2026-09-18T21:12:08Zhttps://dspace.mit.edu/server/oai/request

oai:dspace.mit.edu:1721.1/292422022-01-13T07:54:29Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023

Brian C. Williams. Ragno, Robert J. (Robert John), 1977- Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2005-10-14T19:23:46Z 2005-10-14T19:23:46Z 2002 2002 http://hdl.handle.net/1721.1/29242 51589373 Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002. Includes bibliographical references (p. 37-38). Real-world applications, such as diagnosis and embedded control, are increasingly being framed as OpSAT problems - problems of finding the best solution that satisfies a formula in propositional state logic. Previous methods, such as Conflict-directed A*, solve OpSAT problems through a weak coupling of A* search, used to generate optimal candidates, and a DPLL-based SAT solver, used to test feasibility. This paper achieves a substantial performance improvement by introducing a tightly coupled approach, Clause-directed A * (CIA *). ClA* simultaneously directs the search towards assignments that are feasible and optimal. First, satisfiability is generalized to state logic by unifying the DPLL satisfiability procedure with forward checking. Second, optimal assignments are found by using A* to guide variable splitting within DPLL. Third, search is directed towards feasible regions of the state space by treating all clauses as conflicts, and by selecting only assignments that entail more clauses. Finally, ClA* climbs towards the optimum by using a variable ordering heuristic that emulates gradient search. Empirical experiments on real-world and randomly-generated instances demonstrate an order of magnitude increase in performance over Conflict-directed A*. by Robert J. Ragno. M.Eng. 38 p. 1072047 bytes 1071855 bytes application/pdf application/pdf eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Solving optimal satisfiability problems through clause-directed A* Solving optimal satisfiability problems through ClA* Thesis application/pdf false Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="f6f7f971-3e3a-4ee2-a335-5dabbf8be4a4"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Solving optimal satisfiability problems through clause-directed A*</Title> <Subtitle>Solving optimal satisfiability problems through ClA*</Subtitle> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2002</PublicationDate> <Authors> <Author> <DisplayName>Ragno, Robert J. (Robert John), 1977-</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>Real-world applications, such as diagnosis and embedded control, are increasingly being framed as OpSAT problems - problems of finding the best solution that satisfies a formula in propositional state logic. Previous methods, such as Conflict-directed A*, solve OpSAT problems through a weak coupling of A* search, used to generate optimal candidates, and a DPLL-based SAT solver, used to test feasibility. This paper achieves a substantial performance improvement by introducing a tightly coupled approach, Clause-directed A * (CIA *). ClA* simultaneously directs the search towards assignments that are feasible and optimal. First, satisfiability is generalized to state logic by unifying the DPLL satisfiability procedure with forward checking. Second, optimal assignments are found by using A* to guide variable splitting within DPLL. Third, search is directed towards feasible regions of the state space by treating all clauses as conflicts, and by selecting only assignments that entail more clauses. Finally, ClA* climbs towards the optimum by using a variable ordering heuristic that emulates gradient search. Empirical experiments on real-world and randomly-generated instances demonstrate an order of magnitude increase in performance over Conflict-directed A*.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>