Proceedings of the Annual Meeting of the Cognitive Science Society

A central question about cognition is how, faced with a situation, one explores possible ways of understanding and responding lo it In particular, how do concepts initially considered irrelevant, or not even considered at all, become relevant in response to pressures evoked by the understanding process itself We describe a model of concepts and high-level perception in which concepts consist of a central region surrounded by a dynamic nondeterministic "halo of potential associations, in which relevance and degree of association change as processing proceeds. As the representation of a situation is built, associations arise and are considered in a probabilistic fashion according to a parallel terraced scan, in which many routes toward understanding the situation are tested in parallel, each at a rate and to a depth reflecting ongoing evaluations of its promise. We describe a computer program that implements this model in the context of analogy-making, and illustrate, using screen dumps from a run, how the program's ability to flexibly bring in appropriate concepts for a given situation emerges from the mechanisms we are proposing.