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GECCO
2009
Springer
162views Optimization» more  GECCO 2009»
13 years 5 months ago
Uncertainty handling CMA-ES for reinforcement learning
The covariance matrix adaptation evolution strategy (CMAES) has proven to be a powerful method for reinforcement learning (RL). Recently, the CMA-ES has been augmented with an ada...
Verena Heidrich-Meisner, Christian Igel
SIGMETRICS
2002
ACM
118views Hardware» more  SIGMETRICS 2002»
13 years 7 months ago
Robust traffic engineering: game theoretic perspective
On-line routing algorithms deal with requests as they arrive without assuming any knowledge of the underlying process that generates the streams of requests. By contrast, off-line...
Vladimir Marbukh
AUTOMATICA
2006
152views more  AUTOMATICA 2006»
13 years 7 months ago
Simulation-based optimization of process control policies for inventory management in supply chains
A simulation-based optimization framework involving simultaneous perturbation stochastic approximation (SPSA) is presented as a means for optimally specifying parameters of intern...
Jay D. Schwartz, Wenlin Wang, Daniel E. Rivera
CORR
2010
Springer
146views Education» more  CORR 2010»
13 years 7 months ago
Adaptive Submodularity: A New Approach to Active Learning and Stochastic Optimization
Solving stochastic optimization problems under partial observability, where one needs to adaptively make decisions with uncertain outcomes, is a fundamental but notoriously diffic...
Daniel Golovin, Andreas Krause
ATAL
2009
Springer
14 years 1 months ago
Computing optimal randomized resource allocations for massive security games
Predictable allocations of security resources such as police officers, canine units, or checkpoints are vulnerable to exploitation by attackers. Recent work has applied game-theo...
Christopher Kiekintveld, Manish Jain, Jason Tsai, ...