Modeling synthetic characters which interact with objects in dynamic virtual worlds is important when we want the agents to act in an autonomous and non-preplanned way. Such inter...
In this paper, we introduce a generic framework for semi-supervised kernel learning. Given pairwise (dis-)similarity constraints, we learn a kernel matrix over the data that respe...
Argument diagramming tools can improve reasoning and learning. They are likely to have a significant place in future virtual learning environments whose design will be dominated b...
- This work investigates bandwidth learning algorithms in a version of a distributed heterogeneous data dissemination system called the Agile Information Control Environment (AICE)...
Recent decision-theoric planning algorithms are able to find optimal solutions in large problems, using Factored Markov Decision Processes (fmdps). However, these algorithms need ...
Thomas Degris, Olivier Sigaud, Pierre-Henri Wuille...