Bibliography:

  1. ​ ‘model-free RL’ tag

  2. ​ Towards Playing Full MOBA Games with Deep Reinforcement Learning

  3. ​ Mastering Complex Control in MOBA Games with Deep Reinforcement Learning

  4. ​ Dota 2 with Large Scale Deep Reinforcement Learning

  5. ​ OpenAI Five: 2016–2019

  6. ​ Solving Rubik’s Cube with a Robot Hand

  7. ​ Solving Rubik’s Cube with a Robot Hand [blog]

  8. ​ An Empirical Model of Large-Batch Training

  9. ​ How AI Training Scales

  10. ​ Emergent Complexity via Multi-Agent Competition

  11. ​ Proximal Policy Optimization Algorithms

  12. ​ Net2Net: Accelerating Learning via Knowledge Transfer

  13. ​ Dota 2 With Large Scale Deep Reinforcement Learning § Pg11

  14. ​ 2dcf2c6e7f5e36e4ae4e9e3a498d0b2124399287.pdf#page=11&org=openai

  15. ​ OpenAI’s Long Pursuit of Dota 2 Mastery

  16. ​ Solving Rubik’s Cube With a Robot Hand: Perturbations

  17. ​ NVIDIA NTECH 2018—Ilya Sutskever Keynote Talk

  18. ​ 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.

  19. ​ 2018-mccandlish-openai-howaitrainingscales-gradientnoisescale-summary3-scalevsbatchsize.jpg

  20. ​ 2018-mccandlish-openai-howaitrainingscales-gradientnoisescale-summary3-scalevsbatchsize.svg

  21. ​ https://openai.com/blog/more-on-dota-2/

  22. ​ https://openai.com/research/openai-five

  23. ​ https://openai.com/research/openai-five-benchmark-results

  24. ​ https://openai.com/research/the-international-2018-results

  25. ​ https://web.archive.org/web/20210131091045/https://arena.openai.com/#/results

  26. ​ 358abecc97e99abdc9586789b69f04ef179d3ca6.html

  27. ​ https://www.reddit.com/r/DotA2/comments/beyilz/openai_live_updates_thread_lessons_on_how_to_beat/

  28. ​ 3bf917ba3ac3de91e5f6ba42338862063feb2542.html

  29. ​ https://www.reddit.com/r/DotA2/comments/bf49yk/hello_were_the_dev_team_behind_openai_five_we/

  30. ​ c5445cc9da87d2483b551991afaa34dfe5fe4487.html

  31. ​ https://www.reddit.com/r/reinforcementlearning/comments/8tqzvq/openai_dota_update_ppo_lstm_reaches_amateurlevel/

  32. ​ c7d703754b805b730c1fd6e1ca2241758083c4b9.html

  33. ​ https://www.reddit.com/r/reinforcementlearning/comments/94uziv/openai_five_benchmark_crushes_audience_team/

  34. ​ 104c2271e2f5251e4d0c3110bb163a8cf65e2ad3.html

  35. ​ https://www.reddit.com/r/reinforcementlearning/comments/99ieuw/n_first_openai_oa5_dota2_match_begins/

  36. ​ 0cd0c0afcc73dd01e2c44c22926f47861fc8ee02.html

  37. ​ https://www.reddit.com/r/reinforcementlearning/comments/99thy9/openais_oa5_vs_pro_dota2_matches_at_the/

  38. ​ 2683c51c865159eeab3d953ac7dc974a298bc7ac.html

  39. ​ https://www.reddit.com/r/reinforcementlearning/comments/bctqmv/n_openai_five_dota2_finals_match_livestream_has/

  40. ​ 7d5859c9994a3f666729cfa6229165a070a2d6f5.html

  41. ​ Towards Playing Full MOBA Games with Deep Reinforcement Learning

  42. ​ https%253A%252F%252Farxiv.org%252Fabs%252F2011.12692%2523tencent.html

  43. ​ How AI Training Scales

  44. ​ Sam McCandlish

  45. ​ Jared Kaplan

  46. ​ https%253A%252F%252Fopenai.com%252Fresearch%252Fhow-ai-training-scales.html

  47. Wikipedia Bibliography:

    1. ​ Dota 2

    2. ​ OpenAI Five

    3. ​ Bei Shi

    4. ​ Tengfei Shi

    5. ​ Dario Amodei