"Compiling Probabilistic and Logical Knowledge"

12/3/1999: [time not recorded]
[location not recorded]

Abstract: Compiling knowledge has been emerging recently as a new direction of research for dealing with the computational intractability of reasoning. According to this approach, the reasoning process is split into two phases: an off-line compilation phase and an on-line query-answering phase. The main motivation behind knowledge compilation is to push as much of the computational overhead as possible into the off-line phase, in order to amortize that overhead over all on-line queries. Another motivation is to produce very simplistic on-line reasoning systems, which can be embedded cost effectively into primitive computational platforms. In this talk, I will discuss earlier work on compiling probabilistic knowledge in the form of Bayesian networks into parameterized arithmetic expressions. I will also discuss more recent work on compiling propositional theories into a new logical form, known as decomposable negation normal form (DNNF). I will go over applications of the compilation techniques to model-based diagnosis, and then touch upon recent work on its application to satisfiability-based planning.

Last updated: Mon Jun 19 17:44:06 2006