This paper proposes a novel approach to the problem of training classifiers to detect and correct grammar and usage errors in text by selectively introducing mistakes into the tra...
This paper introduces a gradient-based reward prediction update mechanism to the XCS classifier system as applied in neuralnetwork type learning and function approximation mechani...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
Abstract--In the Relational Reinforcement learning framework, we propose an algorithm that learns an action model allowing to predict the resulting state of each action in any give...
: In this paper, we propose an improved context-aware system for supporting to learning Japanese mimicry and onomatopoeia (MIO) using sensor data. In our two previous studies, we p...
Bin Hou, Hiroaki Ogata, Masayuki Miyata, Mengmeng ...
Mobile computing technologies and social software have given new challenges to technology-enhanced learning. Simple e-learning system personalization, adaptation and authoring beco...