This paper describes some of the interactions of model learning algorithms and planning algorithms we have found in exploring model-based reinforcement learning. The paper focuses...
In recent years, there has been a growing interest in using rich representations such as relational languages for reinforcement learning. However, while expressive languages have ...
Tom Croonenborghs, Jan Ramon, Hendrik Blockeel, Ma...
From some perspectives Automated Collaborative Filtering (ACF) appears quite similar to Case-Based Reasoning (CBR). It works on data organised around users and assets that might be...
Agent technology provides many services to users. The tasks in which agents are involved include information filtering, information retrieval, user's tasks automation, browsin...
In the same way as the “static” Semantic Web deals with data model and language heterogeneity and semantics that lead to RDF and OWL, there is language heterogeneity and the ne...