Hidden Markov models play a critical role in the modelling and problem solving of important AI tasks such as speech recognition and natural language processing. However, the stude...
1 In the classic educational context, observing and identifying learner's emotional response allow the teacher to adapt the lesson, with the aim of improving the quality of th...
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,...
Research indicates that impasse-driven learning can have important benefits for improving student mastery of material. When students recognize gaps in their understanding of a con...
The process of coalition formation, where distinct autonomous agents come together to act as a coherent group is an important form of interaction in multiagent systems. Previous w...
In this paper we present an algorithm and software for generating arbitrarily large Bayesian Networks by tiling smaller real-world known networks. The algorithm preserves the stru...
Ioannis Tsamardinos, Alexander R. Statnikov, Laura...
A conditioning graph is a form of recursive factorization which minimizes the memory requirements and simplifies the implementation of inference in Bayesian networks. The time com...
Cognitive modeling has outgrown the toy problems of the research labs and is increasingly tackling Industrial size applications. This growth is not matched in terms of software to...