A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2006; you can also visit the original URL.
The file type is
Lecture Notes in Computer Science
We introduce ApproxCount, an algorithm that approximates the number of satisfying assignments or models of a formula in propositional logic. Many AI tasks, such as calculating degree of belief and reasoning in Bayesian networks, are computationally equivalent to model counting. It has been shown that model counting in even the most restrictive logics, such as Horn logic, monotone CNF and 2CNF, is intractable in the worst-case. Moreover, even approximate model counting remains a worst-casedoi:10.1007/11499107_24 fatcat:kcx3wvphabbnpmjofo732qlmoe