When a joint distribution P F is given to a set F of facts in a logic program DB = F [R where R is a set of rules, we can further extend it to a joint distribution P DB over the set of possible leastâ€¦ (More)

We propose a logical/mathematical framework for statistical parameter learning of parameterized logic programs, i.e. de nite clause programs containing probabilistic facts with a parameterizedâ€¦ (More)

We present an overview of symbolic-statistical modeling language PRISM whose programs are not only a probabil istic extension of logic programs but also able to learn f rom examples w i th the helpâ€¦ (More)

Since the proposal of logic programming by Horn clauses [5] and Prolog [7] has been gaining popularity because of the unified treatment of declarative semantics and procedural semantics. It has beenâ€¦ (More)

This paper introduces a Minimum Description Length (MDL) principle to de ne tness functions in Genetic Programming (GP). In traditional (Koza-style) GP, the size of trees was usually controlled byâ€¦ (More)

We propose statistical abduction as a rstorder logical framework for representing and learning probabilistic knowledge. It combines logical abduction with a parameterized distribution overâ€¦ (More)

We review a logic-based modeling language PRISM and report recent developments including belief propagation by the generalized inside-outside algorithm and generative modeling with constraints. Theâ€¦ (More)

Recently there has been a growing interest of research in tabling in the logic programming community because of its usefulness in a variety of application domains including program analysis, parsing,â€¦ (More)