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AI Beats Four Top Poker Players

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Re: AI Beats Four Top Poker Players

#161

Post by _dps »

T-hawk wrote: post #154
thefalcon wrote: post #146

Earlier quoted context omitted.

Do you mean to say that 100% random RPSAIs have a lower winrate vs humans than RPSAIs that learn and exploit human patterns? Surely a 100% random RPSAI doesn't have a poor win rate against any other RPSAI?

A 100% random RPS AI doesn't have a poor 1-on-1 win rate against any other RPS AI, but it absolutely can have a poor rate of winning tournaments , if "poor" is defined broadly enough. For a tournament that pays cash to the top 10%, most human players would consider anything in the bottom 90% to be poor, which would include a 50% win rate from a random AI. This happens because some entrants aren't 100% random, and the…

To add something, and to clarify (though I don't think you've made any mistake here, but many people misunderstand this subject):

The 33%-each Nash Equilibrium is the mixed strategy Nash Equilibrium of the micro game (i.e. a single round of RPS, averaged over all possible randomizations).

This is in no way the Nash strategy of the tournament game, which is "win the tournament given a pool of unknown participants and a set of rules for whom you face when". You have to add additional assumptions (e.g. that everyone else is going to play the uniform random strategy) in order for uniform random to be the Nash strategy for the tournament game.

If the pool includes players who deviate from the single-round nash equilibrium strategy, there is opportunity to exploit them (and in doing so, open yourself to possible exploitation). This is why pure random play can often perform very poorly at the tournament game.

Re: AI Beats Four Top Poker Players

#162

Post by xapata »

notahacker wrote: post #145
xapata wrote: post #117

Earlier quoted context omitted.

> Poker is solved using a very large game tree You mean Libratus' strategy used a very large game tree. That is not the only strategy. Take a look at research from the University of Alberta [0]. Also, I'm not certain Libratus' strategy can be simplified to "very large game tree" as I haven't seen the paper, yet. While finding a Nash equilibrium means no other player can beat you, it doesn't mean you're going to make…

A Nash equilibrium (or very close approximation thereof) does sound like it would reliably accumulate a chip lead over a very large number of hands against four top level human players though. They'll tend not to have readily exploitable weaknesses and won't be equilibrium players either.

Fair enough. I'd certainly take a conservative, equilibrium approach when playing against a very skilled opponent.

Re: AI Beats Four Top Poker Players

#163

Post by xapata »

T-hawk wrote: post #154
thefalcon wrote: post #146

Earlier quoted context omitted.

Do you mean to say that 100% random RPSAIs have a lower winrate vs humans than RPSAIs that learn and exploit human patterns? Surely a 100% random RPSAI doesn't have a poor win rate against any other RPSAI?

A 100% random RPS AI doesn't have a poor 1-on-1 win rate against any other RPS AI, but it absolutely can have a poor rate of winning tournaments , if "poor" is defined broadly enough. For a tournament that pays cash to the top 10%, most human players would consider anything in the bottom 90% to be poor, which would include a 50% win rate from a random AI. This happens because some entrants aren't 100% random, and the…

Similarly, poker tournaments are only profitable for a professional because so many weak players will register -- the "dead money" so to speak.

Re: AI Beats Four Top Poker Players

#164

Post by DCF »

xapata wrote: post #127
hnkain wrote: post #100

Earlier quoted context omitted.

It would be surprising to me if a completely deterministic strategy wasn't within some very close margin of an optimal strategy. For example, if you think you should raise with JJ 1/3 of the time and call the rest of the time in some spot, then you can raise JcJd and JhJs and call with the other jacks. This can give your opponent slightly more information about your range in some cases (for example, if they hold a J…

Conversely, I'd be very surprised if any deterministic strategy were remotely good. I've played against people with reasonable tight-aggressive strategies who were a bit too deterministic. They get crushed. It'd be far too easy to recognize when they have a good hand and fold and to push them off all their marginal hands.

Which really shows how the game has gotten so much harder. Ten years ago someone playing a fundamentally solid deterministic strategy could print money online. And in many low stakes casino games that is probably still true.

Re: AI Beats Four Top Poker Players

#165

Post by [deleted] »

halflings wrote: post #98
gexla wrote: post #86

Do a search for "long term" in online poker and you'll find that the suggestion for players to determine their level of play based on that "long term" is something like one million hands. That's running 4 tables for full days of poker over a long period of time. For sure it's playing more than 4 players. The probability space of poker is such that 4 competitors isn't going to tell you much. And defining "top" is diff…

From the article: > A poker-playing AI has beaten four human players in a marathon match lasting 20 days. 20 days seems like plenty of time. No ?

[deleted]

Re: AI Beats Four Top Poker Players

#166

Post by fierycatnet »

bcassedy wrote: post #75

Anyone that's interested in reading a more detailed account of the experiment can do so here: http://www.pokerlistings.com/libratus-poker-ai-smokes-humans... The above article spells out some of the details of the competition. The winrate (14.72bb/100) that the AI achieved over the 120k hand sample is almost certainly not due to luck. It is a huge winrate that most pros have to employ strong game selection techniques…

That's pretty impressive, the win rate and amount of hands played. It's certainly not a fluke. At the same time, these 4 pros, I've never heard of them. This AI and organizers should focus on HU specialists. Perhaps even invite players like Negreanu, Ivey, and more recent online pros who've made a fortune. Just don't let Hellmuth to play this machine, it would be a disaster.

Re: AI Beats Four Top Poker Players

#167

Post by ori_b »

brilliantcode wrote: post #82
ori_b wrote: post #76

Earlier quoted context omitted.

Because this is the language of the domain. Much like code is the language of programming. This isn't academic rigor or lingo. This is how things work. To me, your comment reads similarly to "Much like most business people don't spend their time reading code to do the job, I question why such academic rigor is to be demanded by someone who is translating business requirements into database operations".

I think we are after different things. My goal is not to understand the underlying technology at the academic level but just enough to make money by utilizing the people that do, just like any good capitalist. You don't need to be an oil rig worker to understand where the opportunity lies is what I'm saying. It's possible to understand systems from a blackbox point of view and still be able to exploit them. Afterall,…

Then hire someone who understands it.

Re: AI Beats Four Top Poker Players

#168

Post by paulddraper »

DennisP wrote: post #84
andrewprock wrote: post #56

Earlier quoted context omitted.

I'm surprised that Andrew Ng made this claim. The strategy that was built for Libratus' predecessor did not do sophisticated modeling of the opponents, or use new algorithmic principles. Poker is solved using a very large game tree, just as with the other games. The structure of the tree is modified to support the notion of hidden state, but beyond that it is essentially the same as the other games. The structure for…

The no-limit hold'em game tree has over 10^160 states. Even limit poker is too large to solve directly. In 2015, limit poker was essentially solved with a new technique in game theory that allowed them to find a simplified model. http://spectrum.ieee.org/automaton/robotics/artificial-intel...

Chess has a lot of possible states too. (Yeah, I know that's different.)

Heuristics make analysis practical, and well chosen ones make the difference. This isn't to minimize the accomplishment, but rather to say it has strong similarities to other AI games.

Re: AI Beats Four Top Poker Players

#169

Post by jasonwatkinspdx »

algorias wrote: post #81
jasonwatkinspdx wrote: post #19

Earlier quoted context omitted.

> immune to bluffing There's no such thing. An algorithm playing straight hand value based on probabilities is more susceptible to bluffing, not less. And this is no limit, where a single hand can swing all the chips. Any poker AI that isn't a loser is going to have some pretty sophisticated modeling of the opponent.

Having a poker AI that plays deterministic strategies is an obviously terrible idea, for the precise reason you mention. It makes much more sense for the strategy space to be the set of probability distributions over game moves (i.e. mixed strategies). I think that the optimal mixed strategy for each hand is immune to bluffing (over many hands it will have larger expected winnings against a bluffer). If that wasn't t…

I was just making an informal remark, but reading your comment:

> I think that the optimal mixed strategy for each hand is immune to bluffing (over many hands it will have larger expected winnings against a bluffer). If that wasn't the case, there would exist no Bayes-Nash equilibrium for the game, contradicting Nash's theorem.

I believe that's true. I know for sure that heads up limit hold'em has been solved. That said, I think this context is similar to the iterated prisoners dilemma contest. There's certain to be an equilibrium, but what's interesting isn't the perfect strategy in a min/max sense, but rather a slightly suboptimal strategy that can detect and exploit suboptimal behavior in other players. It sounds like you know this area well, perhaps you can shed some light if I'm on the right hunch?

Re: AI Beats Four Top Poker Players

#170

Post by nojvek »

Once this is out, it's going to be have a big impact on online poker games.

They way things are going with AI. You have a good algorithm, you can get rich very quickly by being a one man business with hardware rented in AWS.

Libratus AI player is modelling it's human counterparts and predicting how they think to outsmart them.

When Google started, they got the page rank algorithm and distributed algorithms good enough to run on shitty unreliable cheap computers. They are well on the way to become the world's largest company overtaking Apple someday.

Their ad algorithms already know that I am applying for a house loan and are blasting me with ads every fucking page I visit on the Internet.

I can totally see Google and Facebook personalizing ads per person and taking advantage of the person's vulnerablaties. Like psychologically modelling them to make them click ads and buy random shit. I can see the start of ultimate God algorithms for marketing.

The ability for AI to create drug like experiences for us that we can't stop craving.

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