/SRL

State Representation Learning for Goal-Conditioned Reinforcement Learning

Primary LanguageJupyter Notebook

State Representation Learning for Goal-Conditioned Reinforcement Learning

Example.ipynb and Example_colab.ipynb present the complete pipeline going from training the model to perform planning on the learned model and use it to solve GC tasks.

Code for the algorithm presented in:

@inproceedings{steccanella2022state, title={State Representation Learning for Goal-Conditioned Reinforcement Learning}, author={Steccanella, Lorenzo and Jonsson, Anders}, booktitle={Joint European Conference on Machine Learning and Knowledge Discovery in Databases}, pages={84--99}, year={2022}, organization={Springer} }