@inproceedings{361f1d9bfff9448d8768fc99f977b377,
title = "Probably approximately correct heuristic search",
abstract = "A* is a best-first search algorithm that returns an optimal solution. w-admissible algorithms guarantee that the returned solution is no larger than w times the optimal solution. In this paper we introduce a generalization of the w-admissibility concept that we call PAC search, which is inspired by the PAC learning framework in Machine Learning. The task of a PAC search algorithm is to find a solution that is w-admissible with high probability. In this paper we formally define PAC search, and present a framework for PAC search algorithms that can work on top of any search algorithm that produces a sequence of solutions. Experimental results on the 15-puzzle demonstrate that our framework activated on top of Anytime Weighted A* (AWA*) expands significantly less nodes than regular AWA* while returning solutions that have almost the same quality.",
author = "Roni Stern and Ariel Felner and Robert Holte",
year = "2011",
month = jan,
day = "1",
doi = "10.1609/socs.v2i1.18207",
language = "English",
isbn = "9781577355373",
series = "Proceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011",
publisher = "AAAI press",
pages = "158--163",
booktitle = "Proceedings of the 4th Annual Symposium on Combinatorial Search, SoCS 2011",
note = "4th International Symposium on Combinatorial Search, SoCS 2011 ; Conference date: 15-07-2011 Through 16-07-2011",
}