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Open Access Publications from the University of California

Steps Toward Automatic Theory Formation

  • Author(s): Brown, John Seely
  • et al.

This paper describes a theory formation system which can discover a partial axiomization of a data base represented as extensionally defined binary relations. The system first discovers all possible intensional definitions of each binary relation in terms of the others. It then determines a minimal set of these relations from which the others can be defined. It then attempts to discover all the ways the relations of this minimal set can interact with each other, thus generating a set of inference rules. Although the system was originally designed to explore automatic techniques for theory construction for question-answering systems, it is currently being expanded to function as a symbiotic system to help social scientists explore certain kinds of data bases.

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