---
title: "Atari 2600"
created: 2026-04-15
updated: 2026-04-15
type: concept
tags: [benchmark, rl]
sources: []
---

# 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.