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As someone who was once semi-pro in dota (4400 MMR, get rekt), it's freaky watching these bots play. It's uncanny. Little things... Like, when the bots are taki

by shawn 8y ago

As someone who was once semi-pro in dota (4400 MMR, get rekt), it's freaky watching these bots play. It's uncanny. Little things... Like, when the bots are taking a tower, one of them will stand in front of the tower and tank the creep wave, so that their creeps do more damage on the tower. They had to learn this. Insta-TPing right when an enemy wastes their stun and can't cancel their TP. Grouping up as 5 at the beginning of the game and pushing into the enemy jungle. Pubs never do this. The most interesting part is that OpenAI appears to be discovering new knowledge in the dota scene. For example, they always take the ranged barracks first, never the melee. This is exactly the opposite of what the pro scene does. Therefore, the smartest pro team should study what the bot is doing and trust that on average it's a better idea to always focus on the ranged barracks first. After all, if it was a bad idea, they probably wouldn't do that. The most hilarious part was when OpenAI paused the game, then resumed it. This illustrates that there is still some unexplainable randomness. Question for OpenAI: Is it more accurate to think of the bots as 5 separate minds, or a single mind controlling 5 heroes? EDIT: By the way, TI is going on right now! https://www.twitch.tv/dota2ti https://www.twitch.tv/dota2ti If you're new to the scene, take a peek. TI is always so high energy -- even if it's hard to follow what's going on, listening to Tobi (the shoutcaster) go nuts during the game is always a highlight. And of course, /r/dota2 has the best memes anywhere, hands-down. https://www.reddit.com/r/DotA2/ https://www.reddit.com/r/DotA2/

apeace 8y ago
> The most hilarious part was when OpenAI paused the game, then resumed it. This illustrates that there is still some unexplainable randomness. I asked about this in a previous thread[1] and received a response that a network blip caused all the players to drop from the game, in which case OpenAI Five was programmed to pause. [1] https://news.ycombinator.com/item?id=17700001 https://news.ycombinator.com/item?id=17700001 EDIT: Fixed thread link.
Benjammer 8y ago
Keep in mind that it's not just pure learning from zero, with these crazy emergent behaviors coming out. There is a fair amount of "coaching" involved. The OpenAI team explained this last year when they revealed the SF mid 1v1 version of their Dota bot. People were astounded that the SF mid was creep blocking at an extremely high level, since wave positioning/management is a very complex behavior/process that doesn't pay off directly right away. The OpenAI team said that they basically taught the SF specifically how to creep block, and they've done this with other behaviors as well, like denying allied creeps, as well as a lot of the meta-level strategic play like warding/vision and item builds/usage.
- antidesitter 8y ago
  Perhaps one day they’ll be able to create the analogue of what AlphaGo Zero (learning from scratch) was to the original AlphaGo (learning from human play). That would be very impressive.
  - Benjammer 8y ago
    Imo, going from OpenAI Five to some kind of OpenAI FiveZero or whatever is like 1000x the amount of progress of AlphaGo to AlphaGo Zero, just based on the complexity of game mechanics and the fact that it's 5v5 and not 1v1.
    - kirillseva 8y ago
      and perfect vs imperfect information - the policy network has to forecast enemy positions and deduce enemy goals. At least in Go you know full game state
- shawn 8y ago
  The thing is, OpenAI are terrible at the game. If they try to coach too much, they'll ruin their chances at beating the top Dota team. They have to let the bot discover its own winning strategies. For example: There are an infinite number of places to place a ward. One way to train the bot is to preselect all possible ward locations, reducing it to 30 or so common ones. Another way is to make an optimization algorithm where the bot focuses on trying to maximize the "strategic vision" (if it's possible to come up with a measure for "strategic") and then let the bot place wards wherever it wants. After hundreds of years of self-play, it should figure out the best place and times. As I write this out, I think you're probably right. There are too many aspects of the game for a purely-random algorithm to be effective... E.g. item builds. But I'm holding out hope that's just because they haven't figured out a good way to encode all dota items into a distance measure. AI has proven over and over that humans aren't so special. And humans know how to adapt to the game. That said, I wish OpenAI would be completely transparent as to what's emergent behavior and what's not. :) Oh, one last interesting thing: Icefrog is going to roll out a big patch after this TI, just like he always does. I wonder how much of the bots' knowledge will transfer over? Or if they'd be better off training from a clean slate?
somebodythere 8y ago
I wonder if AI self-play has any implications for e-sports balance. Could balancing be aided, or at least improved, by ultra-strong AI players, reducing the chance of broken mechanics making it to live?
- jdoliner 8y ago
  Sure seems like it would. A big part of DOTA balance these days is Icefrog (DOTA's BDFL) talking to pro players and about the meta-game and observing pro play to figure out what should change. Having pro-level AIs that you could just set lose to play 100,000 games and then come back to you with statistics about the current patch would probably help a lot. I think it would also raise the level of play that we see from pros. That's what happened with chess bots when they got good enough to be the best human players.
  - shawn 8y ago
    One specific thing that bots could help Icefrog solve: Many games are draft wins, i.e. a >90% chance of winning solely due to the heroes you've picked. There's almost no point in playing these games out for 20-40 minutes; it's boring for everyone involved. This will always exist in dota, but being able to simulate hundreds of years of drafting + games could help reduce this.
    - Benjammer 8y ago
      They're already made great strides into expanding the pro-level meta hero pool over the last several major patches. As an observer it feels like the viable pro hero pool is bigger than ever this year at TI8.
    - trocadero 8y ago
      >Many games are draft wins, i.e. a >90% chance of winning solely due to the heroes you've picked. Can you explain?
      - danielvf 8y ago
jdoliner 8y ago
I'm also very excited about what these bots can tell us about DOTA but I think a certain degree of skepticism is necessary due to the bots not actually having been trained truly tabula rasa. The training contained lots of little "nudges" to reward the bots for things that lead to winning. I.e. there are nudges to get them to go to lane to start, there are nudges to get them to buy the right items. I don't know for sure but I wouldn't be surprised if they kill the ranged barracks first because there's a built in reward for killing barracks that's the same for both melee and ranged barracks but the ranged ones have less health so they value that a little bit higher since it's a more consistent reward than trying to get the melee one. I hope that someday they get to a point where they can truly train from scratch with no human nudges, I'm not sure how much more impressive of an ML result that would be (I'd imagine meaningfully so but I'm not an AI researcher) but it would certainly be a much more interesting result in terms of our understanding of DOTA.
- deleted 8y ago
  [deleted]
- Crespyl 8y ago
  As an admittedly lower-mid level player, when it comes to the ranged barracks at least, I suspect there's actually some value in attacking them over the melee racks simply because the ranged ones do not regenerate their HP, unlike the melee racks. Whenever my team is pushing high-ground and we're not certain we have the time and strength to completely 100-0 the melee racks, we always try to hit the ranged one first, otherwise we'll just get pushed back off the high ground and all the damage we did will just be regenerated, negating the value of all the resources we expended in the push. Ideally, we prefer to take the melee if we know we can, since there's more melee creeps in a wave, the buff is worth more, but if we're not sure we'd rather do damage we know won't evaporate in a few minutes.
  - delusional 8y ago
    That's exactly why pros do it too. If you aren't sure you'll take it, you go for the ranged. The strange thing is that the AI always goes for the ranged, even if it's sure it can take it.
currymj 8y ago
From reading their website, each bot gets its own neural network and its own reward function, so in that sense they are 5 separate agents. When training starts out, the bots solely focus on their own reward functions. This is so they can learn very basic things like how to move around, how to attack, and so on. Over time, the combined team reward function gradually gets weighted more and more heavily, so that teamwork is encouraged.
ufo 8y ago
I heard that the pause was a behavior scripted by the developers, which happened in response to a network connection issue.
- Benjammer 8y ago
  Yeah there's no way they're explicitly integrating pauses-in-time into the winrate calculation... There are so many other central/meta game mechanics that they haven't solved yet, it wouldn't make any sense to incorporate a behavior like strategic pausing.
cc81 8y ago
I think you are putting too much trust in how good OpenAI is at bigger strategy right now. They have a very push focused strategy that fits with the limitations they have put on the game. When OpenAI wins against human opponents it seems mostly be because it is so much better at cooperating and can jump the enemy so quickly. That combined with continued ferrying of regen that would not work in a normal game.
- shawn 8y ago
  Mm, everyone said the same kind of thing last year. It's worth being skeptical, but I'd rather be a true believer and be proven wrong. It seems like betting against technology to say that they can't beat the top dota team in a fair fight within a couple years.
  - Benjammer 8y ago
    I think the argument people used last year is still the same argument though. The 1v1 SF mid was all about computer-precision mechanical skill with hitting creeps and HP management. People said the AI would never be able to match pro-level meta/team strategies. While OpenAI Five is insanely impressive, it's still very glaringly obvious that their range of play styles is very restricted. Many of the pros, even ones who have played against (read: got crushed by) OpenAI Five, still think it's very far away for the bot to out draft a pro team with the full ranked game rules and hero pool. The push heavy death ball strategy is pretty much optimal for the high-precision, perfectly coordinated, mechanical fighting skill the bots have. They get a few kills using the mechanical skill and then they group up and press their advantage as hard as they can. It seems like all the rules/mechanics they are still working on are the more abstract out-of-the-box stuff that evolved to deal with these types of 5-man "teamfight" hero lineups... (warding, game-contextual item builds, courier management, full hero pool with all the "rat" split pushing heroes, etc.)
    - roenxi 8y ago
      > Many of the pros, even ones who have played against (read: got crushed by) OpenAI Five, still think it's very far away for the bot to out draft a pro team with the full ranked game rules and hero pool. Neither AI experts or DotA experts have the necessary background to predict how close anything is to any level of future performance. DotA players are probably the worst to ask, because the AI is already stronger than they are at a subset of the game and they have no insight into how quickly that subset could be generalised into other aspects. OpenAI has a list of something like 7 restrictions. Nobody has any real idea of how quickly these restrictions can be lifted once the OpenAI team has an AI that has mastered the game with those restrictions. Eg, 5 invulnerable couriers is obviously a huge restriction - but once OpenAI knows it gains a benefit by ordering items, how difficult is it to lift that restriction? Nobody knows. Might be easy, might be hard.
eertami 8y ago
>semi-pro in dota >4400 MMR OP is being extremely satirical here by the way. He means he's not great but knows how to play (and definitely not semi-pro) but that context might be lost if you don't play Dota! >Is it more accurate to think of the bots as 5 separate minds, or a single mind controlling 5 heroes? They answered this on the last stream, iirc it's 5 identical clones with the same goals, but not sharing any knowledge, info, or decisions with each other.
- shawn 8y ago
  1v1 me
- hokumguru 8y ago
  I think 4400 MMR places OP in at least Ancient-1 ranking which is approximately the 95th percentile. I'd call that at least semi-pro.
  - PeCaN 8y ago
    4400 isn't even good enough for amateur tournaments.
  - a_humean 8y ago
    Errrrr, at best a dedicated amateur. I'm just 3.5k (I think that's 70th percentile), but I know lots of 4.5k players. To describe the average 4.5k player: Probably has regular groups of people they play with at different skill levels (anywhere from 2.5-5k+), regularly plays battle-cup on Saturdays, maybe played amateur JoinDota league, maybe had a laugh and played open qualifiers only to lose in the first couple rounds, and probably log between between 10-20 hours per week into the game. 4.5k players know how to play to a very good standard and beat the vast majority of other players, but are miles away from the weakest of the professional scene. 4.5k doesn't even appear on the leader boards.
    - bkovacev 8y ago
      I definitely agree with your statement, however.. Solo - the guy that is the captain of Virtus Pro, was at 4k for the longest time. There's more to dota than just mmr. There are players at 5.5-6k range that still do not understand the basics of team play, but are just extremely mechanically gifted and are in great gaming shape.
hcnews 8y ago
The pause was because human players disconnected. They covered that in the post match session. Looks like no one heard that.
IshKebab 8y ago
The AI cannot pause the game. That's not one of its available actions.
- daveguy 8y ago
  Yes. Yes it is.
  - IshKebab 8y ago
    No. No it isn't. Go and look how it works: https://blog.openai.com/openai-five/ https://blog.openai.com/openai-five/
    - daveguy 8y ago
      I'm sorry, I must be missing the part where your link says that pause is not a valid action available to the bots just as it is available to the humans.
zawerf 8y ago
> Question for OpenAI: Is it more accurate to think of the bots as 5 separate minds, or a single mind controlling 5 heroes? They released their architecture: https://www.reddit.com/r/MachineLearning/comments/9533g8/n_openai_five_benchmark_results/e3q0f9l/?context=1 https://www.reddit.com/r/MachineLearning/comments/9533g8/n_o... In the above thread, a reddit user noted that 512 out of the 2048 unit input into the LSTM of each bot is shared (max pooled across players). This means they are telepathically linked and never need to worry about communicating, disagreeing, etc. They know how the others are interpreting their local inputs because it's explicitly shared. So it's not really fair to call it 5 separate minds. You can't really call it a single mind either because if you assume the LSTM is the "mind" (since it's the only place that has memory of previous state), that state isn't read by any other bots.
- shawn 8y ago
  This is fascinating. Thank you!
jlebar 8y ago
> The most hilarious part was when OpenAI paused the game, then resumed it. This illustrates that there is still some unexplainable randomness. This was done by the game coordinator -- the humans' machines DC'ed during the game. https://news.ycombinator.com/item?id=17700233 https://news.ycombinator.com/item?id=17700233
PyroLagus 8y ago
> Therefore, the smartest pro team should study what the bot is doing and trust that on average it's a better idea to always focus on the ranged barracks first. After all, if it was a bad idea, they probably wouldn't do that. This is exactly what is happening with Go right now. Many pros are emulating and learning from AlphaGo (Zero) and are starting to play moves that were always thought to be suboptimal until now.
- shawn 8y ago
  As someone who has no knowledge whatsoever about Go, is there some way I could learn more about what you mention? I’m really curious to see how people are trying to learn from the bot, but I’m not too sure how to find out.

by shawn 8y ago

apeace 8y ago

> The most hilarious part was when OpenAI paused the game, then resumed it. This illustrates that there is still some unexplainable randomness. I asked about this in a previous thread[1] and received a response that a network blip caused all the players to drop from the game, in which case OpenAI Five was programmed to pause. [1] https://news.ycombinator.com/item?id=17700001 https://news.ycombinator.com/item?id=17700001 EDIT: Fixed thread link.

Benjammer 8y ago

Keep in mind that it's not just pure learning from zero, with these crazy emergent behaviors coming out. There is a fair amount of "coaching" involved. The OpenAI team explained this last year when they revealed the SF mid 1v1 version of their Dota bot. People were astounded that the SF mid was creep blocking at an extremely high level, since wave positioning/management is a very complex behavior/process that doesn't pay off directly right away. The OpenAI team said that they basically taught the SF specifically how to creep block, and they've done this with other behaviors as well, like denying allied creeps, as well as a lot of the meta-level strategic play like warding/vision and item builds/usage.

antidesitter 8y ago
Perhaps one day they’ll be able to create the analogue of what AlphaGo Zero (learning from scratch) was to the original AlphaGo (learning from human play). That would be very impressive.
- Benjammer 8y ago
  Imo, going from OpenAI Five to some kind of OpenAI FiveZero or whatever is like 1000x the amount of progress of AlphaGo to AlphaGo Zero, just based on the complexity of game mechanics and the fact that it's 5v5 and not 1v1.
  - kirillseva 8y ago
    and perfect vs imperfect information - the policy network has to forecast enemy positions and deduce enemy goals. At least in Go you know full game state
shawn 8y ago
The thing is, OpenAI are terrible at the game. If they try to coach too much, they'll ruin their chances at beating the top Dota team. They have to let the bot discover its own winning strategies. For example: There are an infinite number of places to place a ward. One way to train the bot is to preselect all possible ward locations, reducing it to 30 or so common ones. Another way is to make an optimization algorithm where the bot focuses on trying to maximize the "strategic vision" (if it's possible to come up with a measure for "strategic") and then let the bot place wards wherever it wants. After hundreds of years of self-play, it should figure out the best place and times. As I write this out, I think you're probably right. There are too many aspects of the game for a purely-random algorithm to be effective... E.g. item builds. But I'm holding out hope that's just because they haven't figured out a good way to encode all dota items into a distance measure. AI has proven over and over that humans aren't so special. And humans know how to adapt to the game. That said, I wish OpenAI would be completely transparent as to what's emergent behavior and what's not. :) Oh, one last interesting thing: Icefrog is going to roll out a big patch after this TI, just like he always does. I wonder how much of the bots' knowledge will transfer over? Or if they'd be better off training from a clean slate?

somebodythere 8y ago

I wonder if AI self-play has any implications for e-sports balance. Could balancing be aided, or at least improved, by ultra-strong AI players, reducing the chance of broken mechanics making it to live?

jdoliner 8y ago
Sure seems like it would. A big part of DOTA balance these days is Icefrog (DOTA's BDFL) talking to pro players and about the meta-game and observing pro play to figure out what should change. Having pro-level AIs that you could just set lose to play 100,000 games and then come back to you with statistics about the current patch would probably help a lot. I think it would also raise the level of play that we see from pros. That's what happened with chess bots when they got good enough to be the best human players.
- shawn 8y ago
  One specific thing that bots could help Icefrog solve: Many games are draft wins, i.e. a >90% chance of winning solely due to the heroes you've picked. There's almost no point in playing these games out for 20-40 minutes; it's boring for everyone involved. This will always exist in dota, but being able to simulate hundreds of years of drafting + games could help reduce this.
  - Benjammer 8y ago
    They're already made great strides into expanding the pro-level meta hero pool over the last several major patches. As an observer it feels like the viable pro hero pool is bigger than ever this year at TI8.
  - trocadero 8y ago
    >Many games are draft wins, i.e. a >90% chance of winning solely due to the heroes you've picked. Can you explain?
    - danielvf 8y ago

jdoliner 8y ago

I'm also very excited about what these bots can tell us about DOTA but I think a certain degree of skepticism is necessary due to the bots not actually having been trained truly tabula rasa. The training contained lots of little "nudges" to reward the bots for things that lead to winning. I.e. there are nudges to get them to go to lane to start, there are nudges to get them to buy the right items. I don't know for sure but I wouldn't be surprised if they kill the ranged barracks first because there's a built in reward for killing barracks that's the same for both melee and ranged barracks but the ranged ones have less health so they value that a little bit higher since it's a more consistent reward than trying to get the melee one. I hope that someday they get to a point where they can truly train from scratch with no human nudges, I'm not sure how much more impressive of an ML result that would be (I'd imagine meaningfully so but I'm not an AI researcher) but it would certainly be a much more interesting result in terms of our understanding of DOTA.

deleted 8y ago
[deleted]
Crespyl 8y ago
As an admittedly lower-mid level player, when it comes to the ranged barracks at least, I suspect there's actually some value in attacking them over the melee racks simply because the ranged ones do not regenerate their HP, unlike the melee racks. Whenever my team is pushing high-ground and we're not certain we have the time and strength to completely 100-0 the melee racks, we always try to hit the ranged one first, otherwise we'll just get pushed back off the high ground and all the damage we did will just be regenerated, negating the value of all the resources we expended in the push. Ideally, we prefer to take the melee if we know we can, since there's more melee creeps in a wave, the buff is worth more, but if we're not sure we'd rather do damage we know won't evaporate in a few minutes.
- delusional 8y ago
  That's exactly why pros do it too. If you aren't sure you'll take it, you go for the ranged. The strange thing is that the AI always goes for the ranged, even if it's sure it can take it.

currymj 8y ago

From reading their website, each bot gets its own neural network and its own reward function, so in that sense they are 5 separate agents. When training starts out, the bots solely focus on their own reward functions. This is so they can learn very basic things like how to move around, how to attack, and so on. Over time, the combined team reward function gradually gets weighted more and more heavily, so that teamwork is encouraged.

ufo 8y ago

I heard that the pause was a behavior scripted by the developers, which happened in response to a network connection issue.

Benjammer 8y ago
Yeah there's no way they're explicitly integrating pauses-in-time into the winrate calculation... There are so many other central/meta game mechanics that they haven't solved yet, it wouldn't make any sense to incorporate a behavior like strategic pausing.

cc81 8y ago

I think you are putting too much trust in how good OpenAI is at bigger strategy right now. They have a very push focused strategy that fits with the limitations they have put on the game. When OpenAI wins against human opponents it seems mostly be because it is so much better at cooperating and can jump the enemy so quickly. That combined with continued ferrying of regen that would not work in a normal game.

shawn 8y ago
Mm, everyone said the same kind of thing last year. It's worth being skeptical, but I'd rather be a true believer and be proven wrong. It seems like betting against technology to say that they can't beat the top dota team in a fair fight within a couple years.
- Benjammer 8y ago
  I think the argument people used last year is still the same argument though. The 1v1 SF mid was all about computer-precision mechanical skill with hitting creeps and HP management. People said the AI would never be able to match pro-level meta/team strategies. While OpenAI Five is insanely impressive, it's still very glaringly obvious that their range of play styles is very restricted. Many of the pros, even ones who have played against (read: got crushed by) OpenAI Five, still think it's very far away for the bot to out draft a pro team with the full ranked game rules and hero pool. The push heavy death ball strategy is pretty much optimal for the high-precision, perfectly coordinated, mechanical fighting skill the bots have. They get a few kills using the mechanical skill and then they group up and press their advantage as hard as they can. It seems like all the rules/mechanics they are still working on are the more abstract out-of-the-box stuff that evolved to deal with these types of 5-man "teamfight" hero lineups... (warding, game-contextual item builds, courier management, full hero pool with all the "rat" split pushing heroes, etc.)
  - roenxi 8y ago
    > Many of the pros, even ones who have played against (read: got crushed by) OpenAI Five, still think it's very far away for the bot to out draft a pro team with the full ranked game rules and hero pool. Neither AI experts or DotA experts have the necessary background to predict how close anything is to any level of future performance. DotA players are probably the worst to ask, because the AI is already stronger than they are at a subset of the game and they have no insight into how quickly that subset could be generalised into other aspects. OpenAI has a list of something like 7 restrictions. Nobody has any real idea of how quickly these restrictions can be lifted once the OpenAI team has an AI that has mastered the game with those restrictions. Eg, 5 invulnerable couriers is obviously a huge restriction - but once OpenAI knows it gains a benefit by ordering items, how difficult is it to lift that restriction? Nobody knows. Might be easy, might be hard.

eertami 8y ago

>semi-pro in dota >4400 MMR OP is being extremely satirical here by the way. He means he's not great but knows how to play (and definitely not semi-pro) but that context might be lost if you don't play Dota! >Is it more accurate to think of the bots as 5 separate minds, or a single mind controlling 5 heroes? They answered this on the last stream, iirc it's 5 identical clones with the same goals, but not sharing any knowledge, info, or decisions with each other.

shawn 8y ago
1v1 me
hokumguru 8y ago
I think 4400 MMR places OP in at least Ancient-1 ranking which is approximately the 95th percentile. I'd call that at least semi-pro.
- PeCaN 8y ago
  4400 isn't even good enough for amateur tournaments.
- a_humean 8y ago
  Errrrr, at best a dedicated amateur. I'm just 3.5k (I think that's 70th percentile), but I know lots of 4.5k players. To describe the average 4.5k player: Probably has regular groups of people they play with at different skill levels (anywhere from 2.5-5k+), regularly plays battle-cup on Saturdays, maybe played amateur JoinDota league, maybe had a laugh and played open qualifiers only to lose in the first couple rounds, and probably log between between 10-20 hours per week into the game. 4.5k players know how to play to a very good standard and beat the vast majority of other players, but are miles away from the weakest of the professional scene. 4.5k doesn't even appear on the leader boards.
  - bkovacev 8y ago
    I definitely agree with your statement, however.. Solo - the guy that is the captain of Virtus Pro, was at 4k for the longest time. There's more to dota than just mmr. There are players at 5.5-6k range that still do not understand the basics of team play, but are just extremely mechanically gifted and are in great gaming shape.

hcnews 8y ago

The pause was because human players disconnected. They covered that in the post match session. Looks like no one heard that.

IshKebab 8y ago

The AI cannot pause the game. That's not one of its available actions.

daveguy 8y ago
Yes. Yes it is.
- IshKebab 8y ago
  No. No it isn't. Go and look how it works: https://blog.openai.com/openai-five/ https://blog.openai.com/openai-five/
  - daveguy 8y ago
    I'm sorry, I must be missing the part where your link says that pause is not a valid action available to the bots just as it is available to the humans.

zawerf 8y ago

> Question for OpenAI: Is it more accurate to think of the bots as 5 separate minds, or a single mind controlling 5 heroes? They released their architecture: https://www.reddit.com/r/MachineLearning/comments/9533g8/n_openai_five_benchmark_results/e3q0f9l/?context=1 https://www.reddit.com/r/MachineLearning/comments/9533g8/n_o... In the above thread, a reddit user noted that 512 out of the 2048 unit input into the LSTM of each bot is shared (max pooled across players). This means they are telepathically linked and never need to worry about communicating, disagreeing, etc. They know how the others are interpreting their local inputs because it's explicitly shared. So it's not really fair to call it 5 separate minds. You can't really call it a single mind either because if you assume the LSTM is the "mind" (since it's the only place that has memory of previous state), that state isn't read by any other bots.

shawn 8y ago
This is fascinating. Thank you!

jlebar 8y ago

> The most hilarious part was when OpenAI paused the game, then resumed it. This illustrates that there is still some unexplainable randomness. This was done by the game coordinator -- the humans' machines DC'ed during the game. https://news.ycombinator.com/item?id=17700233 https://news.ycombinator.com/item?id=17700233

PyroLagus 8y ago

> Therefore, the smartest pro team should study what the bot is doing and trust that on average it's a better idea to always focus on the ranged barracks first. After all, if it was a bad idea, they probably wouldn't do that. This is exactly what is happening with Go right now. Many pros are emulating and learning from AlphaGo (Zero) and are starting to play moves that were always thought to be suboptimal until now.

shawn 8y ago
As someone who has no knowledge whatsoever about Go, is there some way I could learn more about what you mention? I’m really curious to see how people are trying to learn from the bot, but I’m not too sure how to find out.