We propose an opponent modeling approach for no-limit Texas hold-em poker that starts from a (learned) prior, i.e., general expectations about opponent behavior and learns a relat...
Marc J. V. Ponsen, Jan Ramon, Tom Croonenborghs, K...
It has been unclear whether optimal experimental design accounts of data selection may offer insight into evidence acquisition tasks in which the learner’s beliefs change greatl...
This paper analyzes the performance of semisupervised learning of mixture models. We show that unlabeled data can lead to an increase in classification error even in situations wh...
Fabio Gagliardi Cozman, Ira Cohen, Marcelo Cesar C...
Abstract. Building on the current understanding of neural architecture of the visual cortex, we present a graphical model for learning and classification of motion patterns in vid...
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...