Title :
Improving nogood recording using 2SAT
Author :
Stuckey, Peter J. ; Zheng, Lei
Author_Institution :
Dept. of Comput. Sci. & Software Eng., Melbourne Univ., Vic., Australia
Abstract :
Nogood recording is a dynamic learning technique widely applied to solve CSP (constraint satisfaction problems). It is highly effective in reducing the search space for SAT (satisfiability) problems. While SAT is NP-complete, the problem restricted to binary clauses (2SAT) is solvable in linear time. We can improve SAT solving by incorporating 2SAT solving techniques. In this paper we investigate extending nogood recording to make use of binary clause resolution. Our experiments show that nogoods generated from binary resolution can significantly reduce the search space, and size of nogoods generated, as well as the search time.
Keywords :
backtracking; computability; computational complexity; constraint theory; learning (artificial intelligence); problem solving; 2SAT; CSP; NP-complete; SAT; binary clause resolution; binary clauses; binary resolution; constraint satisfaction problems; dynamic learning; linear time; nogood recording; satisfiability problems; search space; search time; systems analysis tool; Artificial intelligence; Australia; Computer science; Information analysis; Reactive power; Software engineering; Space exploration;
Conference_Titel :
Tools with Artificial Intelligence, 2003. Proceedings. 15th IEEE International Conference on
Print_ISBN :
0-7695-2038-3
DOI :
10.1109/TAI.2003.1250175