In reinforcement learning (RL), the duality between exploitation and exploration has long been an important issue. This paper presents a new method that controls the balance betwe...
Contextual reasoning through graphical models such as Markov Random Fields often show superior performance against local classifiers in many domains. Unfortunately, this performanc...
As a child acquires language, he or she: perceives acoustic information in his or her surrounding environment; identifies portions of the ambient acoustic information as languager...
Andrew R. Plummer, Mary E. Beckman, Mikhail Belkin...
This paper presents a versatile and portable digital signal processing (DSP) platform that is highly suitable for learning embedded signal processing anywhere and anytime. This DS...
In this paper we apply the recent notion of anytime universal intelligence tests to the evaluation of a popular reinforcement learning algorithm, Q-learning. We show that a general...