Existing online learning experiences lack the social dimension that characterizes learning in the real world. This social dimension extends beyond the traditional classroom into t...
Abstract. This paper deals with the issue of learning in multi-agent systems (MAS). Particularly, we are interested in BDI (Belief, Desire, Intention) agents. Despite the relevance...
Inference is a key component in learning probabilistic models from partially observable data. When learning temporal models, each of the many inference phases requires a complete ...
Collaborative Filtering (CF) requires user-rated training examples for statistical inference about the preferences of new users. Active learning strategies identify the most infor...
Policy Reuse is a reinforcement learning technique that efficiently learns a new policy by using past similar learned policies. The Policy Reuse learner improves its exploration b...