Algorithms and complexity results for #SAT and Bayesian inference

F. Bacchus, S. Dalmao, T. Pitassi
44th Annual IEEE Symposium on Foundations of Computer Science, 2003. Proceedings.  
Bayesian inference is an important problem with numerous applications in probabilistic reasoning. Counting satisfying assignments is a closely related problem of fundamental theoretical importance. In this paper, we show that plain old DPLL equipped with memoization (an algorithm we call #DPLLCache) can solve both of these problems with time complexity that is at least as good as state-of-the-art exact algorithms, and that it can also achieve the best known time-space tradeoff. We then proceed
more » ... f. We then proceed to show that there are instances where #DPLLCache can achieve an exponential speedup over existing algorithms.
doi:10.1109/sfcs.2003.1238208 dblp:conf/focs/BacchusDP03 fatcat:3k44cr7nprbrdk2cpuf66j72em