@inproceedings{ee89aa8c241745929b58ac5074fc0022,
title = "Multiagent SAT (MASSAT): Autonomous pattern search in constrained domains",
abstract = "In this paper, we present an autonomous pattern search approach to solving Satisfiability Problems (SATs). Our approach is essentially a multi agent system. To solve a SAT problem, we first divide variables into groups, and represent each variable group with an agent. Then, we randomly place each agent onto a position in the correspoding local space which is composed of the domains of the variables that are represented by this agent. Thereafter, all agents will autonomously make search decisions guided by some reactive rules in their local spaces until a special pattern (i.e., solution) is found or a time step threshold is reached. Experimental results on some benchmark SAT test-sets have shown that by employing the MASSAT approach, we can obtain performances comparable to those of other popular algorithms.",
keywords = "Autonomous Pattern Search, MASSAT, Multiagent System, Satisfiability Problem (SAT)",
author = "Xiaolong Jin and Jiming LIU",
note = "Publisher Copyright: {\textcopyright} Springer-Verlag Berlin Heidelberg 2002. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 3rd International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2002 ; Conference date: 12-08-2002 Through 14-08-2002",
year = "2002",
doi = "10.1007/3-540-45675-9_49",
language = "English",
isbn = "9783540440253",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "318--328",
editor = "Hujun Yin and Nigel Allinson and Richard Freeman and John Keane and Simon Hubbard",
booktitle = "Intelligent Data Engineering and Automated Learning - IDEAL 2002 - 3rd International Conference, Proceedings",
address = "Germany",
}