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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
CEC
2010
IEEE
13 years 11 months ago
Learning to overtake in TORCS using simple reinforcement learning
In modern racing games programming non-player characters with believable and sophisticated behaviors is getting increasingly challenging. Recently, several works in the literature ...
Daniele Loiacono, Alessandro Prete, Pier Luca Lanz...
AAAI
2006
13 years 11 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
ESANN
2008
13 years 11 months ago
Learning to play Tetris applying reinforcement learning methods
In this paper the application of reinforcement learning to Tetris is investigated, particulary the idea of temporal difference learning is applied to estimate the state value funct...
Alexander Groß, Jan Friedland, Friedhelm Sch...
NIPS
2001
13 years 11 months ago
Reinforcement Learning with Long Short-Term Memory
This paper presents reinforcement learning with a Long ShortTerm Memory recurrent neural network: RL-LSTM. Model-free RL-LSTM using Advantage learning and directed exploration can...
Bram Bakker