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» MDPs: Learning in Varying Environments
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ML
2002
ACM
143views Machine Learning» more  ML 2002»
13 years 9 months ago
A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
Michael J. Kearns, Yishay Mansour, Andrew Y. Ng
IIE
2006
84views more  IIE 2006»
13 years 9 months ago
Promoting Different Kinds of Learners towards Active Learning in the Web-Based Environment
According to many recent studies the effect of learning style on academic performance has been found to be significant and mismatch between teaching and learning styles causes lear...
Anu Haapala
IROS
2006
IEEE
121views Robotics» more  IROS 2006»
14 years 3 months ago
Planning and Acting in Uncertain Environments using Probabilistic Inference
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Deepak Verma, Rajesh P. N. Rao
NIPS
2007
13 years 11 months ago
Bayes-Adaptive POMDPs
Bayesian Reinforcement Learning has generated substantial interest recently, as it provides an elegant solution to the exploration-exploitation trade-off in reinforcement learning...
Stéphane Ross, Brahim Chaib-draa, Joelle Pi...
WMTE
2005
IEEE
14 years 3 months ago
Supporting Pervasive Learning Environments: Adaptability and Context Awareness in Mobile Learning
In the mobile learning context, it is helpful to consider context awareness and adaptivity as two sides of the same coin. The purpose of the adaptivity and context awareness is to...
Antti Syvänen, Russell Beale, Mike Sharples, ...