Please use this identifier to cite or link to this item: https://doi.org/10.1613/jair.2808
Title: Relaxed survey propagation for the weighted maximum satisfiability problem
Authors: Chieu, H.L.
Lee, W.S. 
Issue Date: 2009
Source: Chieu, H.L.,Lee, W.S. (2009). Relaxed survey propagation for the weighted maximum satisfiability problem. Journal of Artificial Intelligence Research 36 : 229-266. ScholarBank@NUS Repository. https://doi.org/10.1613/jair.2808
Abstract: The survey propagation (SP) algorithm has been shown to work well on large instances of the random 3-SAT problem near its phase transition. It was shown that SP estimates marginals over covers that represent clusters of solutions. The SP-y algorithm generalizes SP to work on the maximum satisfiability (Max-SAT) problem, but the cover interpretation of SP does not generalize to SP-y. In this paper, we formulate the relaxed survey propagation (RSP) algorithm, which extends the SP algorithm to apply to the weighted Max-SAT problem. We show that RSP has an interpretation of estimating marginals over covers violating a set of clauses with minimal weight. This naturally generalizes the cover interpretation of SP. Empirically, we show that RSP outperforms SP-y and other state-of-the-art Max-SAT solvers on random Max-SAT instances. RSP also outperforms state-of-the-art weighted Max-SAT solvers on random weighted Max-SAT instances. © 2009 AI Access Foundation.
Source Title: Journal of Artificial Intelligence Research
URI: http://scholarbank.nus.edu.sg/handle/10635/39039
ISSN: 10769757
DOI: 10.1613/jair.2808
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