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

Raquel Fuentetaja; Michael W Barley; Daniel Borrajo; Jordan Douglas; Santiago Franco Aixela; Patricia J Riddle

doi:10.1609/aaai.v32i1.12091

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

Raquel Fuentetaja, Michael W Barley, Daniel Borrajo, Jordan Douglas, Santiago Franco Aixela, Patricia J Riddle

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

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.

Original language	English
Title of host publication	Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence
Publisher	AAAI press
Pages	6169-6176
Number of pages	8
ISBN (Print)	9781577358008, 9781577358107, 9781577358114, 9781577358121, 9781577358138, 9781577358145, 9781577357858, 9781577358169
DOIs	https://doi.org/10.1609/aaai.v32i1.12091
Publication status	Published - 26 Apr 2018
Event	32nd Association for the Advancement of Artificial Intelligence Conference - Hilton New Orleans Riverside, New Orleans, United States Duration: 2 Feb 2018 → 7 Feb 2018 Conference number: 32 https://aaai.org/Conferences/AAAI-18/ (Link to Conference Details)

Publication series

Name	AAAI Conference on Artificial Intelligence
Publisher	AAAI
Number	1
Volume	32
ISSN (Print)	2159-5399
ISSN (Electronic)	2374-3468

Conference

Conference	32nd Association for the Advancement of Artificial Intelligence Conference
Abbreviated title	AAAI-18
Country/Territory	United States
City	New Orleans
Period	2/02/18 → 7/02/18
Internet address	https://aaai.org/Conferences/AAAI-18/ (Link to Conference Details)

Access to Document

10.1609/aaai.v32i1.12091Licence: Unspecified

Cite this

Fuentetaja, R., Barley, M. W., Borrajo, D., Douglas, J., Franco Aixela, S., & Riddle, P. J. (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 (pp. 6169-6176). (AAAI Conference on Artificial Intelligence; Vol. 32, No. 1). AAAI press. https://doi.org/10.1609/aaai.v32i1.12091

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title = "Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis",

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 selectinga combination to use for all problems within a domain and is competitive with state of the art optimal planners.",

keywords = "Planning, meta-reasoning, Search algorithms, reformulation, heuristic selection, representation selection, Predictive modelling",

author = "Raquel Fuentetaja and Barley, {Michael W} and Daniel Borrajo and Jordan Douglas and {Franco Aixela}, Santiago and Riddle, {Patricia J}",

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Fuentetaja, R, Barley, MW, Borrajo, D, Douglas, J, Franco Aixela, S & Riddle, PJ 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 Conference on Artificial Intelligence, no. 1, vol. 32, AAAI press, pp. 6169-6176, 32nd Association for the Advancement of Artificial Intelligence Conference , New Orleans, Louisiana, United States, 2/02/18. https://doi.org/10.1609/aaai.v32i1.12091

Meta-Search Through the Space of Representations and Heuristics on a Problem by Problem Basis. / Fuentetaja, Raquel; Barley, Michael W; Borrajo, Daniel et al.

Proceedings of the Thirty-Second AAAI Conference on Artificial Intelligence. AAAI press, 2018. p. 6169-6176 (AAAI Conference on Artificial Intelligence; Vol. 32, No. 1).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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