wiitt/DQN-Car-Racing
Implementation of DQN and DDQN algorithms for Playing Car Racing Game
This project helps train an AI agent to play the Car Racing game from OpenAI Gymnasium. It takes in game frames and other car data, processes them, and outputs steering and acceleration commands to navigate a race car efficiently around a track. It's designed for researchers and enthusiasts exploring reinforcement learning for game AI.
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Use this if you are a machine learning researcher or student interested in applying and understanding deep Q-learning (DQN and DDQN) algorithms for game AI in simulated environments.
Not ideal if you're looking for a general-purpose reinforcement learning framework or a tool to play a different game, as it's specifically tailored for the Car Racing environment.
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Aug 31, 2025
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