A New Approach to Iterative Deepening Multiobjective A*

Authors:
J. Coego;L. Mandow;J. L. Pérez De La Cruz
Affiliations:
Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain 29071;Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain 29071;Dpto. Lenguajes y Ciencias de la Computación, Universidad de Málaga, Málaga, Spain 29071
Venue:
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Year:
2009

Citing 6
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Abstract

Multiobjective search is a generalization of the Shortest Path Problem where several (usually conflicting) criteria are optimized simultaneously. The paper presents an extension of the single-objective IDA* search algorithm to the multiobjective case. The new algorithm is illustrated with an example, and formal proofs are presented on its termination, completeness, and admissibility. The algorithm is evaluated over a set of random tree search problems, and is found to be more efficient than IDMOA*, a previous extension of IDA* to the multiobjective case.