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2003
Springer

A Graph Based Backtracking Algorithm for Solving General CSPs

10 years 3 months ago
A Graph Based Backtracking Algorithm for Solving General CSPs
Many AI tasks can be formalized as constraint satisfaction problems (CSPs), which involve finding values for variables subject to constraints. While solving a CSP is an NP-complete task in general, tractable classes of CSPs have been identified based on the structure of the underlying constraint graphs. Much effort has been spent on exploiting structural properties of the constraint graph to improve the efficiency of finding a solution. These efforts contributed to development of a class of CSP solving algorithms called decomposition algorithms. The strength of CSP decomposition is that its worst-case complexity depends on the structural properties of the constraint graph and is usually better than the worst-case complexity of search methods. Its practical application is limited, however, since it cannot be applied if the CSP is not decomposable. In this paper, we propose a graph based backtracking algorithm called ω-CDBT, which shares merits and overcomes the weaknesses of both ...
Wanlin Pang, Scott D. Goodwin
Added 06 Jul 2010
Updated 06 Jul 2010
Type Conference
Year 2003
Where AI
Authors Wanlin Pang, Scott D. Goodwin
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