ELABORATION TOLERANCE

John McCarthy

Computer Science Department

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Stanford University

Abstract:

A formalism is elaboration tolerant to the extent that it is convenient to modify a set of facts expressed in the formalism to take into account new phenomena or changed circumstances. Representations of information in natural language have good elaboration tolerance when used with human background knowledge. Human-level AI will require representations with much more elaboration tolerance than those used by present AI programs, because human-level AI needs to be able to take new phenomena into account.

The simplest kind of elaboration is the addition of new formulas. We'll call these additive elaborations. Next comes changing the values of parameters. Adding new arguments to functions and predicates represents more of a change. However, elaborations not expressible as additions to the object language representation may be treatable as additions at a meta-level expression of the facts.

Elaboration tolerance requires nonmonotonic reasoning. The elaborations that are tolerated depend on what aspects of the phenomenon are treated nonmonotonically. Representing contexts as objects in a logical formalism that can express relations among contexts should also help.

We use the missionaries and cannibals problem and about 20 variants as our Drosophila in studying elaboration tolerance in logical AI.

The present version has only some parts of a situation calculus formalization. However, the English language elaborations listed are enough to serve as a challenge to logical AI formalisms claiming elaboration tolerance.