Behavioral research suggests that human learning in some multi-agent systems can be predicted with surprisingly simple “foresight-free” models. The current note discusses the ...
We describe an adaptation and application of a search-based structured prediction algorithm "Searn" to unsupervised learning problems. We show that it is possible to red...
In this paper, we present our research results about a UML-based modeling language dedicated to Problem-Based Learning design. The CPM (Cooperative Problem-Based learning Metamode...
The paper describes an ontology-based framework for bridging learning design and learning object content. In present solutions, researchers have proposed conceptual models and dev...
Several algorithms for learning near-optimal policies in Markov Decision Processes have been analyzed and proven efficient. Empirical results have suggested that Model-based Inter...