To learn to behave in highly complex domains, agents must represent and learn compact models of the world dynamics. In this paper, we present an algorithm for learning probabilist...
Hanna Pasula, Luke S. Zettlemoyer, Leslie Pack Kae...
Abstract. We present an approach to agents that can reason, react to the environment and are able to update their own knowledge as a result of new incoming information. Each agents...
We develop a logic for representing and reasoning about coalitional games without transferable payoffs. Although a number of logics of cooperation have been proposed over the past...
We suggest a new representation of defeasible entailment and specificity in the framework of default logic. The representation is based on augmenting the underlying classical lan...
Weintroducea formalcontext mechanism,embeddedinto a descriptionlogicsframework,whichis ableto uniformly represent and managedifferent formsof ambiguitiesas theyoccurin the courseo...