State Representation Learning

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics
Scaling end-to-end reinforcement learning to control real robots from vision presents a series of challenges, in particular in terms of …
Antonin Raffin, Ashley W.D. Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, David Filliat
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S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
State representation learning aims at learning compact representations from raw observations in robotics and control applications. …
Antonin Raffin, Ashley W.D. Hill, René Traoré, Timothée Lesort, Natalia Díaz-Rodríguez, David Filliat
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S-RL Toolbox
S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics
S-RL Toolbox