https://github.com/kartik2309/rlpack

Implementation of RL Algorithms with PyTorch.

a2c-agent a2c-algorithm a2c-pytorch a3c a3c-agent a3c-pytorch deep-reinforcement-learning dqn dqn-pytorch gym-environments prioritized-experience-replay pytorch-implementation reinforcement-learning

Last synced: 09 Oct 2025

https://github.com/germanpaul12/lunar_lander_reinforcement_genetic_policy_learning

a2c-agent dqn-agents genetic-algorithm gymnasium-environment lunar-lander ppo-agent reinforce-algorithm reinforcement-learning

Last synced: 16 May 2026

https://github.com/jookie/jojostock1

An adaptive Machine Reinforcement Learning (MRL) system is being developed to gather and analyze media data using web scraping, training models to predict outcomes in areas like stock market trends, sports events, and other performance domains. It continuously refines its strategies based on real-time data and evolving patterns.

a2c-agent cryptocurrency day-trader ddpg-algorithm ppo-agent sentiment-analysis td3-pytorch

Last synced: 19 Mar 2026

https://github.com/starlitdreams/kungfu-a2c

Kung Fu Master A2C Agent is a PyTorch implementation of the Advantage Actor–Critic (A2C) algorithm, engineered to learn and play the Atari classic Kung Fu Master. It uses Gymnasium (with ALE ROMs) to manage multiple parallel environments and a custom preprocessing wrapper.

a2c a2c-agent actor-critic agentic-ai atari convolutional-neural-networks deep-reinforcement-learning gymnasium image-preprocessing kungfumaster python python3 pytorch reinforcement-learning

Last synced: 17 Apr 2026