We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Personalized instruction is seen as a desideratum of today's e-learning systems. The focus of this paper is on those platforms that use learning styles as personalization crit...
— The least squares approach works efficiently in value function approximation, given appropriate basis functions. Because of its smoothness, the Gaussian kernel is a popular an...
Masashi Sugiyama, Hirotaka Hachiya, Christopher To...
A neglected challenge in existing e-Learning (eL) systems is providing access to multimedia to all users regardless of environmental conditions such as diverse device capabilities,...
Inverse Reinforcement Learning (IRL) is the problem of learning the reward function underlying a Markov Decision Process given the dynamics of the system and the behaviour of an e...