Decision theory and artificial intelligence: I. A semantics-based region analyzer

摘要

Mathematical decision theory can be combined with heuristic techniques to attack Artificial Intelligence problems. As a first example, the problem of breaking an image into meaningful regions is considered. Bayesian decision theory is seen to provide a mechanism for including problem dependent (semantic) information in a general system. Some results are presented which make the computation feasible. A programming system based on these ideas and its application to road scenes is described.