Best First Search Algorithm for Logic Programs with Uncertainties

Abstract

It is very important for many rule-based systems to specify certainties of rules and to compute certainties of inferred conclusions. One of the promising logical frameworks for it is logic programs with uncertainties (LPU). This paper proposes a best first search (BFS) algorithm for LPU. It allows us to make useful interpreter for LPU that can give, to a given query, the current best solution in the remaining solutions (or tell us the failure of finding it) each time we ask the interpreter for another solution. Important is that each solution is found with the minimal computation required at each time. Using BFS algorithm we implemented an extended Prolog which has the BFS interpreter avoiding the infinite computations and dealing with the negation as failure similar to standard Prolog.