Human level Atari 200x faster Reimplementation
- Implemented a deep reinforcement-learning agent based on DQN that surpasses human benchmark on the atari suite.
- Implemented algorithmic optimizations to reduce compute requirements by 200x compared to its predecessor Agent57.
- Achieved state-of-the-art performance across all 57 Atari games, demonstrating robust generalization and sample efficiency.