Abstract. Learning in the context of constraint solving is a technique by which previously unknown constraints are uncovered during search and used to speed up subsequent search. R...
Ian P. Gent, Christopher Jefferson, Lars Kotthoff,...
Traditional Machine Learning approaches based on single inference mechanisms have reached their limits. This causes the need for a framework that integrates approaches based on aba...
Abstract. Learning from streams is a process in which a group of learners separately obtain information about the target to be learned, but they can communicate with each other in ...
Abstract. Learning Object Metadata (LOM) is an interoperable standard focused on enabling the reuse of learning material for authoring lessons. Nevertheless, few work was done on t...
An open problem in reinforcement learning is discovering hierarchical structure. HEXQ, an algorithm which automatically attempts to decompose and solve a model-free factored MDP h...