• I saw it on Twitter.
• I enjoy participating in reinforcement learning competitions.

## Short Summary

• Reinforcement learning (RL) has now reached superhuman level on most environments of Arcade Learning Environment, so we need a new benchmark.
• Obstacle Tower environment is a new environment, with challenges in generalization, vision, planning, and control.
• Agents that use Hierarchical RL, Intrinsic Motivation, Meta-Learning or Model-based methods will probably perform better than pure baseline algorithms such as Rainbow or PPO.
• The Obstacle Tower Challenge will begin on February 11th.

## Thoughts

• The Obstacle Tower environment can perhaps be better summarized as a 3D stochastic version of Montezuma’s Revenge with an easy version of Sokoban.
• The environment is perhaps too difficult: it requires an agent with good exploration and planning, paired with a good convolutional neural network (CNN).