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As someone who plays Dota, the matches were a clear demonstration of sloppy snowballing and brute force cheesing. Coordination 'appears' to be beyond human leve

by iotb 8y ago

As someone who plays Dota, the matches were a clear demonstration of sloppy snowballing and brute force cheesing. Coordination 'appears' to be beyond human level because the bots are collectively synced on a team goal value. If a true 'pro' or pro team was allowed to observe and play multiple games against this bot, I'm more than certain one could find an exploit of such an unintelligent mathematical approach to action selection at the individual or group level. In fact, this would be what you would use dark seer strategically for or a whole host of other characters and functionality that is currently banned. Not everything can be calculated especially when tricks are intentionally done to throw a bot off. > I am not sure how such coordinations are modeled in dnn, which itself seems the most valuable from this research. There's a tuned group/individual driver function centered on various calculations. This is not actually a valuable part of the research as its dynamic and game dependent and can't cover all of the possibilities thus why someone broke their 1v1 bot (corner case) > In general I think with this show match, it pretty much sealed the doom of human players in dota2. If you are indeed a player and have viewed that many hours of dota2, I question the nature of such a comment. A great player wouldn't look to see how to 'beat' their bot, as it is a bot w/ no intelligence, the strategy would instead be to try to break it and shove it into corner cases. It's not playing the full range of characters that were intended to disrupt cheesy snowballing so I wonder why you're making such an optimistic statement .. being that you claim you have watch so many dota matches. Do you play much yourself? Maybe that would change your opinion. > As it shows that the general approach is scalable and capable to handle the problem itself. As from laning to team fight, and item building, the AI did not show weakness at all. I'm starting to see a pattern with your commentary. The gameplay look like your typical "south" players. Hardly anything impressive : Aggressive boneheaded tower diving and aggressive and cheesy snowballing.. If you can last past 30min, you outwit and outplay such people in the mid/late game. > superior to humans > superior to humans > superior to humans More than 50% of the Dota 2 dynamics aren't even present and are restricted at the moment. Are you getting paid for this post?

justicezyx 8y ago
> A great player wouldn't look to see how to 'beat' their bot, as it is a bot w/ no intelligence, the strategy would instead be to try to break it and shove it into corner cases. I cannot see any differences between "beating opponents" vs. "break it and shove it into corner cases", that's always how dota games are played out. Unless we formed different views on how Dota is played through our thousands of time watching games (I sensed from your statement that you had similar gaming experiences :) )
- iotb 8y ago
  I have thousands of hours logged playing various Dota variants. I rarely watch as it's not a good way to retain skills or understand what's going on. If you play enough, you should understand exactly what I'm saying. I watch on rare occasions to get exposed to something I haven't thought of or tried but that's about it. Beating an opponent especially a good one is far different that 'breaking a bot'. What I mean by 'breaking the bot' is literally doing things to confuse an unintelligent mathematical algorithm into constant miscalculations and mis-predictions and for bonus points for finding a bug in the way it individually or collectively performs actions/interprets data. It's how their first 1v1 bot is defeated. This doesn't occur to a human being because we have intelligence and aren't just optimization algorithms purring along using game state data. This is what Strong AI is centered on.
make3 8y ago
"not everything can be calculated" that's not how neural networks work. it develops a super complex model of the game by itself by playing a huge amount of game, and optimizing to progressively learn to win more
nopinsight 8y ago
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.)
- justicezyx 8y ago
  My feeling is that humans are not adaptive to changing game flows either. 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.

by iotb 8y ago

justicezyx 8y ago

> A great player wouldn't look to see how to 'beat' their bot, as it is a bot w/ no intelligence, the strategy would instead be to try to break it and shove it into corner cases. I cannot see any differences between "beating opponents" vs. "break it and shove it into corner cases", that's always how dota games are played out. Unless we formed different views on how Dota is played through our thousands of time watching games (I sensed from your statement that you had similar gaming experiences :) )

iotb 8y ago
I have thousands of hours logged playing various Dota variants. I rarely watch as it's not a good way to retain skills or understand what's going on. If you play enough, you should understand exactly what I'm saying. I watch on rare occasions to get exposed to something I haven't thought of or tried but that's about it. Beating an opponent especially a good one is far different that 'breaking a bot'. What I mean by 'breaking the bot' is literally doing things to confuse an unintelligent mathematical algorithm into constant miscalculations and mis-predictions and for bonus points for finding a bug in the way it individually or collectively performs actions/interprets data. It's how their first 1v1 bot is defeated. This doesn't occur to a human being because we have intelligence and aren't just optimization algorithms purring along using game state data. This is what Strong AI is centered on.

make3 8y ago

"not everything can be calculated" that's not how neural networks work. it develops a super complex model of the game by itself by playing a huge amount of game, and optimizing to progressively learn to win more

nopinsight 8y ago

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.)

justicezyx 8y ago
My feeling is that humans are not adaptive to changing game flows either. 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.