Autonomous Pokémon Red agent using local Qwen3-VL and PyBoy. Zero API calls, zero cost, pure local VLM reasoning and computer vision.

Gameboy (Color) Environments in Gymnasium.

Super Mario Land Reinforcement Learning with Pufferlib

PPO reinforcement-learning agents that learn to play classic games from scratch - DOOM, Pokemon Red, and Street Fighter II - one standalone trainer per branch. Experimental R&D; bring your own ROMs.

Local Pokemon Red LLM-agent harness with live gameplay UI, structured traces, save states, replay, and turn-by-turn agent observability.

PyBoyとGBDK(GameBoy Developers Kit)の例

An AI agent for Street Fighter that uses reinforcement learning to improve through repeated matches, adapting its actions and strategies based on gameplay experience.

Twitch-plays-Pokemon style bot for Slack using PyBoy

AI Gym environment for Castlevania: The Adventure (Game Boy), using the PyBoy emulator.

🎮🌟A Reinforcement Learning (RL) project using Double Deep Q-Network (DDQN) to train an agent to play Kirby's Dreamland.

Reinforcement learning toolkit for training agents to play Pokémon Red. Built on PyBoy, Stable-Baselines3, and Gymnasium. Includes pixel/symbolic/hybrid observation treatments and rliable-based statistical analysis.

A learning experiment exploring how to teach an AI model how to play the game Tetris for GameBoy using StableBaselines3 and PyBoy.

Playing Pokemon Red with Reinforcement Learning

Explores reinforcement learning and its core algorithms through a PyBoy-emulated instance of Pokémon Blue.