This paper introduces the execution model of a declarative programming language intended for agent applications. Features supported by the language include functional and logic pro...
In recent years there have been efforts to develop a probabilistic framework to explain the workings of a Learning Classifier System. This direction of research has met with lim...
We present a novel representation of cyclic human locomotion based on a set of spatio-temporal curves of tracked points on the surface of a person. We start by extracting a set of...
We propose a new semantics for modeling belief, mixing conncepts from qualitative probabilistic and classical possible world accounts. Our belief structures are coherent sets of q...
This paper presents an unsupervised learning algorithm that can derive the probabilistic dependence structure of parts of an object (a moving human body in our examples) automatic...