Learning a hierarchy

OpenAI Blog · 8 years ago

DeepMind developed a hierarchical reinforcement learning algorithm that learns reusable high-level actions to solve multiple tasks more efficiently. The algorithm enabled agents to master navigation tasks requiring thousands of timesteps by discovering intermediate behaviors like directional walking and crawling. This approach allows new tasks to be solved faster by reusing previously learned high-level action patterns rather than learning from scratch each time.