Proceedings of the Annual Meeting of the Cognitive Science Society

Opportunistic planning requires a talent for noticing plans' conditions of applicability in the world. In a reasonably complex environment, there is a great proliferation of features, and their relations to useful plans are very intricate. Thus, ''noticing" is a very complicated affair. To compound difficulties, the need to efficiently perceive conditions of applicability is simultaneously true for the thousands of possible plans an agent might use. We examine the implications of this problem for memory and planning behavior, and present an architecture developed to address it. Tools from signal detection theory and numerical optimization provide the model with a form of learning.