Implemenation of DDPG with numpy only (without Tensorflow)

PGuNN - Playing Games using Neural Networks

Policy-Based Methods. Learn the theory behind evolutionary algorithms and policy-gradient methods. Design your own algorithm to train a simulated robotic arm to reach target locations.

Robust Deep Monte Carlo Counterfactual Regret Minimization: Addressing Theoretical Risks in Neural Fictitious Self-Play

Using reinforcement learning method, Deep Q-Learning ("DQN") to have an agent learn an algorithm for automated stock trading.

Research-grade Reinforcement Learning framework for single-agent and multi-agent warehouse navigation using Deep Q-Networks (DQN), PyTorch, replay buffer, target networks, logging, and full test suite. Built for PhD-level RL and autonomous systems research.