KNOWLEDGE COMPILATION AND THEORY APPROXIMATION

Computational efficiency is a central concern in the design of knowled ge representation systems. In order to obtain efficient systems, it ha s been suggested that one should limit the form of the statements in t he knowledge base or use an incomplete inference mechanism. The former approach is often too restrictive for practical applications, whereas the latter leads to uncertainty about exactly what can and cannot be inferred from the knowledge base. We present a third alternative, in w hich knowledge given in a general representation language is translate d (compiled) into a tractable form-allowing for efficient subsequent q uery answering. We show how propositional logical theories can be comp iled into Horn theories that approximate the original information. The approximations bound the original theory from below and above in term s of logical strength. The procedures are extended to other tractable languages (for example, binary clauses) and to the first-order case. F inally, we demonstrate the generality of our approach by compiling con cept descriptions in a general frame-based language into a tractable f orm.