We develop a framework based on Bayesian model averaging to explain how animals cope with uncertainty about contingencies in classical conditioning experiments. Traditional accoun...
Aaron C. Courville, Nathaniel D. Daw, Geoffrey J. ...
This paper presents a motivational system for an autonomous robot which is designed to regulate human-robot interaction. The mode of social interaction is that of a caretaker-infa...
This paper proposes an emotion model for life-like agents with emotions and motivations. This model consists of reactive and deliberative mechanisms. The former generates low-leve...
Sampling has become an important strategy for inference in belief networks. It can also be applied to the problem of selecting actions in influence diagrams. In this paper, we pre...
We describe a method for the fully automatic learning of hierarchical finite state translation models. The input to the method is transcribed speech utterances and their correspon...