hanyas / reps

Implementation of different Relative Entropy Policy Search flavors

Geek Repo:Geek Repo

Github PK Tool:Github PK Tool

REPS

Implementation of different Relative Entropy Policy Search flavors

This package provides reference implementations for a family of algorithms all related to Relative Entropy Policy Search (REPS), one of the first algorithms to propose a KL-based trust-region regularization in reinforcement learning.

The following references are not all are specifically implemented, but have informed the available implementations.

General REPS Formulation:

Jan Peters, Katharina Mulling, and Yasemin Altun. "Relative entropy policy search"

https://www.ias.informatik.tu-darmstadt.de/uploads/Team/JanPeters/Peters2010_REPS.pdf

Herk Van Hoof, Gerhard Neumann, and Jan Peters. "Non-parametric policy search with limited information loss"

https://www.jmlr.org/papers/volume18/16-142/16-142.pdf

Boris Belousov, and Jan Peters. "f-Divergence constrained policy improvement"

https://arxiv.org/pdf/1801.00056.pdf

Christian Wirth, Johannes Fürnkranz, and Gerhard Neumann. "Model-free preference-based reinforcement learning"

https://ojs.aaai.org/index.php/AAAI/article/view/10269

Episodic/Contextual REPS

Marc Deisenroth, Gerhard Neumann, and Jan Peters. "A survey on policy search for robotics"

https://www.ias.informatik.tu-darmstadt.de/uploads/Site/EditPublication/PolicySearchReview.pdf

Simone Parisi, Hany Abdulsamad, Alexandros Paraschos, Christian Daniel, and Jan Peters. "Reinforcement learning vs human programming in tetherball robot games"

https://ieeexplore.ieee.org/abstract/document/7354296/

Andras Kupcsik, Marc Deisenroth, Jan Peters, and Gerhard Neumann. "Data-efficient generalization of robot skills with contextual policy search"

https://ojs.aaai.org/index.php/AAAI/article/view/8546

Hierarchical REPS

Christian Daniel, Gerhard Neumann, and Jan Peters. "Hierarchical relative entropy policy search"

https://proceedings.mlr.press/v22/daniel12/daniel12.pdf

Christian Daniel, Herke Van Hoof, Jan Peters, and Gerhard Neumann. "Probabilistic inference for determining options in reinforcement learning"

https://link.springer.com/article/10.1007/s10994-016-5580-x

(Model-Based) Episodic/Contextual REPS (MORE):

Abbas Abdolmaleki, Rudolf Lioutikov, Jan Peters, Nuno Lau, Luis Pualo Reis, and Gerhard Neumann. "Model-based relative entropy stochastic search"

https://papers.nips.cc/paper/2015/hash/36ac8e558ac7690b6f44e2cb5ef93322-Abstract.html

Voot Tangkaratt, Herke van Hoof, Simone Parisi, Gerhard Neumann, Jan Peters, and Masashi Sugiyama. "Policy search with high-dimensional context variables"

https://ojs.aaai.org/index.php/AAAI/article/view/10911

About

Implementation of different Relative Entropy Policy Search flavors

License:MIT License


Languages

Language:Python 100.0%