https://blog.janestreet.com/accelerating-self-play-learning-in-go/

1968

Wu D. J. (2019). Accelerating Self-Play Learning in Go // https://arxiv.org/abs/1902.10565

1969

Boardsize 19x19 - 15 minutes per side (2021) / Computer Go ServerH, Last Update: 2021-03-14 14:43:24 UTC // http://www.yss-aya.com/cgos/19x19/standings.html

1970

Nasu Y. (2018). ƎUИИ: Efficiently Updatable Neural-Network-based Evaluation Functions for Computer Shogi // https://www.apply.computer-shogi.org/wcsc28/appeal/the_end_of_genesis_T.N.K.evolution_turbo_type_D/nnue.pdf

1971

Chess Programming Wiki contributors. (2020, August 31). Stockfish NNUE. In Wikipedia, Chess Programming Wiki contributors. Retrieved 08:00, September 2, 2020, from https://www.chessprogramming.org/Stockfish_NNUE

1972

Poundstone W. (2011). Prisoner's Dilemma. Knopf Doubleday Publishing Group // https://books.google.ru/books?id=twNXXfYVB1UC

1973

Bowling M., Burch N., Johanson M., Tammelin O. (2015). Heads-up Limit Hold’em Poker is Solved / Science, Vol. 347, Iss. 6218, pp. 145—149 // https://doi.org/10.1126/science.1259433

1974

Moravčík M., Schmid M., Burch N., Lisý V., Morrill D., Bard N., Davis T., Waugh K., Johanson M., Bowling M. (2017). DeepStack: Expert-level artificial intelligence in heads-up no-limit poker / Science, Vol. 356, Iss. 6337, pp. 508—513 // https://doi.org/10.1126/science.aam6960

1975

Mets C. (2017). Inside Libratus, the Poker AI That Out-Bluffed the Best Humans / Wired, 02.01.17 // https://www.wired.com/2017/02/libratus/

1976

Rodriguez J. (2019). Inside Pluribus: Facebook’s New AI That Just Mastered the World’s Most Difficult Poker Game / KDnuggets // https://www.kdnuggets.com/2019/08/inside-pluribus-facebooks-new-ai-poker.html

1977

Blair A., Saffidine A. (2019). AI surpasses humans at six-player poker / Science, Vol. 365, Iss. 6456, pp. 864–865 // https://doi.org/10.1126/science.aay7774

1978

Brown N., Lerer A., Gross S., Sandholm T. (2019). Deep Counterfactual Regret Minimization / Proceedings of the 36th International Conference on Machine Learning, PMLR 97:793-802 // http://proceedings.mlr.press/v97/brown19b.html

1979

Ontañón S., Synnaeve G., Uriarte A., Richoux F., Churchill D., Preuss M. (2013). A Survey of Real-Time Strategy Game AI Research and Competition in StarCraft / IEEE Transactions on Computational Intelligence and AI in Games, Vol. 5, No. 4, pp. 293—311 // https://doi.org/10.1109/TCIAIG.2013.2286295

1980

Schulman J., Klimov O., Wolski F., Dhariwal P., Radford A. (2017). Proximal Policy Optimization / OpenAI blog, July 20, 2017 // https://openai.com/blog/openai-baselines-ppo/

1981

Chan B., Tang J., Pondé H., Raiman J., Wolski F., Petrov M., Zhang S., Dennison C., Farhi D., Sidor S., Dębiak P., Pachocki J., Brockman G. (2018). OpenAI Five: Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2 / OpenAI blog // https://openai.com/blog/openai-five/

1982

Matiisen T. (2018). The use of Embeddings in OpenAI Five / Computational Neuroscience Lab, Institute of Computer Science, University of Tartu, September 9, 2018 // https://neuro.cs.ut.ee/the-use-of-embeddings-in-openai-five/

1983

Chan B., Tang J., Pondé H., Raiman J., Wolski F., Petrov M., Zhang S., Dennison C., Farhi D., Sidor S., Dębiak P., Pachocki J., Brockman G. (2018). OpenAI Five: Our team of five neural networks, OpenAI Five, has started to defeat amateur human teams at Dota 2 / OpenAI blog // https://openai.com/blog/openai-five/

1984

OpenAI Five Defeats Dota 2 World Champions (2019) / OpenAI blog, April 15, 2019 // https://openai.com/blog/openai-five-defeats-dota-2-world-champions/

1985

Vinyals O., Babuschkin I., Chung J., Mathieu M., Jaderberg M., Czarnecki W., Dudzik A., Huang A., Georgiev P., Powell R., Ewalds T., Horgan D., Kroiss M., Danihelka I., Agapiou J., Oh J., Dalibard V., Choi D., Sifre L., Sulsky Y., Vezhnevets S., Molloy J., Cai T., Budden D., Paine T., Gulcehre C., Wang Z., Pfaff T., Pohlen T., Yogatama D., Cohen J., McKinney K., Smith O., Schaul T., Lillicrap T., Apps C., Kavukcuoglu K., Hassabis D., Silver D. (2019). AlphaStar: Mastering the Real-Time Strategy Game StarCraft II / DeepMind blog, 24 Jan 2019 // https://deepmind.com/blog/alphastar-mastering-real-time-strategy-game-starcraft-ii/

1986

Wünsch D. (2019) / Twitter // https://twitter.com/liquidtlo/status/1088524496246657030

1987

Solimito S. (2019). Is Alphastar really impressive? // https://medium.com/@stefano.solimito/is-alphastar-really-impressive-31ab02bf0882

1988

Kosker S. (2019). Künstliche Intelligenz gegen Mensch: DeepMind AlphaStar // https://stefankosker.com/alphastar-starcraft-deepmind-kuenstliche-intelligenz/#Prominente_Meinungen_zu_AlphaStar

1989

Lee T. B. (2019). An AI crushed two human pros at StarCraft—but it wasn’t a fair fight / Ars Technica // https://arstechnica.com/gaming/2019/01/an-ai-crushed-two-human-pros-at-starcraft-but-it-wasnt-a-fair-fight/

1990

SoulDrivenOlives (2019). DeepMind's PR regarding Alphastar is unbelievably bafflingg / Reddit // https://www.reddit.com/r/MachineLearning/comments/dr2vir/d_deepminds_pr_regarding_alphastar_is/

1991

Lee T. B. (2019). An AI crushed two human pros at StarCraft—but it wasn’t a fair fight. Superhuman speed and precision helped a StarCraft AI defeat two top players / Ars Technica, 1/30/2019 // https://arstechnica.com/gaming/2019/01/an-ai-crushed-two-human-pros-at-starcraft-but-it-wasnt-a-fair-fight/

1992

u/SoulDrivenOlives (2019).[D] An analysis on how AlphaStar's superhuman speed is a band-aid fix for the limitations of imitation learning / Reddit // https://www.reddit.com/r/MachineLearning/comments/ak3v4i/d_an_analysis_on_how_alphastars_superhuman_speed/

1993

Vinyals O., Babuschkin I., Czarnecki W. M., Mathieu M., Dudzik A., Chung J., Choi D. H., Powell R., Ewalds T., Georgiev P., Oh J., Horgan D., Kroiss M., Danihelka I., Huang A., Sifre L., Cai T., Agapiou J. P., Jaderberg M., Vezhnevets A. S., Leblond R., Pohlen T., Dalibard V., Budden D., Sulsky Y., Molloy J., Paine T. L., Gulcehre C., Wang Z., Pfaff T., Wu Y., Ring R., Yogatama D., Wünsch D., McKinney K., Smith O., Schaul T., Lillicrap T., Kavukcuoglu K., Hassabis D., Apps C., Silver D. (2019). Grandmaster level in StarCraft II using multi-agent reinforcement learning / Nature, Vol. 575, pp. 350–354 (2019) // https://doi.org/10.1038/s41586-019-1724-z

1994

* Пер. М. Лозинского.

1995

Pandya D. A., Dennis B. H., Russell R. D. (2017). A computational fluid dynamics based artificial neural network model to predict solid particle erosion / Wear, Vol. 378—379, 15 May 2017, pp. 198—210 // https://doi.org/10.1016/j.wear.2017.02.028