SLIM: Skill Learning with Multiple Critics

no code implementations • 1 Feb 2024 • David Emukpere, Bingbing Wu, Julien Perez, Jean-Michel Renders

As it requires impacting a possibly large set of degrees of freedom composing the environment, mutual information maximization fails alone in producing useful and safe manipulation behaviors.

Hierarchical Reinforcement Learning

gym-DSSAT: a crop model turned into a Reinforcement Learning environment

no code implementations • 7 Jul 2022 • Romain Gautron, Emilio J. Padrón, Philippe Preux, Julien Bigot, Odalric-Ambrym Maillard, David Emukpere

gym-DSSAT is a gym interface to the Decision Support System for Agrotechnology Transfer (DSSAT), a high fidelity crop simulator.

Management reinforcement-learning +1

Successor Feature Neural Episodic Control

no code implementations • 4 Nov 2021 • David Emukpere, Xavier Alameda-Pineda, Chris Reinke

A longstanding goal in reinforcement learning is to build intelligent agents that show fast learning and a flexible transfer of skills akin to humans and animals.

reinforcement-learning Reinforcement Learning (RL) +1