A clean PyTorch implementation of PPO, SAC, and TD3 made from scratch. It is built for testing and comparing continuous control RL algorithms on complex environments such as BipedalWalker-v3.
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Updated
Jan 28, 2026 - Python
A clean PyTorch implementation of PPO, SAC, and TD3 made from scratch. It is built for testing and comparing continuous control RL algorithms on complex environments such as BipedalWalker-v3.
Yet another deep reinforcement learning
Derived and Implemented 9 RL algorithms from scratch in Python and simulated with GYM environments
Reinforcement learning agents (TD3 & SAC) for AirHockey, exploring the impact of policy noise, delay, and other training variations.
PyTorch implementation of off-policy RL algorithms (TD3 and SAC). Tested in OpenAI Gymnasium.
Twin-Delayed Deep Deterministic Policy Gradient network for HalfCheetahBulletEnv-v0 environment
TD3 Reinforcement Learning Implementation Project
Autonomous Robotic Arm Control (Franka Panda) using Twin Delayed DDPG (TD3) in Robosuite/MuJoCo. An implementation of Deep Reinforcement Learning for continuous control tasks like Door Opening.
Distributed Deep Learning framework based on Tensorflow2
PyTorch Implementation of off-policy reinforcement learning algorithms like Q-learning, DQN, DDPG and TD3.
Neural network and Reinforcement learning algorithms for the Bipedal Walker problem
Collection of codes pertaining to my research in model-free RL algorithms.
Jaxplorer is a Jax reinforcement learning (RL) framework for exploring new ideas.
Implemented a reinforcement learning-based autonomous parking system using TD3 in a custom Unity environment with ray sensors, stochastic initialization, and optimized reward shaping for efficient learning. 🚗🤖
Implementation of some deep RL algorithms
Direct port of TD3_BC to JAX using Haiku and optax.
Implementation of (Deep) Reinforcement Learning algorithms using PyTorch & TensorFlow2
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