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JMLR
2010
189views more  JMLR 2010»
15 years 1 months ago
Adaptive Step-size Policy Gradients with Average Reward Metric
In this paper, we propose a novel adaptive step-size approach for policy gradient reinforcement learning. A new metric is defined for policy gradients that measures the effect of ...
Takamitsu Matsubara, Tetsuro Morimura, Jun Morimot...
NN
2010
Springer
187views Neural Networks» more  NN 2010»
15 years 1 months ago
Efficient exploration through active learning for value function approximation in reinforcement learning
Appropriately designing sampling policies is highly important for obtaining better control policies in reinforcement learning. In this paper, we first show that the least-squares ...
Takayuki Akiyama, Hirotaka Hachiya, Masashi Sugiya...
AAAI
2011
14 years 6 months ago
Linear Dynamic Programs for Resource Management
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Marek Petrik, Shlomo Zilberstein

Publication
151views
14 years 5 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
MOBICOM
2009
ACM
16 years 27 days ago
Interference management via rate splitting and HARQ over time-varying fading channels
The coexistence of two unlicensed links is considered, where one link interferes with the transmission of the other, over a timevarying, block-fading channel. In the absence of fa...
Marco Levorato, Osvaldo Simeone, Urbashi Mitra