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eate account log in contents move to sidebar hide top 1 history 2 architecture 3 comparisons with other game ai systems 4 reception 5 references 6 external links toggle the table of contents openai five 11 languages العربية català deutsch español فارسی 日本語 한국어 русский svenska українська 中文 edit links article talk english read edit view history tools tools move to sidebar hide actions read edit view history general what links here related changes upload file permanent link page information cite this page get shortened url switch to legacy parser print export download as pdf printable version in other projects wikidata item appearance move to sidebar hide from wikipedia the free encyclopedia machine learned bot project using the video game dota 2 openai five is a computer program by openai that plays the five on five video game dota 2 its first public appearance occurred in 2017 where it was demonstrated in a live one on one game against the professional player dendi who lost to it the following year the system had advanced to the point of performing as a full team of five and began playing against and showing the capability to defeat professional teams by choosing a game as complex as dota 2 to study machine learning openai thought they could more accurately capture the unpredictability and continuity seen in the real world thus constructing more general problem solving systems the algorithms and code used by openai five were eventually borrowed by another neural network in development by the company one which controlled a physical robotic hand openai five has been compared to other similar cases of artificial intelligence ai playing against and defeating humans such as alphastar in the video game starcraft ii alphago in the board game go deep blue in chess and watson on the television game show jeopardy history edit development on the algorithms used for the bots began in november 2016 openai decided to use dota 2 a competitive five on five video game as a base due to it being popular on the live streaming platform twitch having native support for linux and had an application programming interface api available 1 before becoming a team of five the first public demonstration occurred at the international 2017 in august the annual premiere championship tournament for the game where dendi a ukrainian professional player lost against an openai bot in a live one on one matchup 2 3 after the match cto greg brockman explained that the bot had learned by playing against itself for two weeks of real time and that the learning software was a step in the direction of creating software that can handle complex tasks like being a surgeon 4 5 openai used a methodology called reinforcement learning as the bots learn over time by playing against itself hundreds of times a day for months in which they are rewarded for actions such as killing an enemy and destroying towers 6 7 8 by june 2018 the ability of the bots expanded to play together as a full team of five and were able to defeat teams of amateur and semi professional players 9 6 10 11 at the international 2018 openai five played in two games against professional teams one against the brazilian based pain gaming and the other against an all star team of former chinese players 12 13 14 although the bots lost both matches openai still considered it a successful venture stating that playing against some of the best players in dota 2 allowed them to analyze and adjust their algorithms for future games 15 the bots final public demonstration occurred in april 2019 where they won a best of three series against the international 2018 champions og at a live event in san francisco 16 a four day online event to play against the bots open to the public occurred the same month 17 there the bots played in 42 729 public games winning 99 4 of those games 18 architecture edit each openai five bot is a neural network containing a single layer with a 4096 unit 19 lstm that observes the current game state extracted from the dota developer s api the neural network conducts actions via numerous possible action heads no human data involved and every head has meaning for instance the number of ticks to delay an action what action to select the x or y coordinate of this action in a grid around the unit in addition action heads are computed independently the ai system observes the world as a list of 20 000 numbers and takes an action by conducting a list of eight enumeration values also it selects different actions and targets to understand how to encode every action and observe the world 20 openai five has been developed as a general purpose reinforcement learning training system on the rapid infrastructure rapid consists of two layers it spins up thousands of machines and helps them talk to each other and a second layer runs software by 2018 openai five had played around 180 years worth of games in reinforcement learning running on 256 gpus and 128 000 cpu cores 21 using proximal policy optimization a policy gradient method 20 22 comparison chart openai 1v1 bot 2017 openai five 2018 cpus 60 000 cpu cores on microsoft azure 128 000 pre emptible cpu cores on the google cloud platform gcp gpus 256 k80 gpus on azure 256 p100 gpus on the gcp experience collected 300 years per day 180 years per day size of observation 3 3kb 36 8kb observations per second of gameplay 10 7 5 batch size 8 388 608 observations 1 048 576 observations batches per minute 20 60 comparisons with other game ai systems edit prior to openai five other ai versus human experiments and systems have been successfully used before such as jeopardy with watson chess with deep blue and go with alphago 23 24 25 in comparison with other games that have used ai systems to play against human players dota 2 differs as explained below 20 long run view the bots run at 30 frames per second for an average match time of 45 minutes which results in 80 000 ticks per game openai five observes every fourth frame generating 20 000 moves by comparison chess usually ends before 40 moves while go ends before 150 moves partially observed state of the game players and their allies can only see the map directly around them the rest of it is covered in a fog of war which hides enemies units and their movements thus playing dota 2 requires making inferences based on this incomplete data as well as predicting what their opponent could be doing at the same time by comparison chess and go are full information games as they do not hide elements from the opposing player 26 continuous action space each playable character in a dota 2 game known as a hero can take dozens of actions that target either another unit or a position the openai five developers allow the space into 170 000 possible actions per hero without counting the perpetual aspects of the game there are an average of 1 000 valid actions each tick by comparison the average number of actions in chess is 35 and 250 in go continuous observation space dota 2 is played on a large map with ten heroes five on each team along with dozens of buildings and non player character npc units the openai system observes the state of a game through developers bot api as 20 000 numbers that constitute all information a human is allowed to get access to a chess board is represented as about 70 lists whereas a go board has about 400 enumerations reception edit openai five have received acknowledgement from the ai tech and video game community at large microsoft founder bill gates called it a big deal as their victories required teamwork and collaboration 8 27 chess champion garry kasparov who lost against the deep blue ai in 1997 stated that despite their losing performance at the international 2018 the bots would eventually get there and sooner than expected 28 in a conversation with mit technology review ai experts also considered openai five system as a significant achievement as they noted that dota 2 was an extremely complicated game so even beating non professional players was impressive 26 pc gamer wrote that their wins against professional players was a significant event in machine learning 29 in contrast motherboard wrote that the victory was basically cheating due to the simplified hero pools on both sides as well as the fact that bots were given direct access to the api as opposed to using computer vision to interpret pixels on the screen 30 the verge wrote that the bots were evidence that the company s approach to reinforcement learning and its general philosophy about ai was yielding milestones 17 in 2019 deepmind unveiled a similar bot for starcraft ii alphastar like openai five alphastar used reinforcement learning and self play the verge reported that the goal with this type of ai research is not just to crush humans in various games just to prove it can be done instead it s to prove that with enough time effort and resources sophisticated ai software can best humans at virtually any competitive cognitive challenge be it a board game or a modern video game they added that the deepmind and openai victories were also a testament to the power of certain uses of reinforcement learning 31 it was openai s hope that the technology could have applications outside of the digital realm in 2018 they were able to reuse the same reinforcement learning algorithms and training code from openai five for dactyl a human like robot hand with a neural network built to manipulate physical objects 32 in 2019 dactyl solved the rubik s cube 33 references edit openai openai five openai com five archived from the original on 1 september 2018 retrieved 10 october 2018 savov vlad 14 august 2017 my favorite game has been invaded by killer ai bots and elon musk hype the verge archived from the original on 26 june 2018 retrieved 25 june 2018 frank blair hanley openai s bot beats top dota 2 player so badly that he quits venture beat archived from the original on 12 august 2017 retrieved 12 august 2017 openai 11 august 2017 dota 2 blog openai com archived from the original on 11 august 2017 retrieved 12 august 2017 openai 16 august 2017 more on dota 2 blog openai com archived from the original on 16 august 2017 retrieved 16 august 2017 1 2 simonite tom 25 june 2018 can bots outwit humans in one of the biggest esports games wired archived from the original on 25 june 2018 retrieved 25 june 2018 kahn jeremy 25 june 2018 a bot backed by elon musk has made an ai breakthrough in video game world bloomberg com archived from the original on 27 june 2018 retrieved 27 june 2018 1 2 bill gates says gamer bots from elon musk backed nonprofit are huge milestone in a i cnbc 28 june 2018 archived from the original on 28 june 2018 retrieved 28 june 2018 openai 18 july 2018 openai five benchmark blog openai com archived from the original on 26 august 2018 retrieved 25 august 2018 vincent james 25 june 2018 ai bots trained for 180 years a day to beat humans at dota 2 the verge archived from the original on 25 june 2018 retrieved 25 june 2018 savov vlad 6 august 2018 the openai dota 2 bots just defeated a team of former pros the verge archived from the original on 7 august 2018 retrieved 7 august 2018 hutson matthew 31 july 2019 just months old a game playing a i takes on the world medium retrieved 12 june 2025 simonite tom pro gamers fend off elon musk backed ai bots for now wired archived from the original on 24 august 2018 retrieved 25 august 2018 quach katyanna game over machines humans defeat openai bots once again at video games olympics the register archived from the original on 25 august 2018 retrieved 25 august 2018 openai 24 august 2018 the international 2018 results blog openai com archived from the original on 24 august 2018 retrieved 25 august 2018 wiggers kyle 13 april 2019 openai five defeats professional dota 2 team twice venture beat archived from the original on 13 april 2019 retrieved 13 april 2019 1 2 statt nick 13 april 2019 openai s dota 2 ai steamrolls world champion e sports team with back to back victories the verge vox media archived from the original on 15 april 2019 retrieved 15 april 2019 wiggers kyle 22 april 2019 openai s dota 2 bot defeated 99 4 of players in public matches venture beat archived from the original on 11 july 2019 retrieved 22 april 2019 dota 2 with large scale deep reinforcement learning pdf openai archived pdf from the original on 26 september 2024 retrieved 29 september 2024 1 2 3 openai 25 june 2018 openai five blog openai com archived from the original on 25 june 2018 retrieved 25 june 2018 why are ai researchers so obsessed with games quartz 4 august 2018 archived from the original on 4 august 2018 retrieved 4 august 2018 schulman john wolski filip dhariwal prafulla radford alec klimov oleg 2017 proximal policy optimization algorithms arxiv 1707 06347 cs lg gabbatt adam 17 february 2011 ibm computer watson wins jeopardy clash the guardian archived from the original on 21 september 2013 retrieved 17 february 2011 chess grandmaster garry kasparov on what happens when machines reach the level that is impossible for humans to compete business insider archived from the original on 29 december 2017 retrieved 29 december 2017 deepmind s go playing ai doesn t need human help to beat us anymore verge 18 october 2017 archived from the original on 18 october 2017 retrieved 18 october 2017 1 2 knight will 25 june 2018 a team of ai algorithms just crushed humans in a complex computer game mit tech review retrieved 25 june 2018 bill gates hails huge milestone for ai as bots work in a team to destroy humans at video game dota 2 business insider archived from the original on 27 june 2018 retrieved 27 june 2018 garry kasparov s twitter 24 august 2018 retrieved 24 august 2018 park morgan 11 august 2018 how the openai five tore apart a team of dota 2 pros pc gamer retrieved 25 may 2020 gault matthew 17 august 2018 openai is beating humans at dota 2 because it s basically cheating vice retrieved 25 may 2020 statt nick 30 october 2019 deepmind s starcraft 2 ai is now better than 99 8 percent of all human players the verge retrieved 25 may 2020 openai andrychowicz marcin baker bowen chociej maciek józefowicz rafał mcgrew bob pachocki jakub petron arthur plappert matthias powell glenn ray alex schneider jonas sidor szymon tobin josh welinder peter weng lilian zaremba wojciech 2019 learning dexterous in hand manipulation arxiv 1808 00177v5 cs lg openai akkaya ilge andrychowicz marcin chociej maciek litwin mateusz mcgrew bob petron arthur paino alex plappert matthias powell glenn ribas raphael 2019 solving rubik s cube with a robot hand arxiv 1910 07113v1 cs lg external links edit video games portal official website official blog v t e dota valve games defense of the ancients dota 2 artifact dota underlords esports the international 2014 2015 2016 2017 2018 2019 2021 2022 2023 2024 2025 notable teams alliance aurora gaming cdec gaming evil geniuses invictus gaming mineski newbee natus vincere og psg lgd team falcons 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