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I don't understand. Maybe there are some good resources to read, so I could see it better? Essentially, you are explaining why poker it hard. This is no surpri
by krick 10y ago
I don't understand. Maybe there are some good resources to read, so I could see it better?
Essentially, you are explaining why poker it hard. This is no surprise, and I already included it into my question to an extent. The real question is, why is it harder for computers than for humans? Both seem to be completely oblivious to what is truly going on due to imperfect information nature of poker, and both seem to be able to make simple estimations. Computers are better at multiplying fractions (needed to estimate probability) and computers are better at not-worrying (needed to bluff well). I'd assume it is humans who are at disadvantage, and your post doesn't explain (it seems) why is it the otherwise.
- spectrum1234 10y agoAs said before because of hidden information the optimal strategy appears to diverge unless you have more (all) the information in the decision tree. Basically you can never make a decision with the specific hand you have in isolation without knowing what you'd do with every other hand (and same for your opponent). This is very different than chess/go! So while poker may even have a simpler game tree than chess/go you need to have more of it upfront to solve the game, and being "off" means much much greater error. Depth matters less than breadth. Said another way in chess/go you can brute force get near optimal for the current decision, then reset and do again for the next decision. But with poker you have to solve for ALL POSSIBLE decisions (hands) up front (and inclusive of all possible board situations), and THEN do AGAIN 3 more times (pre-flop flop turn river) plus the numerous times you are raised means this is much more than 4 times total. Example: Bot is out of position with AdAh on AsKsQc facing a big raise. In isolation its probably best to re-raise and simulations show this makes the most money. But you also need to account for the times you have AT (no flush draw) and need to save AT money. But this logic doesn't stop here. Typically on the river out of position you will check the majority of your range if your opponent has bet every street (this is one of the few "proven" strategies because you always want the pot smaller out of position on average). So, you literally need to have the entire game solved in order to know HOW TO GET TO THE RIVER in a balanced way with good and bad hands. And, getting to the river to play profitably likely means giving up profitability on every other street - this is the diverging from optimal that default algorithms will be wrong on unless they have the entire game tree in front of them.
- krick 10y agoThis again has nothing to do with question in hand. Yes, poker is imperfect information game, everybody knows that. Why does it make it easier for humans than for computers? Humans cannot do these computations in the head any better than computers, quite the contrary.
- spectrum1234 10y agoHard to explain well. Let me try another way. Thinking through this more right now, it seems like the default way of computers to solve this penalizes them. Every time they get more depth it hurts them unless you account for more breadth. So lets say the programers know this. This STILL probably doesn't help much because...well idk. What's interesting is Tensor Flow is supposed to be massively parallel (breadth) and abstract the software/algorithms to do this. But if you follow this logic the answer must be gradient decent algorithms also get stuck somewhere... This must have to do with hyper-sensitivity to really having the full decision tree before optimizing. The answer seems to be if computers are modeling this exactly as humans do, (using neural networks which then simplify this problem with heuristics), it just takes this much computer power to simulate 1 human brain optimizing for this. Alternatively if they model it in a more brute force way it must take even more computer power because this is proving to be less efficient.
- nabla9 10y agoThis is very good question. We covered why poker is hard. Now, lets cover why it is hard for computers. Simply: building model of the opponent(s) is part of poker. In games like Chess and Go without hidden information you can just "play the game" best you can. Other players are not important. Optimal strategy against good player is optimal against bad player are the same. It's just playing the game. In poker this is not true. Bets reveal information about the player's strategy and his hand. Figuring the other player out is part of the game. Against bad player, optimal strategy is usually different than against good player. Playing against tight-agressive is different than playing against tight-passive. In multi-way poker it's important to know how strong is the player sitting left to you and change your game accordingly.
- krick 10y agoThat makes sense. But does it mean that if I don't have a real idea of what I'm doing (i.e. you cannot assume my moves are optimal from my point of view) your expertise is essentially useless against me?
- nabla9 10y agoIf someone plays crazy, the solution is to go back playing simple near optimal poker aka playing the cards, calculate expected values and bet accordingly.
- leakybit 10y agoBecause a computer has to adapt to the opponents strategy or else the human can simply exploit the rule based algorithm that the computer is following. Most dedicated online players are already using an arsenal of software for probability, statistics, and player profiling while playing, so a computer would really not have an edge with the math since the human is running the same computations. A human can start poking around and explore methods to fool the computer.