Probabilistic models have been adopted for many computer vision applications, however inference in highdimensional spaces remains problematic. As the statespace of a model grows, ...
A parallel distributed computational model for reasoning and learning is discussed based on a belief network paradigm. Issues like reasoning and learning for the proposed model ar...
The capability of revising its beliefs upon new information in a rational and efficient way is crucial for an intelligent agent. The classical work in belief revision focuses on i...
Existing approaches to knowledge representation and reasoning in the context of open systems either deal with "objective" knowledge or with beliefs. In contrast, there ha...
Action formalisms like the fluent calculus have been developed to endow logic-based agents with the abilities to reason about the effects of actions, to execute high-level strateg...