No description available

Jax implementation of Proximal Policy Optimization (PPO) specifically tuned for Procgen, with benchmarked results and saved model weights on all environments.

Implementation of Proximal Policy Optimization in Jax+Flax

RL environments and PPO training code to develop trajectory tracking controllers for various robot systems, written in Jax.

KAGE-Bench: pure JAX 2D platformer RL benchmark for visual OOD generalization. Massively-parallel (vmap/JIT) RGB env with YAML-configurable visuals/physics, plus PPO-CNN (Flax) training scripts.

JAX Implementation of Proximal Policy Optimisation Algorithm

Implementing and testing HiPPO and S4

jax version of ppo algorithm in mujoco enviroment, achieve SOTA(tianshou)

No description available

This repository aims to provide the minimalism of cleanRL with the performance of SBX

a jax implementation of highway environment PPO agent with discrete and continuous spaces

Near-SOTA PPO implementation with Jax+Brax+Equinox

A repo of Proximal Policy Optimisation (PPO) algorithms written in JAX

Implementation of PPO for recurrent/stateful networks using JAX and flax.nnx

A JAX/Flax implementation of Independent PPO for cooperative multi-agent reinforcement learning on the Overcooked-AI benchmark

A custom, high-performance Proximal Policy Optimization (PPO) agent implemented in pure JAX/Equinox, designed to control building energy simulations (PhyLFlex project) at massive scale.

Deep Reinforcement Learning based Rubik’s Cube solver written in JAX, Haiku and RLax. Developed a custom environment supporting cubes of variable size. Currently developing support for DQN, QR-DQN and PPO.

JAX-Brax reinforcement learning pipeline for training a passive bipedal walker. Implements a curriculum from FSM expert demonstrations to BC-seeded PPO for robust locomotion. Features GPU-accelerated physics, parallel training, and scalable network architectures for efficient learning.

ppo in jax

No description available

ppo in pure jax

Cartpole PPO with JAX

Minimal implementation of Proximal Policy Optimization (PPO) using Jax

No description available

No description available

Easy-to-follow implementation of Proximal Policy Optimization in JAX (Gym Compatible)

JAX implementation of Proximal Policy Optimization (PPO) applied to CartPole environment. Demonstrates policy gradient reinforcement learning with modular, efficient code. Includes neural network policy, value function, and adaptive training techniques.

No description available

a fully jitted & multi accelerator JAX implementation of PPO for discrete and continuous envs

minimal PPO training script (JAX)