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by nopinsight
2879 days ago
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Your point regarding the fact that the bots ‘may’ not be adaptive to surprising strategies is a good one. We do not know for sure in the case of OpenAI Five as there are too few public games to look at. AlphaGo Lee (the version which won 4-1 against Lee Sedol) did seem to get thrown off track by Lee’s surprising move and lost that game. However, AlphaGo Zero, which is based on some of the same principles/sets of algorithms, were much stronger than AlphaGo Lee (More than 3 stones according to DeepMind. Three stones is about a difference between top pros and top amateurs/beginning pros.) and seemed like it would be insusceptible to any surprises thrown its way from human experts. The difference was that AlphaGo Lee learned from play records of human Go experts while AlphaGo Zero did not and only learned via self-playing. Dota 2 is clearly more complex than Go but if the same principles apply then an AI trained from pure self-plays would be adaptive to most surprises in the domain, if the system had explored those edge cases before (which depends in turn on how the self-plays were conducted during training). (As a side note: OpenAI Five probably chose the “simple-minded” snowballing-cheesing strategy because it determined from extensive experience that the strategy is most likely to yield a win given its capabilities (which are advantageous to humans in some respect like instantaneous global information observation, great coordination, consistency, etc). This is very different from the reason some human players choose the strategy. Perhaps precisely because Five bots don’t get sloppy that the strategy is so effective for them.) |
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Most pro games are played with a strategy that is settled once draft is finalized. If the strategy turns out not working, Humans did not show noticeably different adaptivity.
Occasionally, a versatile team can transition from a late-game oriented line up to play a split push game. But usually such transition is based on a suiting draft, which requires the team members to be versatile in playing their heroes in slightly different styles; and a well-oiled team coordination to transition from one to another style.
> the “simple-minded” snowballing-cheesing strategy
In the show matches, there is no cheesing. It's plain team fight + push; the AIs executed the plan with ruthless precisions.
TBH, a typical pub game is best described as strategy-less game play. And pro games probably have 3 styles of play:
- Team fight
- Stick-together push
- Split push
The most close team that shows vastly better versatility is Wings gaming, which pretty much run any lineups they feel fitting.
Sadly the team disbanded after TI6, otherwise, their match against with OpenAI would be the most interesting thing I can imagine.