We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
Most existing approaches for learning action models work by extracting suitable low-level features and then training appropriate classifiers. Such approaches require large amount...
The modelling of affective behaviour and appropriate bodily expression to make synthetic characters more believable becomes important in many types of applications such as games, s...
— We introduce the Oracular Partially Observable Markov Decision Process (OPOMDP), a type of POMDP in which the world produces no observations; instead there is an “oracle,” ...
Abstract. Solutions to the symbol grounding problem, in psychologically plausible cognitive models, have been based on hybrid connectionist/symbolic architectures, on robotic appro...