- See Also
-
Links
- “Towards Playing Full MOBA Games With Deep Reinforcement Learning”, Et Al 2020
- “Mastering Complex Control in MOBA Games With Deep Reinforcement Learning”, Et Al 2019
- “OpenAI Five: 2016–2019”, OpenAI 2019
- “Dota 2 With Large Scale Deep Reinforcement Learning”, Et Al 2019
- “Solving Rubik’s Cube With a Robot Hand”, OpenAI Et Al 2019
- “Solving Rubik’s Cube With a Robot Hand [blog]”, OpenAI 2019
- “How AI Training Scales”, Et Al 2018
- “An Empirical Model of Large-Batch Training”, Et Al 2018
- “Emergent Complexity via Multi-Agent Competition”, Et Al 2017
- “Proximal Policy Optimization Algorithms”, Et Al 2017
- “Net2Net: Accelerating Learning via Knowledge Transfer”, Et Al 2015
- “If You Want to Solve a Hard Problem in Reinforcement Learning, You Just Scale. It’s Just Gonna Work Just like Supervised Learning. It’s the Same, the Same Story Exactly. It Was Kind of Hard to Believe That Supervised Learning Can Do All Those Things, but It’s Not Just Vision, It’s Everything and the Same Thing Seems to Hold for Reinforcement Learning Provided You Have a Lot of Experience.”
- Wikipedia
- Miscellaneous
- Link Bibliography
See Also
Links
“Towards Playing Full MOBA Games With Deep Reinforcement Learning”, Et Al 2020
“Towards Playing Full MOBA Games with Deep Reinforcement Learning”, 2020-11-25 ( ; similar; bibliography)
“Mastering Complex Control in MOBA Games With Deep Reinforcement Learning”, Et Al 2019
“Mastering Complex Control in MOBA Games with Deep Reinforcement Learning”, 2019-12-20 ( ; similar)
“OpenAI Five: 2016–2019”, OpenAI 2019
“OpenAI Five: 2016–2019”, 2019-12-13 (backlinks)
“Dota 2 With Large Scale Deep Reinforcement Learning”, Et Al 2019
“Dota 2 with Large Scale Deep Reinforcement Learning”, 2019-12-13 (similar)
“Solving Rubik’s Cube With a Robot Hand”, OpenAI Et Al 2019
“Solving Rubik’s Cube with a Robot Hand”, 2019-10-16 ( ; similar)
“Solving Rubik’s Cube With a Robot Hand [blog]”, OpenAI 2019
“Solving Rubik’s Cube with a Robot Hand [blog]”, 2019-10-15 ( ; backlinks; similar)
“How AI Training Scales”, Et Al 2018
“How AI Training Scales”, 2018-12-14 ( ; backlinks; similar; bibliography)
“An Empirical Model of Large-Batch Training”, Et Al 2018
“An Empirical Model of Large-Batch Training”, 2018-12-14 ( ; similar)
“Emergent Complexity via Multi-Agent Competition”, Et Al 2017
“Emergent Complexity via Multi-Agent Competition”, 2017-10-10 ( ; similar)
“Proximal Policy Optimization Algorithms”, Et Al 2017
“Proximal Policy Optimization Algorithms”, 2017-07-20 ( ; similar)
“Net2Net: Accelerating Learning via Knowledge Transfer”, Et Al 2015
“Net2Net: Accelerating Learning via Knowledge Transfer”, 2015-11-18 ( ; backlinks; similar)
“If You Want to Solve a Hard Problem in Reinforcement Learning, You Just Scale. It’s Just Gonna Work Just like Supervised Learning. It’s the Same, the Same Story Exactly. It Was Kind of Hard to Believe That Supervised Learning Can Do All Those Things, but It’s Not Just Vision, It’s Everything and the Same Thing Seems to Hold for Reinforcement Learning Provided You Have a Lot of Experience.”
Wikipedia
Miscellaneous
-
https://medium.com/syncedreview/openais-long-pursuit-of-dota-2-mastery-1d3a861472bd
-
https://old.reddit.com/r/DotA2/comments/bf49yk/hello_were_the_dev_team_behind_openai_five_we/
-
https://openai.com/blog/openai-five-defeats-dota-2-world-champions/
-
https://web.archive.org/web/20210131091045/https://arena.openai.com/#/results
Link Bibliography
-
https://arxiv.org/abs/2011.12692#tencent
: “Towards Playing Full MOBA Games With Deep Reinforcement Learning”, : -
https://openai.com/blog/science-of-ai/
: “How AI Training Scales”, Sam McCandlish, Jared Kaplan, Dario Amodei: