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» A New Way to Introduce Knowledge into Reinforcement Learning
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IJCAI
2003
14 years 11 months ago
A Bayesian Approach to Imitation in Reinforcement Learning
In multiagent environments, forms of social learning such as teaching and imitation have been shown to aid the transfer of knowledge from experts to learners in reinforcement lear...
Bob Price, Craig Boutilier
HICSS
2008
IEEE
236views Biometrics» more  HICSS 2008»
15 years 4 months ago
A Case Study: Introducing eXtreme Programming in a US Government System Development Project
The US Military’s ability to meet its mission critical requirements calls for increased agility in its information technology development process. The purpose of this case study...
Ann L. Fruhling, Patrick McDonald, Christopher Dun...
ICANN
2010
Springer
14 years 10 months ago
Exploring Continuous Action Spaces with Diffusion Trees for Reinforcement Learning
We propose a new approach for reinforcement learning in problems with continuous actions. Actions are sampled by means of a diffusion tree, which generates samples in the continuou...
Christian Vollmer, Erik Schaffernicht, Horst-Micha...
ICML
2008
IEEE
15 years 10 months ago
An object-oriented representation for efficient reinforcement learning
Rich representations in reinforcement learning have been studied for the purpose of enabling generalization and making learning feasible in large state spaces. We introduce Object...
Carlos Diuk, Andre Cohen, Michael L. Littman
ATAL
2010
Springer
14 years 9 months ago
PAC-MDP learning with knowledge-based admissible models
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
Marek Grzes, Daniel Kudenko