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bsuite is a collection of carefully-designed experiments that investigate core capabilities of a reinforcement learning (RL) agent with two main objectives.
The main features of google-deepmind/bsuite are: World Models.
Projects with overlapping indexed features include: aravindr93/mjrl — This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo. arise-initiative/robomimic — [[Homepage]](https://robomimic.github.io/)   [[Documentation]](https://robomimic.github.io/docs/introduction/overv… arise-initiative/robosuite — robosuite: A Modular Simulation Framework and Benchmark for Robot Learning. bit1029public/hrssm — Code for the paper Learning Latent Dynamic Robust Representations for World Models (ICML-24). conglu1997/v-d4rl — V-D4RL provides pixel-based analogues of the popular D4RL benchmarking tasks, derived from the dmcontrol** suite,… alfworld/alfworld — Aligning Text and Embodied Environments for Interactive Learning Mohit Shridhar, Xingdi (Eric) Yuan, Marc-Alexandre…
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
[Homepage](https://robomimic.github.io/)   [Documentation](https://robomimic.github.io/docs/introduction/overview.html)   [Study Paper](https://arxiv.org/abs/2108.03298)   [Study Website](https://robomimic.github.io/study/)   [[ARISE…
robosuite: A Modular Simulation Framework and Benchmark for Robot Learning
Aligning Text and Embodied Environments for Interactive Learning Mohit Shridhar, Xingdi (Eric) Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, Matthew Hausknecht ICLR 2021