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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
ATAL
2007
Springer
14 years 2 months ago
Letting loose a SPIDER on a network of POMDPs: generating quality guaranteed policies
Distributed Partially Observable Markov Decision Problems (Distributed POMDPs) are a popular approach for modeling multi-agent systems acting in uncertain domains. Given the signi...
Pradeep Varakantham, Janusz Marecki, Yuichi Yabu, ...
ATAL
2009
Springer
14 years 2 months ago
Generalized model learning for reinforcement learning in factored domains
Improving the sample efficiency of reinforcement learning algorithms to scale up to larger and more realistic domains is a current research challenge in machine learning. Model-ba...
Todd Hester, Peter Stone
ERSHOV
1989
Springer
13 years 12 months ago
Experiments with Implementations of Two Theoretical Constructions
This paper reports two experiments with implementations of constructions from theoretical computer science. The first one deals with Kleene’s and Rogers’ second recursion the...
Torben Amtoft Hansen, Thomas Nikolajsen, Jesper La...
COR
2007
86views more  COR 2007»
13 years 7 months ago
Sourcing with random yields and stochastic demand: A newsvendor approach
We studied a supplier selection problem, where a buyer, while facing random demand, is to decide ordering quantities from a set of suppliers with different yields and prices.We pr...
Shitao Yang, Jian Yang, Layek Abdel-Malek