Partial Compilation of Strategic Knowledge

Abstract

Many system building efforts in artificial intelligence intentionally begin with expressively rich and flex-ible declarative structures for the control of prob-lem solving-especially when the best problem solv-ing strategies are not known. However, as experience with a system increases, it sometimes becomes desir-able to compile declarative knowledge into procedures for purposes of efficiency. We present a paradigm for compilation which begins with declarative oppor-tunism, moves to a phase of heuristic implementation of a partial plan and finally evolves into a fully elab-orated procedure. We use the PROTEAN geometric constraint satisfaction system as an example. Using results from a purely declarative structure, we were