The Frame Problem: An AI Fairy Tale

Author: Korb, K.B.

Source: Minds and Machines, Volume 8, Number 3, 1998 , pp. 317-351(35)

Publisher: Springer

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Abstract:

I analyze the frame problem and its relation to other epistemological problems for artificial intelligence, such as the problem of induction, the qualification problem and the "general" AI problem. I dispute the claim that extensions to logic (default logic and circumscriptive logic) will ever offer a viable way out of the problem. In the discussion it will become clear that the original frame problem is really a fairy tale: as originally presented, and as tools for its solution are circumscribed by Pat Hayes, the problem is entertaining, but incapable of resolution. The solution to the frame problem becomes available, and even apparent, when we remove artificial restrictions on its treatment and understand the interrelation between the frame problem and the many other problems for artificial epistemology. I present the solution to the frame problem: an adequate theory and method for the machine induction of causal structure. Whereas this solution is clearly satisfactory in principle, and in practice real progress has been made in recent years in its application, its ultimate implementation is in prospect only for future generations of AI researchers.

Keywords: Bayesian learning; MML; artificial intelligence; causal induction; frame problem; logicism; machine learning

Document Type: Regular Paper

Affiliations: School of Computer Science and Software Engineering, Monash University, Clayton, Victoria 3168, Australia (email: korb@cs.monash.edu.au)

Publication date: January 1, 1998

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