We present a reinforcement learning architecture, Dyna-2, that encompasses both samplebased learning and sample-based search, and that generalises across states during both learni...
— Traditional approaches to integrating knowledge into neural network are concerned mainly about supervised learning. This paper presents how a family of self-organizing neural m...
This paper presents an experience in designing, implementing, and evaluating a studio-based learning model for CS2. Adapted from architecture and art education, as well as from co...
T. Dean Hendrix, Lakshman Myneni, N. Hari Narayana...
Abstract. We report our work towards building user models of learner’s development based upon evidence of their interactions with an e-learning website composed of multimedia lea...
Reinforcement learning (RL) is one of the machine learning techniques and has been received much attention as a new self-adaptive controller for various systems. The RL agent auto...