A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
In this paper we present a cooperative negotiation protocol that solves a distributed resource allocation problem while conforming to soft real-time constraints in a dynamic envir...
Current recommender systems, based on collaborative filtering, implement a rather limited model of interaction. These systems intelligently elicit information from a user only dur...
Affective reasoning holds great potential for interactive digital entertainment, education, and training. Incorporating affective reasoning into the decision-making capabilities o...
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Evidence suggests that credal ...