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GECCO
2006
Springer
133views Optimization» more  GECCO 2006»
14 years 16 days ago
On-line evolutionary computation for reinforcement learning in stochastic domains
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...
Shimon Whiteson, Peter Stone
ATAL
2008
Springer
13 years 11 months ago
Graph Laplacian based transfer learning in reinforcement learning
The aim of transfer learning is to accelerate learning in related domains. In reinforcement learning, many different features such as a value function and a policy can be transfer...
Yi-Ting Tsao, Ke-Ting Xiao, Von-Wun Soo
DAS
2008
Springer
13 years 10 months ago
Truthing for Pixel-Accurate Segmentation
We discuss problems in developing policies for ground truthing document images for pixel-accurate segmentation. First, we describe ground truthing policies that apply to four diff...
Michael A. Moll, Henry S. Baird, Chang An
CLUSTER
2006
IEEE
13 years 9 months ago
Deferred Assignment Scheduling in Cluster-Based Servers
This paper proposes a new scheduling policy for cluster-based servers called DAS (Deferred Assignment Scheduling). The main idea in DAS is to defer scheduling as much as possible,...
Victoria Ungureanu, Benjamin Melamed, Michael N. K...
JSAC
2011
159views more  JSAC 2011»
13 years 3 months ago
An Anti-Jamming Stochastic Game for Cognitive Radio Networks
—Various spectrum management schemes have been proposed in recent years to improve the spectrum utilization in cognitive radio networks. However, few of them have considered the ...
Beibei Wang, Yongle Wu, K. J. Ray Liu, T. Charles ...