises with the appearance of a variety of heuristic algorithms. The first works claimed the supremacy of some algorithm for a given problem. Subsequent works revealed the supremacy of algorithms only applied to a subset of instances. However, it was not explained why an algorithm solved better a subset of instances. In this respect, this work approaches the problem of explaining through causal model the interrelations between instances characteristics and the inner workings of algorithms. For validating the results of the proposed approach, a set of experiments was carried out in a study case of the Threshold Accepting algorithm to solve the Bin Packing problem. Finally, the proposed approach can be useful for redesigning the logic of heuristic algorithms and for justifying the use of an algorithm to solve an instance subset. This information could contribute to algorithm selection for NP problems.