Abstract
Heuristic search is a fundamental problem solving paradigm in artificial intelligence. We address the problem of developing heuristic search algorithms where intermediate results are sought at intervals of time which may or may not be known apriori. In this paper, we propose an efficient anytime algorithm called Anytime Contract Search (based on the contract search framework) which incrementally explores the state-space with the given contracts (intervals of reporting). The algorithm works without restarting and dynamically adapts for the next iteration based on the current contract and the currently explored state-space. The proposed method is complete on bounded graphs. Experimental results with different contract sequences on the Sliding-tile Puzzle Problem and the Travelling Salesperson Problem (TSP) show that Anytime Contract Search outperforms some of the state-of-the art anytime search algorithms that are oblivious to the given contracts. Also, the non-parametric version of the proposed algorithm which is oblivious of the reporting intervals (making it an anytime algorithm) performs well compared to many available schemes.
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Patra, S., Vadlamudi, S.G., Chakrabarti, P.P. (2013). Anytime Contract Search. In: Bramer, M., Petridis, M. (eds) Research and Development in Intelligent Systems XXX. SGAI 2013. Springer, Cham. https://doi.org/10.1007/978-3-319-02621-3_10
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DOI: https://doi.org/10.1007/978-3-319-02621-3_10
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