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NIPS
1994
14 years 11 months ago
Finding Structure in Reinforcement Learning
Reinforcement learning addresses the problem of learning to select actions in order to maximize one's performance inunknownenvironments. Toscale reinforcement learning to com...
Sebastian Thrun, Anton Schwartz
BROADNETS
2004
IEEE
15 years 1 months ago
Efficient QoS Provisioning for Adaptive Multimedia in Mobile Communication Networks by Reinforcement Learning
The scarcity and large fluctuations of link bandwidth in wireless networks have motivated the development of adaptive multimedia services in mobile communication networks, where i...
Fei Yu, Vincent W. S. Wong, Victor C. M. Leung
AGENTS
2001
Springer
15 years 2 months ago
Using background knowledge to speed reinforcement learning in physical agents
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
Daniel G. Shapiro, Pat Langley, Ross D. Shachter
ICML
2006
IEEE
15 years 10 months ago
Autonomous shaping: knowledge transfer in reinforcement learning
We introduce the use of learned shaping rewards in reinforcement learning tasks, where an agent uses prior experience on a sequence of tasks to learn a portable predictor that est...
George Konidaris, Andrew G. Barto
79
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ATAL
2008
Springer
14 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