We present a data-driven approach to learn user-adaptive referring expression generation (REG) policies for spoken dialogue systems. Referring expressions can be difficult to unde...
Agent technology is a good approach for solving a number of problems concerned with personalized learning. In personal learning contexts individual students are given an environme...
Ali M. Aseere, Enrico H. Gerding, David E. Millard
In response to Rodriguez' recent article (2001) we compare the performance of simple recurrent nets and "Long Short-Term Memory" (LSTM) recurrent nets on context-fr...
In this paper, we propose a context-aware food recommendation system for well-being care applications. The proposed system, called u-BabSang, provides individualized food recommend...
Abstract. Factored Markov Decision Processes is the theoretical framework underlying multi-step Learning Classifier Systems research. This framework is mostly used in the context ...