flâneur — a map of the web's best reading

[1707.06347] Proximal Policy Optimization Algorithms

arxiv.org · 649 words · saved by 1 readers

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. arXiv Operational Status Get status notifications via email or slack

[1707.06347] Proximal Policy Optimization Algorithms Skip to main content arXiv is now an independent nonprofit! Learn more × Search arXiv Press Enter to search · Advanced search --> Computer Science > Machine Learning arXiv:1707.06347 (cs) [Submitted on 20 Jul 2017 ( v1 ), last revised 28 Aug 2017 (this version, v2)] Title: Proximal Policy Optimization Algorithms Authors: John Schulman , Filip Wolski , Prafulla Dhariwal , Alec Radford , Oleg Klimov View a PDF of the paper titled Proximal Policy Optimization Algorithms, by John Schulman and 4 other authors View PDF Abstract: We pr

Explore this link on the map →

related reading