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Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis

Franco, Santiago (2018) Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis. In: Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI Press, pp. 6169-6176.

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Abstract

Two key aspects of problem solving are representation and search heuristics. Both theoretical and experimental studies have shown that there is no one best problem representation nor one best search heuristic. Therefore, some recent methods, e.g., portfolios, learn a good combination of problem solvers to be used in a given domain or set of domains. There are even dynamic portfolios that select a particular combination of problem solvers specific to a problem. These approaches: (1) need to perform a learning step; (2) do not usually focus on changing the representation of the input domain/problem; and (3) frequently do not adapt the portfolio to the specific problem. This paper describes a meta-reasoning system that searches through the space of combinations of representations and heuristics to find one suitable for optimally solving the specific problem. We show that this approach can be better than selecting a combination to use for all problems within a domain and is competitive with state of the art optimal planners.

Item Type: Book Chapter
Subjects: Q Science > Q Science (General)
T Technology > T Technology (General)
Schools: School of Computing and Engineering
Related URLs:
Depositing User: Sharon Beastall
Date Deposited: 19 Dec 2017 08:57
Last Modified: 15 Aug 2018 13:30
URI: http://eprints.hud.ac.uk/id/eprint/34102

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