Bayes Networks for Estimating the Number of Solutions to a CSP

The problem of counting the number of solutions to a constraint satisfaction problem (CSP) is rephrased in terms of probability updating in Bayes networks. Approximating the probabilities in Bayes networks is a problem which has been studied for a while, and may well provide a good approximation to counting the number of solutions. We use a simple approximation based on independence, and show that it is correct for tree-structured CSPs. For other CSPs, it is a less optimistic approximation than those suggested in prior work, and experiments show that it is more accurate on the average. We present empirical evidence that our approximation is a useful search heuristic for finding a single solution to a CSP.

[1]  Edward P. K. Tsang,et al.  Foundations of constraint satisfaction , 1993, Computation in cognitive science.

[2]  Robert M. Haralick,et al.  Increasing Tree Search Efficiency for Constraint Satisfaction Problems , 1979, Artif. Intell..

[3]  Barbara M. Smith,et al.  The Phase Transition and the Mushy Region in Constraint Satisfaction Problems , 1994, ECAI.

[4]  Judea Pearl,et al.  Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.

[5]  Gregory M. Provan,et al.  An Experimental Comparison of Numerical and Qualitative Probabilistic Reasoning , 1994, UAI.

[6]  Rina Dechter,et al.  Network-Based Heuristics for Constraint-Satisfaction Problems , 1987, Artif. Intell..

[7]  Peter C. Cheeseman,et al.  Where the Really Hard Problems Are , 1991, IJCAI.

[8]  Gregory F. Cooper,et al.  The Computational Complexity of Probabilistic Inference Using Bayesian Belief Networks , 1990, Artif. Intell..

[9]  R. Martin Chavez,et al.  Approximating Probabilistic Inference in Bayesian Belief Networks , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  D. Knuth Estimating the efficiency of backtrack programs. , 1974 .

[11]  Eugene Charniak,et al.  A New Admissible Heuristic for Minimal-Cost Proofs , 1991, AAAI.

[12]  Eugene Santos,et al.  Sample-and-Accumulate Algorithms for Belief Updating in Bayes Networks , 1996, UAI.

[13]  Amnon Meisels,et al.  CSPs with counters: a likelihood-based heuristic , 1998, J. Exp. Theor. Artif. Intell..

[14]  Michael Luby,et al.  Approximating Probabilistic Inference in Bayesian Belief Networks is NP-Hard , 1993, Artif. Intell..