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» Using Machine Learning to Focus Iterative Optimization
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AI
2002
Springer
15 years 2 months ago
Multiagent learning using a variable learning rate
Learning to act in a multiagent environment is a difficult problem since the normal definition of an optimal policy no longer applies. The optimal policy at any moment depends on ...
Michael H. Bowling, Manuela M. Veloso
105
Voted
AAAI
2008
15 years 4 months ago
Adaptive Treatment of Epilepsy via Batch-mode Reinforcement Learning
This paper highlights the crucial role that modern machine learning techniques can play in the optimization of treatment strategies for patients with chronic disorders. In particu...
Arthur Guez, Robert D. Vincent, Massimo Avoli, Joe...
CORR
2010
Springer
105views Education» more  CORR 2010»
15 years 27 days ago
Optimism in Reinforcement Learning Based on Kullback-Leibler Divergence
We consider model-based reinforcement learning in finite Markov Decision Processes (MDPs), focussing on so-called optimistic strategies. Optimism is usually implemented by carryin...
Sarah Filippi, Olivier Cappé, Aurelien Gari...
ALT
2008
Springer
15 years 11 months ago
Numberings Optimal for Learning
This paper extends previous studies on learnability in non-acceptable numberings by considering the question: for which criteria which numberings are optimal, that is, for which nu...
Sanjay Jain, Frank Stephan
CHI
2009
ACM
16 years 2 months ago
EnsembleMatrix: interactive visualization to support machine learning with multiple classifiers
Machine learning is an increasingly used computational tool within human-computer interaction research. While most researchers currently utilize an iterative approach to refining ...
Justin Talbot, Bongshin Lee, Ashish Kapoor, Desney...