We introduce a learning framework that combines elements of the well-known PAC and mistake-bound models. The KWIK (knows what it knows) framework was designed particularly for its...
Comparative evaluation of Machine Learning (ML) systems used for Information Extraction (IE) has suffered from various inconsistencies in experimental procedures. This paper repor...
Neil Ireson, Fabio Ciravegna, Mary Elaine Califf, ...
In classification with monotonicity constraints, it is assumed that the class label should increase with increasing values on the attributes. In this paper we aim at formalizing ...
— In this paper, we propose a reinforcement learning approach to address multi-robot cooperative navigation tasks in infinite settings. We propose an algorithm to simultaneously...
How can game designers realize the balance of “educational function” and “entertainment” in a Computer-based Educational Game (CEG)? The concept of IMS learning design (LD...