How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box function. This type of optimization is used across scientific and engineering disciplines in ways such as designing proteins and DNA sequences with particular…
Official code for the "Towards Evaluating Adaptivity of Model-Based Reinforcement Learning" paper.
This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
ROBEL is an open-source platform of cost-effective robots and associated reinforcement learning environments for benchmarking reinforcement learning in the real world. It provides Gym-compliant environments that easily run in both simulation (for rapid prototyping) and on real hardware. ROBEL…
The main features of google-research/robel are: Reinforcement Learning Environments.
Projects with overlapping indexed features include: benelot/pybullet-gym — PyBullet Gymperium. brandontrabucco/design-bench — Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that… chandar-lab/loca2 — Official code for the "Towards Evaluating Adaptivity of Model-Based Reinforcement Learning" paper. clvoloshin/cobs — COBS is an Off-Policy Policy Evaluation (OPE) Benchmarking Suite. The goal is to provide fine experimental control to… cvdfoundation/kinetics-dataset — Kinetics is a collection of large-scale, high-quality datasets of URL links of up to 650,000 video clips that cover… aravindr93/mjrl — This package contains implementations of various RL algorithms for continuous control tasks simulated with MuJoCo.
