S-RL Toolbox: Environments, Datasets and Evaluation Metrics for State Representation Learning
| Autor: | Antonin Raffin, Ashley Hill, René Traoré, Timothée LESORT, Natalia Díaz-Rodríguez, David Filliat |
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| Přispěvatelé: | Unité d'Informatique et d'Ingénierie des Systèmes (U2IS), École Nationale Supérieure de Techniques Avancées (ENSTA Paris), Flowing Epigenetic Robots and Systems (Flowers), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Unité d'Informatique et d'Ingénierie des Systèmes (U2IS), École Nationale Supérieure de Techniques Avancées (ENSTA Paris)-École Nationale Supérieure de Techniques Avancées (ENSTA Paris), Thales Research and Technology [Palaiseau], THALES, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), THALES [France] |
| Rok vydání: | 2018 |
| Předmět: |
Computer Science::Machine Learning
FOS: Computer and information sciences reinforcement learning Computer Science - Machine Learning Statistics - Machine Learning robotic priors [INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO] Deep learning Machine Learning (stat.ML) state representation learning Machine Learning (cs.LG) |
| Zdroj: | HAL NeurIPS 2018 Workshop on “Deep Reinforcement Learning” NeurIPS 2018 Workshop on “Deep Reinforcement Learning”, Dec 2018, Montreal, Canada |
| DOI: | 10.48550/arxiv.1809.09369 |
| Popis: | 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 generic priors on the state characteristics. However, the diversity in applications and methods makes the field lack standard evaluation datasets, metrics and tasks. This paper provides a set of environments, data generators, robotic control tasks, metrics and tools to facilitate iterative state representation learning and evaluation in reinforcement learning settings. Comment: Github repo: https://github.com/araffin/robotics-rl-srl Documentation: https://s-rl-toolbox.readthedocs.io/en/latest/ |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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