@inproceedings{bf4204ee32d442e0b6fc95716f46be08,
title = "Partial weighted MaxSAT for optimal planning",
abstract = "We consider the problem of computing optimal plans for propositional planning problems with action costs. In the spirit of leveraging advances in general-purpose automated reasoning for that setting, we develop an approach that operates by solving a sequence of partial weighted MaxSAT problems, each of which corresponds to a step-bounded variant of the problem at hand. Our approach is the first SAT-based system in which a proof of cost-optimality is obtained using a MaxSAT procedure. It is also the first system of this kind to incorporate an admissible planning heuristic. We perform a detailed empirical evaluation of our work using benchmarks from a number of International Planning Competitions.",
author = "Nathan Robinson and Charles Gretton and Pham, {Duc Nghia} and Abdul Sattar",
year = "2010",
doi = "10.1007/978-3-642-15246-7_23",
language = "English",
isbn = "3642152457",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "231--243",
booktitle = "PRICAI 2010",
note = "11th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2010 ; Conference date: 30-08-2010 Through 02-09-2010",
}