In this paper, we define a continuum of modeling styles, ranging from collections of very simple agents on one end to collections of very complex agents at the other end, and a s...
Learning reusable sequences can support the development of expertise in many domains, either by improving decisionmaking quality or decreasing execution speed. This paper introduc...
In this paper, we focus on the problem of learning reactive skills for use by physical agents. We propose a new representation for such procedures, teleoreactive logic programs, al...
Abstract. We investigate the generalization behavior of sequential prediction (online) algorithms, when data are generated from a probability distribution. Using some newly develop...
We describe a framework that can be used to model and predict the behavior of MASs with learning agents. It uses a difference equation for calculating the progression of an agent&...