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» Algorithms for Inverse Reinforcement Learning
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ICML
2003
IEEE
14 years 8 months ago
Hierarchical Policy Gradient Algorithms
Hierarchical reinforcement learning is a general framework which attempts to accelerate policy learning in large domains. On the other hand, policy gradient reinforcement learning...
Mohammad Ghavamzadeh, Sridhar Mahadevan
AAAI
2006
13 years 9 months ago
Reinforcement Learning with Human Teachers: Evidence of Feedback and Guidance with Implications for Learning Performance
As robots become a mass consumer product, they will need to learn new skills by interacting with typical human users. Past approaches have adapted reinforcement learning (RL) to a...
Andrea Lockerd Thomaz, Cynthia Breazeal
IJCAI
2001
13 years 9 months ago
Reinforcement Learning in Distributed Domains: Beyond Team Games
Using a distributed algorithm rather than a centralized one can be extremely beneficial in large search problems. In addition, the incorporation of machine learning techniques lik...
David Wolpert, Joseph Sill, Kagan Tumer
ECML
2006
Springer
13 years 11 months ago
Skill Acquisition Via Transfer Learning and Advice Taking
We describe a reinforcement learning system that transfers skills from a previously learned source task to a related target task. The system uses inductive logic programming to ana...
Lisa Torrey, Jude W. Shavlik, Trevor Walker, Richa...
ICML
2007
IEEE
14 years 8 months ago
Tracking value function dynamics to improve reinforcement learning with piecewise linear function approximation
Reinforcement learning algorithms can become unstable when combined with linear function approximation. Algorithms that minimize the mean-square Bellman error are guaranteed to co...
Chee Wee Phua, Robert Fitch