{"data":{"full_name":"ShivamGupta92/Reinforcement_learning_SnakeGameAI","name":"Reinforcement_learning_SnakeGameAI","description":"Deep Q-Networks (DQN) to train an AI agent to play the Snake game. The AI controls the snake, making decisions in real-time to maximize its score while avoiding collisions. The agent learns to improve its performance by playing multiple games and adjusting its strategy based on rewards and penalties.","stars":1.0,"forks":0.0,"language":"Python","license":"Apache-2.0","archived":0.0,"subcategory":"snake-game-ai","last_pushed_at":"2024-08-17T04:45:57+00:00","pypi_package":null,"npm_package":null,"downloads_monthly":0.0,"dependency_count":0.0,"commits_30d":null,"reverse_dep_count":0.0,"maintenance_score":0.0,"adoption_score":1.0,"maturity_score":9.0,"community_score":0.0,"quality_score":10.0,"quality_tier":"experimental","risk_flags":"['stale_6m', 'no_package', 'no_dependents']"},"meta":{"timestamp":"2026-04-08T15:17:25.667398+00:00"}}