Partial Compilation of Strategic Knowledge

Russ B. Altman, Bruce G. Buchanan

Many system building efforts in artificial intelligence intentionally begin with expressively rich and flexible declarative structures for the control of problem solving-especially when the best problem solving strategies are not known. However, as experience with a system increases, it sometimes becomes desirable to compile declarative knowledge into procedures for purposes of efficiency. We present a paradigm for compilation which begins with declarative opportunism, moves to a phase of heuristic implementation of a partial plan and finally evolves into a fully elaborated procedure. We use the PROTEAN geometric constraint satisfaction system as an example. Using results from a purely declarative structure, we were able to compile strategic knowledge into a procedure for planning a solution. The problem solving behavior of the new system is reported.

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