There is a genuine demand for personalization and guidance in learning systems, as well as in general commercial learning systems for the WWW, and further, for the new, emerging S...
Alexandra I. Cristea, Angelo Wentzler, Egbert Heuv...
Abstract. The student modeling (SM) is a core component in the development of Intelligent Learning Environments (ILEs). In this paper we describe how a Multi-agent Intelligent Lear...
Reinforcement learning can provide a robust and natural means for agents to learn how to coordinate their action choices in multiagent systems. We examine some of the factors that...
We apply a constrained Hidden Markov Model architecture to the problem of simultaneous localization and surveying from sensor logs of mobile agents navigating in unknown environmen...
An original Reinforcement Learning (RL) methodology is proposed for the design of multi-agent systems. In the realistic setting of situated agents with local perception, the task o...