We present an overview of the Virtual Patient project at the University of Maryland, which is developing a cognitive model of humans experiencing various states of health and dise...
Sergei Nirenburg, Marjorie McShane, Stephen Beale,...
Personalized support for learners becomes even more important, when e-Learning takes place in open and dynamic learning and information networks. This paper shows how to realize p...
Peter Dolog, Nicola Henze, Wolfgang Nejdl, Michael...
Multiagent learning can be seen as applying ML techniques to the core issues of multiagent systems, like communication, coordination, and competition. In this paper, we address the...
We report on our on-going effort to build an adaptive driver support system, Driver AdvocateTM , merging various AI techniques, in particular, agents, ontology, production systems...
Chung Hee Hwang, Noel Massey, Bradford W. Miller, ...
Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....