In this paper, we pose a novel research problem for machine learning that involves constructing a process model from continuous data. We claim that casting learned knowledge in ter...
Will Bridewell, Pat Langley, Ljupco Todorovski, Sa...
Abstract. In this paper, we propose an approach to attach semantic annotations to textual cases for their representation. To achieve this goal, a framework that combines machine le...
The training experiences needed by a learning system may be selected by either an external agent or the system itself. We show that knowledge of the current state of the learner...
— In the reinforcement learning literature, transfer is the capability to reuse on a new problem what has been learnt from previous experiences on similar problems. Adapting tran...
Interactive Digital TV (IDTV) opens new learning possibilities where new forms of education are needed. In this paper we explain a new conception of t-learning experiences where TV...