概念导读
The Atari 2600 game console serves as a foundational benchmark environment in reinforcement learning research. Its suite of games (via the Arcade Learning Environment) provides diverse challenges for evaluating RL algorithms, including policy-distillation and deep-q-network methods.
- Related
- References
Atari 2600
The Atari 2600 game console serves as a foundational benchmark environment in reinforcement learning research. Its suite of games (via the Arcade Learning Environment) provides diverse challenges for evaluating RL algorithms, including policy-distillation and deep-q-network methods.
Related
- policy-distillation — Atari 2600 was used as the primary benchmark in the original Policy Distillation paper (DeepMind 2015)
- deep-q-network — DQN achieved human-level performance on Atari games, establishing the benchmark
References
- Mnih et al. (2015). "Human-level control through deep reinforcement learning." Nature.