Probabilistic Model for Uncertain Problem Solving.

摘要

With growing interest in the application of research to problems that arise in real-world contexts, issues raised by consideration of uncertain states and unreliable operators are receiving increased attention in artificial intelligence research. In this paper, a model is presented for dealing with such concerns. The model is a probabilistic generalization of the familiar notion of 'problem space.' The author discusses the specification of uncertain states and unreliable operators, problem-solving search methods, and the need for information-gathering operators to control state disunity and provide pragmatic focusing. Search methods are generalized to produce tree-structured plans incorporating the use of such operators. Several application domains for the model also are discussed.