Learning a hierarchy
8a
Idade
- Publicado
- Coletado
We’ve developed a hierarchical reinforcement learning algorithm that learns high-level actions useful for solving a range of tasks, allowing fast solving of tasks requiring thousands of timesteps. Our algorithm, when applied to a set of navigation problems, discovers a set of high-level actions for walking and crawling in different directions, which enables the agent to master new navigation tasks quickly.
O overfeed.news indexa e aponta. Publicamos um trecho curto — o artigo completo fica em OpenAI News.
Mais de OpenAI News
Entre para seguir esta fonteBetter answers, broader thinking: What students gain from ChatGPT and critical-thinking training
A randomized study of more than 1,000 students examines ChatGPT, critical thinking, originality, and student performance on a real-world university assignment.
Expanding OpenAI’s presence in Brazil
OpenAI is expanding its presence in Brazil, deepening engagement with developers, businesses, and communities to support AI adoption across the country.
Learning never stops: How AI makes learning continuous
OpenAI’s new report explores how students and educators use ChatGPT to make learning more continuous, with support that extends beyond the classroom.
Bringing ChatGPT for Teachers to more U.S. school districts
ChatGPT for Teachers is expanding to 55 U.S. school systems, bringing secure AI tools, training, and support to over 100,000 more educators and staff.