A collection of robotics simulation environments for reinforcement learning
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Updated
Sep 7, 2026 - Python
A collection of robotics simulation environments for reinforcement learning
High-quality single-file implementations of SOTA Offline and Offline-to-Online RL algorithms: AWAC, BC, CQL, DT, EDAC, IQL, SAC-N, TD3+BC, LB-SAC, SPOT, Cal-QL, ReBRAC
Unified Implementations of Offline Reinforcement Learning Algorithms
Clean single-file implementation of offline RL algorithms in JAX
Single-file SAC-N implementation on jax with flax and equinox. 10x faster than pytorch
Codes accompanying the paper "Score Regularized Policy Optimization through Diffusion Behavior" (ICLR 2024).
PyTorch Implementation of Offline Reinforcement Learning algorithms
Non-modular implementation of common RL algorithms
[NeurIPS 2025] A human-like RL framework that improves human-likeness while achieving strong performance, and can be easily integrated into various RL algorithms
Learning from Sparse Offline Datasets via Conservative Density Estimation (ICLR 2024)
a clear and fast jax/flax version of [Diffusion-Policies-for-Offline-RL](https://github.com/Zhendong-Wang/Diffusion-Policies-for-Offline-RL)
D4RL benchmark but ported to work end to end with gymnasium
🌟 Align diffusion processes with detailed human preferences to improve machine learning models for richer, more accurate outputs.
Online goal-reaching RL with diffusion planning: a 2D point-mass prototype plus a Maze2D Diffuser workflow driven by an autonomous agentic experiment controller.
Split conformal prediction for off-policy evaluation in offline RL (D4RL MuJoCo). Stage 1 of 4: episode reconstruction and data foundation, with guards for two silent D4RL failure modes.
Unified offline RL / offline-to-online RL course project scaffold with D4RL smoke tests
Offline RL via sequence modeling: BC, Decision Transformer, and Online DT comparison on D4RL benchmarks
[IcETRAN 2026] Official implementation of Flow Matching Policy for Behavioral Cloning paper.
Diffusion-Guided Tree Search: Uncertainty-Aware Planning with Learned World Models
ANA 699 Capstone — Offline reinforcement learning for robotics using Decision Transformers and MuJoCo
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