Because uncertain reasoning is often intractable, it is hard to reason with a large amount of knowledge. One solution to this problem is to specify a set of possible models, some s...
Charles A. Sutton, Brendan Burns, Clayton T. Morri...
Reinforcement techniques have been successfully used to maximise the expected cumulative reward of statistical dialogue systems. Typically, reinforcement learning is used to estim...
In this paper we extend a methodology for constructing a frame of discernment from belief functions for one problem, into a methodology for constructing multiple frames of discernm...
Horn-to-Horn belief revision asks for the revision of a Horn knowledge base such that the revised knowledge base is also Horn. Horn knowledge bases are important whenever one is c...
In recent years there has been a flurry of works on learning probabilistic belief networks. Current state of the art methods have been shown to be successful for two learning scen...