State Representation Learning

Decoupling feature extraction from policy learning: assessing benefits of state representation learning in goal based robotics

We evaluate the benefits of decoupling feature extraction from policy learning in robotics and propose a new way of combining state representation learning methods.

S-RL Toolbox

S-RL Toolbox: Reinforcement Learning (RL) and State Representation Learning (SRL) for Robotics

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. Approaches used for this objective are auto-encoders, learning forward models, inverse dynamics or learning using …

Arduino Robust Serial

A simple and robust serial communication protocol. Implementation in C Arduino, C++, Python and Rust.

Unsupervised learning of state representations for multiple tasks

We present an approach for learning state representations in multi-task reinforcement learning. Our method learns multiple low-dimensional state representations from raw observations in an unsupervised fashion, without any knowledge of which task is …