Operationalizing heuristics: some AI methods for assisting AI programming

  • Authors:
  • Jack Mostow;Frederick Hayes-Roth

  • Affiliations:
  • Computer Science Department, Carnegie-Mellon University, Pittsburgh, Pennsylvania;Information Sciences Department, The Rand Corporation, Santa Monica, California

  • Venue:
  • IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 1979

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Abstract

Machine-aided heuristic programming is a paradigm for incorporating domain knowledge In Intelligent task performance programs. In this paradigm, a system interactively assimilates a natural language description of the task advice on how to perform it, and definitions of the domain concepts in terms of which the advice is expressed. This system translates this input into an internal representation, operationalizes the assimilated knowledge to make it effective, integrates different pieces of advice, and applies them to the performance of the task. A typed applicative LISP-like language is used for the internal representation of domain knowledge. Operationally Ion la defined in terms of transforming well-defined but non-effective expressions Into effectively executable ones. Several techniques for performing this process mechanically are presented and applied to an example drawn from the domain of the card game Hearts. A system to operationalize Hearts advice is currently being implemented in an Instantiation of the advocated paradigm.