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» Ensemble Algorithms in Reinforcement Learning
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ATAL
2008
Springer
15 years 6 months ago
Sigma point policy iteration
In reinforcement learning, least-squares temporal difference methods (e.g., LSTD and LSPI) are effective, data-efficient techniques for policy evaluation and control with linear v...
Michael H. Bowling, Alborz Geramifard, David Winga...
CP
2007
Springer
15 years 10 months ago
On Universal Restart Strategies for Backtracking Search
Abstract. Constraint satisfaction and propositional satisfiability problems are often solved using backtracking search. Previous studies have shown that a technique called randomi...
Huayue Wu, Peter van Beek
ICML
2000
IEEE
15 years 8 months ago
Lightweight Rule Induction
We propose a new rule induction algorithm for solving classification problems via probability estimation. The main advantage of decision rules is their simplicity and good interp...
Sholom M. Weiss, Nitin Indurkhya
133
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KDD
2010
ACM
304views Data Mining» more  KDD 2010»
15 years 2 months ago
Automatic malware categorization using cluster ensemble
Malware categorization is an important problem in malware analysis and has attracted a lot of attention of computer security researchers and anti-malware industry recently. Today...
Yanfang Ye, Tao Li, Yong Chen, Qingshan Jiang
GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 7 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson