[HN Gopher] Professional poker players know the optimal strategy...
___________________________________________________________________
Professional poker players know the optimal strategy but don't
always use it
Author : alexahn
Score : 120 points
Date : 2024-07-19 03:17 UTC (19 hours ago)
(HTM) web link (www.scientificamerican.com)
(TXT) w3m dump (www.scientificamerican.com)
| mxwsn wrote:
| Essentially all AI work I've seen in games aims for game theory
| optimal play, but I think it could be really interesting to
| consider AI for exploitative play. Does this exist? Poker with
| imperfect information, human pressure and fallibility means that
| players will inevitably stray from Nash equilibrium. The decision
| on how to exploit without getting exploited back oneself seems
| really fascinating to consider from an AI perspective. At a
| glance it seems to require considering how others view you..
| raincole wrote:
| > Imperfect information, human pressure... inevitably stray
| from Nash equilibrium
|
| Human pressure yes. Imperfect information no.
|
| When we talk about Nash equilibrium for a game like poker, it's
| already based on imperfect information.
| mxwsn wrote:
| Ah right, thanks
| waprin wrote:
| Within solvers, you can do something called "node locking",
| which means you "lock" a tree in the game node to play a fixed
| strategy. You would typically lock it to play as you suspect
| your opponent plays. This lets the solver calculate the optimal
| exploitative solution against your specific oppoents.
|
| Piosolver, the first public solver and the one mentioned in the
| article, has this feature.
|
| However, what often happens is if you lock one node, then
| several other nodes in the game tree over-adjust in drastic
| ways, forcing you to lock all of the, which may be infeasiable.
| As a result, Piosolver recently introduced "incentives", which
| gives a player in the game an additional incentive to take a
| certain action . For example, you may suspect your opponent
| calls too much and doesn't raise enough, so you can just set
| that incentive and it will include that in its math equations
| and give you something similar to an exploitative solution with
| a much simpler UX.
|
| This feature was literally just introduced a few months ago so
| it's still very much an active area of research, both for game
| theory nerds, and people trying to use the game theory nerd
| research to make money !
| Buttons840 wrote:
| I want to see strong AI used in video games, especially
| strategy games. People often retort that strong AI is not
| fun; it's too challenging and that's not what players want.
| But once we have a strong AI we can adjust its goal function
| in fun ways. What you're describing is effectively the same,
| and it's the first time I've seen this used in a strong AI.
| currymj wrote:
| GT Sophy is now a permanent feature in Gran Turismo and
| basically does this!
| dontlikeyoueith wrote:
| In essence, you need strong (probably unbeatable) game AI
| in order to make more interesting weak (beatable but
| challenging and fun) game AI.
| asdasdsddd wrote:
| I think it'd be interesting to see if an AI with visual input
| playing exploitatively can out perform AI playing GTO. In doing
| so, we can measure the effect of visual tells.
| tialaramex wrote:
| You mean, can the exploitative strategy take money from fish
| faster? Yes. But it doesn't need to care about visual tells.
|
| The point of the optimal strategy is that it's unexploitable
| so you can disregard the other player's actions (in the game
| or outside it) entirely.
|
| All exploitative strategies are in turn exploitable.
| bubblyworld wrote:
| I think you have to be careful with saying stuff like
| "optimal strategies are unexploitable", because it usually
| means "unexploitable in a particular game theory sense".
|
| Whether the assumptions of the Nash equilibrium (or any of
| the others) make sense for your situation in a game of
| poker is an empirical question, right? It's not a given
| that playing a NE means you'll be "perfect" in the human
| sense of the word, or that you'll get the best possible
| outcome.
|
| The best superhuman poker AIs at the moment do not play
| equilibriums either, for instance.
| tialaramex wrote:
| I agree that because of, for example rake or table fees
| for cash games or competition structure for tournament in
| practice a game theoretically optimal choice may not be
| the right choice in practical play.
|
| However the situation with an AI powered competitor which
| uses exploitative play is identical to a human, the GTO
| play will gradually take their chips at no risk.
|
| It's not that they're optimal but that they've chosen
| _not_ to be optimal and so that 's why they lose money
| against GTO.
|
| The AI is at least unemotional about this, humans with a
| "system" easily get tilted by GTO play and throw
| tantrums. How can it get there with KToff? What kind of
| idiot bluffs here with no clubs? Well the answer will
| usually be the one that's taking all your chips, be
| better. Humans used to seeing exploitable patterns in the
| play of other humans may mistake ordinary noise in the
| game for exploitable play in a GTO strategy and then get
| really angry when it's a mirage.
| bubblyworld wrote:
| Right, I see what you're saying, but this is what I'm
| disputing - in two player games, what you wrote is true,
| but those properties of Nash equilibria don't generalise.
|
| When there are more players, there can be multiple Nash
| equilibria, and (unlike the two player case) combinations
| of equilibrium strategies may no longer be an equilibrium
| strategy. So it's no longer true that you cannot be
| exploited, because that depends on other player's
| strategies too, and you cannot control those.
|
| (See this paper for instance: https://webdocs.cs.ualberta
| .ca/~games/poker/publications/AAM...)
| tialaramex wrote:
| Yes, I agree that more players makes the theory at least
| extremely difficult and perhaps imponderable. That paper
| was interesting, thanks
| bubblyworld wrote:
| Yes, this exists! Look up models based on counterfactual regret
| minimisation - they learn to exploit regularities in their
| opponents play, and often stray from the GTO play when it makes
| sense. I believe they have beaten poker professionals in
| thousands-of-hands playoffs but I may be misremembering.
| phreeza wrote:
| The obvious follow up question: are there methods in use to
| bait such models into suboptimal play and then switch play
| style to exploit that?
| codethief wrote:
| > I believe they have beaten poker professionals in
| thousands-of-hands playoffs
|
| I really don't know anything about poker AIs but could it be
| you are referring to Libratus and/or Pluribus[0]?
|
| [0]: https://noambrown.github.io/
| bubblyworld wrote:
| To be honest I didn't have a specific AI in mind, more the
| technique, but it sounds like these ones also use a variant
| of CFRM.
| energy123 wrote:
| I do not believe these attempt to exploit regularities.
| currymj wrote:
| no, CFR is mainly just a way of computing Nash equilibria and
| (although in some sense it is an online, iterative algorithm)
| would typically be used to precompute Nash strategies, not
| update them in real time. real poker playing systems augment
| the CFR strategies with some real-time solving, but just to
| get even closer to Nash at the end of a hand.
|
| on top of this, you could think about augmenting these
| systems to exploit weaknesses in opponent strategies. there
| is some work on this, but I don't think it's done much. The
| famous systems that played against professionals don't use
| it, they just try to get as close to GTO as possible and wait
| for opponents to screw up.
| genewitch wrote:
| it took me a while to track this down last month:
| https://codegolf.stackexchange.com/questions/tagged/king-of-...
| there's also cops and robbers and at least one other "all AI
| compete against eachother" with the submitter usually making
| the first couple of "naive" bots.
| ggjkvcxddd wrote:
| An AI that plays a fixed exploitative strategy will end up
| getting figured out relatively quickly and counter exploited
| pretty hard. This actually happens in real life sometimes when
| people attempt to deploy poker bots online.
|
| Any exploitative AI also needs the ability to adjust in real
| time to a different exploitative strategy, which also needs to
| be not easily predictable, etc.
| brigadier132 wrote:
| "Game theory optimal" (as poker players like to call it) is not
| really the optimal strategy. It's the nash equilibrium strategy
| _assuming_ the other players are also playing a nash equilibrium
| strategy. As soon as one player deviates from the nash
| equilibrium it 's not optimal anymore :).
|
| It's interesting how this affects play. If a player is bluffing
| slightly less than they should be, the adjustment is drastic, you
| should actually never call with hands that do not beat their
| value hands. If they are bluffing optimally, you are supposed to
| call using what is known as "minimum defense frequency". What's
| interesting about this is the minimum defense frequency is based
| on what the strongest hands you can possibly have in that
| situation are and the opponents possible hands do not even factor
| into it. It's required to prevent your opponent from bluffing
| with any two cards profitably.
|
| To do the math, if you are on the river and the opponent bets 100
| into 100, for this to be profitable for them they need to win 50%
| of the time or more. If your opponent is bluffing optimally, you
| need to call with 50% of the strongest hands you have in that
| specific situation (if you don't know what hands you have in a
| specific situation that's a problem) and sometimes they can be
| dogshit like King high.
|
| But, very important to note, very few players actually bluff
| enough and if they bluff less than they should you should only
| ever call when your hand actually beats their range of possible
| value hands. (value vs bluff is kind of a difficult thing to
| communicate, generally it's value if you want your opponent to
| call)
|
| Most players don't bluff enough as a result of most players
| calling too much! When they call too much you should obviously
| not bluff! This leads to very boring games of poker.
| waprin wrote:
| > What's interesting about this is the minimum defense
| frequency is based on what the strongest hands you can possibly
| have in that situation are and the opponents possible hands do
| not even factor into it.
|
| This is actually not quite true. MDF is purely a formula based
| on pot size and the bet size (pot size / pot size + bet size).
| The fact that it doesn't consider various ranges is why it's
| not really useful - it was a simplified formula used to try to
| understand the game before solvers existed.
|
| There are situations where your opponent can bet any two cards
| profitably and you do have to fold - imagine they bet the size
| of the pot, but have the better hand 99% of the time, you're
| simply forced to let them bluff the 1% of the time they're
| bluffing. MDF is a pre-solver concept and not an especially
| useful concept in the modern game.
| brigadier132 wrote:
| I'm pretty sure mdf applies to rivers when you are last to
| act. I'd be interested in being proven wrong however if you
| have solver output that shows it. I remember studying solver
| output and seeing it in action.
|
| I know that before the river there are range advantages that
| make defending mdf a losing play.
| waprin wrote:
| What's true is that equilibrium strategies typically
| converge to solutions where the better makes the caller
| indifferent between calling and folding. In the toy example
| I've given where the betters range is so strong, the caller
| should always fold, the better now has an incentive to add
| more bluffs to the range to take advantage of the folds.
| Then the caller will want to call more. This might converge
| to the MDF which might be what you're suggesting, assuming
| we started with ranges that could have enough bluffs given
| the runouts.
|
| If you open up the solver, and give one player only Ace-Ace
| as their starting range, and the other player a pair of
| twos, and the board Ace-Ace-Three-Three-Three, then the
| pair of twos will fold 100% on river and will not call at
| MDF.
| brigadier132 wrote:
| You are absolutely right! Haha damn back to the drawing
| board
| Raidion wrote:
| I think another way to say this is that MDF works only if
| you're in a spot where you have hands that are strong
| enough to call. If you play every hand, and you see every
| river in that 100into100 situation, you shouldn't call
| with 50% of your hands because your hand range is too
| wide for that to be profitable.
|
| So you can't make a ton of mistakes say "MDF" and call
| off, you have to have done the right things in previous
| streets to end up with a range that can call at MDF. That
| range (and those street actions) require an understanding
| of GTO (and the adjustments needed when someone isn't
| playing GTO).
| Lordarminius wrote:
| This is why I swear by chess. Bluffing has minimal value
| against best play.
| tucnak wrote:
| Not in blitz it doesn't
| jurassicfoxy wrote:
| That being said, when Super GMs play a bad move against a
| lower rated GM, they quite often gets a pass. They don't
| capitalize, simply because they assume the move is excellent.
| ajkjk wrote:
| Chess manages in practice to be a game of imperfect
| information, like poker. Obviously it is explicitly a game of
| perfect information on the board, but the hidden information
| is all psychological. For instance: "do they actually know
| this opening/endgame? do they see a tactic? did they take a
| long time because they calculated that it's a good move, or
| are they bluffing by making it seem like they calculated
| something? are they actually better than me or just acting
| like they are?". etc.
|
| It's true that "bluffing has minimal value against best
| play", but no human is in that situation. Even super-GMs will
| play "bluffs" if they are behind (or playing a lower-rated
| player and sure they can recover later. or just for fun if
| the stakes are low).
|
| And that's not even mentioning optimal strategy under time
| pressure. For instance some of the Lichess tournaments are
| structured such that winning _fast_ is more valuable than
| winning slowly because the resulting score comes from how
| many wins you can get in (or in other cases, how big of a
| streak you can get). So people will play in a way that
| optimizes for winning quickly by taking big bets / bluffing
| / creating chaos with un-calculated gambits, especially if
| they have a good reason to believe they're better than their
| opponents.
| hibikir wrote:
| But every serious chess game is a matter of time allocation.
| The best players in the world are unable to calculate as much
| as they want in every position: Ultimately there is bluffing
| and risk taking. See the last game of the last candidates,
| where both Fabi and Ian have to win to get into a playoff,
| and they get themselves into extremely complicated positions,
| where accurate play just takes too long for a human. At an 8
| hour time limit, the game is very different than at the time
| the players actually had, as ultimately Fabi just couldn't
| calculate to the end on every position he knew was key.
|
| It wasn't the most accurate game of the tournament, but the
| most instructive as far as the psychology of chess goes
| tialaramex wrote:
| In the narrow range of poker variants (all heads up, ie only
| two players, not full ring like all but the last few hands of
| the Main Event) where it's meaningful to talk about a truly
| optimal game, any theoretical optimal play will still take
| money from all humans it's just slower (but with zero risk)
| compared to exploitative play.
|
| In live cash games, speed matters, you want to take all the
| available chips before the fish realise they're out-matched,
| but to protect yourself the optimal play, if you could memorise
| it, would be safer because it can't be exploited yet it does
| take the opponent's chips.
|
| Poker players are gamblers. So "safer" isn't really what they
| were going for anyway.
| brigadier132 wrote:
| More important than speed is variance. If you really crush
| your opponents you are less at risk of busting from bad
| bankroll management.
| jason-johnson wrote:
| >"Game theory optimal" (as poker players like to call it) is
| not really the optimal strategy. It's the nash equilibrium
| strategy assuming the other players are also playing a nash
| equilibrium strategy. As soon as one player deviates from the
| nash equilibrium it's not optimal anymore :).
|
| This is not really what most people mean when they say "optimal
| strategy". It's true that exploitative play will make more
| money _if_ you know exactly what your opponent is doing and
| _if_ they keep doing it despite it not working. Neither of
| these will generally hold in an actual game.
|
| The reason it's called "optimal strategy" is because it works
| no matter what your opponent is doing. It will not make as much
| as a strategy tailored perfectly to your opponent but it will
| never lose to anyone under any circumstances, assuming infinite
| games (assuming infinite games just so we can ignore variance).
| The worse case the strategy has is break even to anyone else
| using it.
| pfortuny wrote:
| You are assuming there are no collusions among players
| (agreements to play against another one). That perturbs the
| Nash optimality.
| im3w1l wrote:
| I'm kind of curious how accidental collusion could work
| out. Like imagine multiple players playing in such a way
| that they help each other - but purely out of ignorance on
| how best to play the game!
| 8note wrote:
| Isn't it pretty standard, and how professional poker
| players make money?
|
| All of the good players identify the worst, riches player
| at the table, and they all take that players money.
|
| Once they're out, you leave the table too
| Moon1024 wrote:
| You're writing something that is at best accidentally
| misleading and at worst confidentially incorrect.
|
| What is your formal definition of "optimal strategy"? A Nash
| equilibrium is considered optimal in the sense that it's a
| state where no one can gain an advantage by deviating from the
| equilibrium.
|
| Sure, if your opponents don't play the Nash equilibrium, there
| is room to exploit that deviation and potentially gain more
| than what you would get from playing the Nash equilibrium.
| However, you also make yourself exploitable in return, so I
| don't think you're presenting the whole picture here.
| brigadier132 wrote:
| Poker players typically optimize for making the most money in
| expectation per hand. Either way, I'm certain that the
| exploits I've described for players that bluff too much or
| call too much are correct so I'm not too worried about being
| slightly off. Poker strategy is about heuristics.
| PeterisP wrote:
| For practical poker, I'd formally define "optimal strategy"
| as the strategy that maximizes profit per time (or per game)
| for a set of opponents, including also the actions needed to
| "explore" and discover any bias before exploiting it.
|
| Assuming at least one of opponents is not playing Nash
| equilibrium (which is a very solid assumption), playing the
| Nash equilibrium becomes suboptimal as it doesn't exploit the
| exploitable as much.
| 14 wrote:
| Trying to understand what you are getting at made me realize
| why I do not gamble I am just not smart enough or lucky enough.
| I had a friend try and convince me he knew a sure fire way to
| beat roulette but in the end the house always wins. He
| eventually had to admit he had a gambling addiction and quit
| doing it all together.
| namanyayg wrote:
| Like anything else, Poker is a skill that you can learn with
| time and practice.
|
| It is not really related to your smartness or luck (doesn't
| apply to _everyone_ of course but I'd wager that the average
| HN reader is already smart enough for poker)
| tmiku wrote:
| Of all the gambling games to insist you know a secret
| solution too, roulette has to be one of the funniest.
| mkatx wrote:
| I love poker, and I'm solid on the math foundations, but I
| still suck..
|
| Any book/other resource recommendations for brushing up on this
| stuff?
| Raidion wrote:
| Modern Poker Theory by Acevedo was the premier book on this,
| but I've been out of the game a few years. Idk if I'd fully
| trust his charts given modern sizing theory, but it's going
| to improve your game if you understand the concepts. If
| you're really serious, you want to get a solver: GTO+,
| PIOSolver, or GTOWizard (online version).
| dmurray wrote:
| > When they call too much you should obviously not bluff! This
| leads to very boring games of poker.
|
| I don't know, poker theory is all about optimal ranges and Nash
| equilibrium, but there's something satisfying (and very
| practically important, since if all your opponents even
| understand the phrase Nash equilibrium you should find a
| different game) about trying to make the most money against an
| opponent who calls or bluffs way too much.
| gweinberg wrote:
| Boring but profitable. It's super easy to take money from a
| "calling machine": just bet big when you have a strong hand.
| waprin wrote:
| I'm working on a project aiming to help pro (or serious amateur)
| poker players learn game theory, mostly via flashcards with
| spaced-repetition.
|
| https://www.livepokertheory.com
|
| I do personally dislike that GTO became the nomenclature , as I
| prefer "theory-based", since it causes this confusion, but trying
| to fight it at this point is hopeless because GTO is the search
| term people are using. And when people say they "play GTO" they
| usually mean "equilibrium" rather than "optimal against my
| specific opponents" which is "exploitative".
|
| If you actually watch what the top players advocate for, everyone
| suggests you want to play exploitatively. However, there's one
| equilibrium solution and effectively infinite exploitative
| solutions, so equilibrium is a reasonble starting point to
| develop a baseline understanding of the mechanics of the game.
| It's tough to know how much "too much" bluffing is unless you
| know a baseline.
|
| Furthermore, if you "exploit" people by definition you are
| opening yourself up to being exploited so you need to be very
| careful your assumptions are true.
|
| Also, with solvers like piosolver, you can "node lock" (tell a
| node in the game tree to play like your opponent, rather than an
| equilibrium way plays), but there's many pitfalls, such as the
| solver adjusting in very unnatural ways on other nodes to adjust,
| and it being impractical to "lock" a strategy every node in the
| tree. There's new ideas called "incentives" which gives the
| solver an "incentive" to play more like a human would (e.g.
| calling too much) but these are new ideas still being actively
| explored.
|
| Rock paper scissors is frequently used to explain GTO but it's
| not the best example because equilibrium in rock paper scissors
| will break even against all opponents, but equilibrium poker
| strategy will actually beat most human poker players, albeit not
| as much as a maximally exploitative one.
|
| There's two other huge pieces this article glosses over:
|
| 1) It's as impossible for a human to play like a computer in
| poker as in chess - in fact far more impossible, because in poker
| you need to implement mixed strategies. In chess there's usually
| a best move, but in poker the optimal solution often involves
| doing something 30% of the time and something else 70% of the
| time. The problem is that, not only are there too many situations
| to memorize all the solutions, but actually implementing the
| correct frequencies is impossible for a human. Some players like
| to use "randomizers" like dice at the table, or looking at a
| clock, but I find that somewhat silly since it still so unlikely
| you are anywhere near equilbrium.
|
| 2) Reading someone's "tells" live is still a thing. While solvers
| have led to online poker to decline due to widespread "real time
| assistance", live poker is booming (the 2024 World Series of
| Poker Main Event just broke the record yet again) , and in person
| in live poker, people still give off various information about
| their hand via body language. From the 70s to the early 2000s,
| people were somewhat obsessed with "tells" as a way to win at
| poker. Since computers have advanced so much, it's fallen out of
| favor, but the truth is, both are useful. It's totally mistaken
| to think that advancement in poker AI , GTO , and solvers have
| rendered live reads obsolete. In fact, in 2023, Tom Dwan won the
| biggest pot in televised poker history (3.1 million) and credited
| a live read to his decision, in a spot where the solver would
| randomize between a call and a fold.
| isatty wrote:
| Very nice! WC3/Dota inspired streaks on the demo flash cards?
| waprin wrote:
| Yes indeed glad you noticed! Been too addicted to that
| godforsaken game at points so figured borrow some of its
| qualities for my studying apps...in general I'm interested in
| gamification + studying.
| mckn1ght wrote:
| It's funny they mentioned Magic: the Gathering, because the first
| thing I thought of when reading the headline is all the
| conversation I see in r/EDH, and less frequently in other related
| subreddits, about a reluctance or even disdain for "optimal"
| play, which would be trying to win as efficiently as possible. To
| preserve the excitement and surprise of gameplay, people
| discourage building decks out of "staple" cards that would
| quickly homogenize play. "Broken" or "busted" cards that turn out
| to be more powerful than anticipated by the game's designers wind
| up banned in sanctioned tournament play.
| ip26 wrote:
| If you're going to play MTG as a simple game theory optimal
| affair, might as well switch to poker... a Nash equilibrium
| surely exists all the same, but charm of the game is in the
| variety and checks & balances.
| rcxdude wrote:
| Well, from the perspective of optimal play the more complex
| and changing nature of MTG means that optimal play is harder
| to find and doesn't stay still, so there's a lot more
| metagame of figuring out what that play is.
| rcxdude wrote:
| EDH is especially prone to it as a format, because it's a
| format which allows almost every card ever printed (with a
| pretty... inconsistent banlist). This makes for some pretty
| wild variations in power levels, and the top end tends to be
| both very samey and very expensive. It's very popular as a
| format but it only really works because there's a culture of
| trying to match power levels between decks (to be fair, there's
| also the fact that 100 card singleton does tend to mean it's
| hard to be completely consistent, so there's a lot more
| 'bleedover' between power levels in terms of chance to win in a
| given match, as well as the >2 player aspect levelling things
| out as a player obviously in the lead will tend to be ganged up
| on)
| willcipriano wrote:
| EDH is the variant of the game for people who aren't that
| competitive. They spend a lot of time trying not to win too
| hard. The format is fine but I don't like it beacuse of this
| culture around it, it basically has this social metagame where
| you can get better players removed out of play by complaining
| about them.
|
| Draft, Standard and Modern are for people who want a real game
| without having to worry about playing too well.
| thom wrote:
| And yet overpowered Commander cards continue to mess up Cube
| and eternal formats.
| r34 wrote:
| There is a huge difference between game theoretic optimal
| strategy and actual profitable strategy due to the human nature
| of the players. I imagine a professional poker player as someone
| who certainly knows the odds (math of the poker game in general),
| but is also very good in interpreting his opponents behavior
| (which would minimize the information revealed by them, but could
| they do it completely?). There are so many biases which even
| professional players have to overcome, that in my opinion poker
| is strongly psychological game. Also because of that I think that
| online poker and live poker are slightly different games.
| thih9 wrote:
| As a person who enjoys poker recreationally, whenever I visit
| these submissions I soon realize that this is a very different
| game from the one I'm playing.
| PaulRobinson wrote:
| I'm a fan of the levels of Poker thinking:
| https://www.blackrain79.com/2020/01/outsmart-your-opponents-...
|
| Basically, play one level - exactly one level - beyond where you
| peg your opponents at.
|
| Poker is not about playing cards. It's about playing people.
| Cards is just how we keep it civil and not too personal.
| midiguy wrote:
| It used to be about playing people back when no one knew
| anything. Now that people study GTO, it's definitely more about
| the cards.
| kruhft wrote:
| Is that not called 'bluffing' with strategic planning?
| kkwteh wrote:
| Watching Doug Polk discuss hands on YouTube really opened my eyes
| as to how professional pokers think about hands.
| leesec wrote:
| Optimal in this case means least exploitable it doesn't mean most
| profitable, which is the real point of poker
| krukah wrote:
| One thing I haven't seen anyone mention yet is that Nash
| equilibria do not actually exist when you move beyond heads-up
| into multi-way play. There's strong empirical evidence that
| solving abstracted games using MCCFR and using real-time depth-
| limited tree search dominates humans and outperforms all other AI
| strategies, but these results aren't theoretically sound, unlike
| in heads-up play.
|
| I've actually been working slowly on
| https://github.com/krukah/robopoker, an open-source Rust
| implementation of Pluribus, the SOTA poker AI. What I've found
| interesting is the difference in how I approach actually playing
| poker versus how I approach building a solver. Playing the game
| naturally consists of reasoning about narratives and
| incorporating information like hand history, play style, live
| tells. Whereas solving the game is about evaluating tradeoffs
| between the guarantees of imperfect-information game theory and
| the constraints of Texas Hold'em, finding a balance between
| abstract and concrete reasoning.
| waprin wrote:
| Looks cool I'll keep an eye on it.
| mcswell wrote:
| Sort of related: I was at a restaurant last night where a sports
| channel was playing a poker tournament. Paint drying would have
| been more interesting; it was hard to tell if one of the players
| was even alive.
| cheeze wrote:
| This can be said of so many things. Like a cycling race, or
| NASCAR, or golf, or chess.
|
| I love it. Love cycling as well.
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