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» Reinforcement learning in a nutshell
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ATAL
2008
Springer
13 years 9 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
ICML
2004
IEEE
14 years 8 months ago
Apprenticeship learning via inverse reinforcement learning
We consider learning in a Markov decision process where we are not explicitly given a reward function, but where instead we can observe an expert demonstrating the task that we wa...
Pieter Abbeel, Andrew Y. Ng
ICML
2005
IEEE
14 years 8 months ago
Exploration and apprenticeship learning in reinforcement learning
We consider reinforcement learning in systems with unknown dynamics. Algorithms such as E3 (Kearns and Singh, 2002) learn near-optimal policies by using "exploration policies...
Pieter Abbeel, Andrew Y. Ng
CEC
2010
IEEE
13 years 8 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 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