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» Ensemble Algorithms in Reinforcement Learning
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ML
2006
ACM
163views Machine Learning» more  ML 2006»
15 years 4 months ago
Extremely randomized trees
Abstract This paper proposes a new tree-based ensemble method for supervised classification and regression problems. It essentially consists of randomizing strongly both attribute ...
Pierre Geurts, Damien Ernst, Louis Wehenkel
ICML
2000
IEEE
16 years 5 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
ICML
2004
IEEE
15 years 9 months ago
Towards tight bounds for rule learning
While there is a lot of empirical evidence showing that traditional rule learning approaches work well in practice, it is nearly impossible to derive analytical results about thei...
Ulrich Rückert, Stefan Kramer
NIPS
1996
15 years 5 months ago
Exploiting Model Uncertainty Estimates for Safe Dynamic Control Learning
Model learning combined with dynamic programming has been shown to be e ective for learning control of continuous state dynamic systems. The simplest method assumes the learned mod...
Jeff G. Schneider
AIIDE
2008
15 years 6 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,...