We develop a probabilistic criterion for belief expansion that is sensitive to the degree of contextual fit of the new information to our belief set as well as to the reliability...
This paper introduces a new approach to adjust a class of neurofuzzy networks based on the idea of participatory learning. Participatory learning is a mean to learn and revise bel...
Michel Hell, Rosangela Ballini, Pyramo Costa Jr., ...
Probabilistic logic programming is a powerful technique to represent and reason with imprecise probabilistic knowledge. A probabilistic logic program (PLP) is a knowledge base whi...
We present a framework for incorporating perception-induced beliefs into the knowledge base of a rational agent. Normally, the agent accepts the propositional content of perception...
We describe a discrete time probabilitylogic for use as the representation language of a temporal knowledge base. In addition to the usual expressive power of a discrete temporal ...
Scott D. Goodwin, Howard J. Hamilton, Eric Neufeld...