Easy to use Python library for creating 2D arcade games.
-
Updated
Jul 10, 2026 - Python
Easy to use Python library for creating 2D arcade games.
A Universal Deep Reinforcement Learning Framework
Codes for "Efficient Offline Policy Optimization with a Learned Model", ICLR2023
(ICLR 2021) Learning to Represent Action Values as a Hypergraph on the Action Vertices
Distributed RL platform with modified IMPALA architecture. Implements CLEAR, LASER V-trace modifications along with Attentive and Elite sampling experience replay methods.
Experiments with multiple reinforcement ML algorithms to learn how to beat Street Fighter II
Reinforcement learning with Qbert. Assignment 3 of ECSE-526.
Trained a reinforcement learning agent to play the Atari 2600 game of Ms. Pac-Man. Built a web-app to live stream gameplay with TCP/IP in real-time with Flask as the app interface.
A learned continuous slow→fast latent channel for real-time game agents: frozen MiniCPM-o 4.5 (fast) + Qwen3-VL-8B-Thinking (slow), 33M-param bridge. The latent helps iff slow reasoning helps (T>F). Paper: arXiv:2606.24470
Implementation of the Arcade Learning Environment (ALE) for playing pacman on the Atari 2600 using Machine Learning
track and log actions for a human player via Arcade Learning Environment
This project implements a Deep Q-Network (DQN) to train an agent to play an Atari game. The agent is trained using reinforcement learning and interacts with the environment to maximize its score.
A Deep Q-Network (DQN) implementation for Atari Space Invaders using Gymnasium and PyTorch.
Deep reinforcement learning on Atari Donkey Kong: a reproducible single-GPU study of PPO and self-imitation learning.
Go transliteration of MinAtar
Add a description, image, and links to the arcade-learning-environment topic page so that developers can more easily learn about it.
To associate your repository with the arcade-learning-environment topic, visit your repo's landing page and select "manage topics."