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» Qualitative reinforcement learning
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IJCNN
2008
IEEE
14 years 3 months ago
Learning to select relevant perspective in a dynamic environment
— When an agent observes its environment, there are two important characteristics of the perceived information. One is the relevance of information and the other is redundancy. T...
Zhihui Luo, David A. Bell, Barry McCollum, Qingxia...
JCAL
2002
80views more  JCAL 2002»
13 years 8 months ago
Factors contributing to teachers' successful implementation of IT
It has become increasingly important for educators to examine successful ICT implementations with the aim of understanding precisely what makes them successful in teaching and lear...
C. A. Granger, M. L. Morbey, H. Lotherington, Rona...
ITS
2004
Springer
155views Multimedia» more  ITS 2004»
14 years 2 months ago
Modeling the Development of Problem Solving Skills in Chemistry with a Web-Based Tutor
This research describes a probabilistic approach for developing predictive models of how students learn problem-solving skills in general qualitative chemistry. The goal is to use ...
Ron Stevens, Amy Soller, Melanie Cooper, Marcia Sp...
AIIDE
2008
13 years 11 months ago
Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...
ICML
2000
IEEE
14 years 10 months ago
Eligibility Traces for Off-Policy Policy Evaluation
Eligibility traces have been shown to speed reinforcement learning, to make it more robust to hidden states, and to provide a link between Monte Carlo and temporal-difference meth...
Doina Precup, Richard S. Sutton, Satinder P. Singh