CMU's Libratus builds substantial lead in Brains vs. AI competition • Hacker News Board

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#81

Post by levthedev » Mon, Jan 23, 2017, 2:19 PM UTC

echelon wrote: post #58

nopinsight wrote: post #31

I believe we are witnessing the Cambrian explosion of intelligences. The techniques behind Libratus (abstraction algorithm and game theory [1]) appear to be qualitatively distinct from those behind AlphaGo (deep reinforcement learning and MCMC) and DeepBlue (search and heuristics). An ecology of Artificial Intelligences, unbounded by our evolutionary history and neural architecture, could evolve to suit each particul…

Chess, Go, Poker... All feel like variations on the same theme. While it's obvious there is innovation being done, I want to see something more challenging. Something with more dimensionality and integration of several types of input. How about a machine that can beat someone at Smash Bros, a game with varied characters, complex comboing mechanics, and a nontrivial computer vision task? Or--more difficult by a few or…

Check out https://github.com/vladfi1/Phillip. It is a Super Smash Bros bot that can beat most anyone and is trained with a tensorflow model that you can build yourself by playing it for a few days.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#82

Post by levthedev » Mon, Jan 23, 2017, 2:21 PM UTC

echelon wrote: post #58

nopinsight wrote: post #31

I believe we are witnessing the Cambrian explosion of intelligences. The techniques behind Libratus (abstraction algorithm and game theory [1]) appear to be qualitatively distinct from those behind AlphaGo (deep reinforcement learning and MCMC) and DeepBlue (search and heuristics). An ecology of Artificial Intelligences, unbounded by our evolutionary history and neural architecture, could evolve to suit each particul…

Chess, Go, Poker... All feel like variations on the same theme. While it's obvious there is innovation being done, I want to see something more challenging. Something with more dimensionality and integration of several types of input. How about a machine that can beat someone at Smash Bros, a game with varied characters, complex comboing mechanics, and a nontrivial computer vision task? Or--more difficult by a few or…

Check out https://github.com/vladfi1/Phillip. It's a Super Smash Bros bot that can beat the top players in the world and is run by a tensorflow model that can be created by playing against it for a few days.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#83

Post by czzarr » Mon, Jan 23, 2017, 2:41 PM UTC

That is very unconvincing as 49k hands is really nothing and not enough to iron out variance unless the edge is really big (which doesn't seem to be the case). Any serious poker player will tell you that. They should play 1-10 million hands (depending on the edge) in order to get a decent idea of where this is going.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#84

Post by deong » Mon, Jan 23, 2017, 2:46 PM UTC

Anderkent wrote: post #80

angelofm wrote: post #46

I played poker part time heads up (one against one) previously and the amount of study and analyses players have to do is huge to only get to a reasonable level. This challenge is very unfair to players so I wouldn't say it won, players have a massive disadvantage, every professional player has tracking software and a database to analyse every decisions that has been made. This is of course extremely important becaus…

>o the bot adjusts it's play based on their human opponents but humans cannot do the same and are left with a guessing game Do we know if it actually does it? I imagine it's much simpler to build a bot that plays a balanced profitable strategy rather than one that tries to build a model of their opponent and exploit it.

It's stated in the article. During a day's play, the AI suggests plays based on its current knowledge. At night, the day's events are fed into the system for it to learn on for the next day.

I assume there are probably papers that specify what form of learning is taking place, but the article didn't go into that level of detail and I haven't tried to track it down.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#85

Post by [deleted] » Mon, Jan 23, 2017, 2:50 PM UTC

xapata wrote: post #23

spectrum1234 wrote: post #4

Earlier quoted context omitted.

And tanking for 1+ mins on turn and river decisions (it would time out in real online poker). And $10M in computer resources. But impressive nonetheless.

Eh, I'll tank for a few minutes in live poker. I don't mind that the computer does too.

[deleted]

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#86

Post by jat850 » Mon, Jan 23, 2017, 3:42 PM UTC

cdelsolar wrote: post #44

jat850 wrote: post #10

Earlier quoted context omitted.

If it's unfair in any regard (and I disagree with GP that it's unfair on the merit of physical reads), it's that humans get fatigued and computers do not. Having played poker for stretches of 16+ hours I know that the number of mistakes I make late in the day drastically outnumber the ones I make when I am fresh. And breaks only do so much to counter this fatigue. I'd have to say that playing poker for long stretches…

is at least as what?

At least as tiring (physically, mentally). Like my brain obviously was when I wrote that post :)

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#87

Post by xapata » Mon, Jan 23, 2017, 4:12 PM UTC

echelon wrote: post #58

nopinsight wrote: post #31

I believe we are witnessing the Cambrian explosion of intelligences. The techniques behind Libratus (abstraction algorithm and game theory [1]) appear to be qualitatively distinct from those behind AlphaGo (deep reinforcement learning and MCMC) and DeepBlue (search and heuristics). An ecology of Artificial Intelligences, unbounded by our evolutionary history and neural architecture, could evolve to suit each particul…

Chess, Go, Poker... All feel like variations on the same theme. While it's obvious there is innovation being done, I want to see something more challenging. Something with more dimensionality and integration of several types of input. How about a machine that can beat someone at Smash Bros, a game with varied characters, complex comboing mechanics, and a nontrivial computer vision task? Or--more difficult by a few or…

Poker is somewhat different due to incomplete information and its highly stochastic nature. It's easy to infer incorrect action-payoff relationships from observing hundreds or even thousands of hands. Like the stock market, the cards can stay irrational longer than you can stay solvent.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#88

Post by vannevar » Mon, Jan 23, 2017, 4:22 PM UTC

czzarr wrote: post #83

That is very unconvincing as 49k hands is really nothing and not enough to iron out variance unless the edge is really big (which doesn't seem to be the case). Any serious poker player will tell you that. They should play 1-10 million hands (depending on the edge) in order to get a decent idea of where this is going.

Yes, I'm wondering if anyone is tracking the relative strength of each player's hands. In the end, the bot should be declared the "winner" only if its winnings were disproportionately high in relation to the strength of its hands.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#89

Post by Qworg » Mon, Jan 23, 2017, 4:24 PM UTC

logicallee wrote: post #76

echelon wrote: post #58

Earlier quoted context omitted.

Chess, Go, Poker... All feel like variations on the same theme. While it's obvious there is innovation being done, I want to see something more challenging. Something with more dimensionality and integration of several types of input. How about a machine that can beat someone at Smash Bros, a game with varied characters, complex comboing mechanics, and a nontrivial computer vision task? Or--more difficult by a few or…

>Something with more dimensionality and integration of several types of input. like using a few degrees of freedom and little strength to chop onions and some vegetable, crack eggs, whisking them, pour a bit of oil into a pan and lighting a stove, pour the omelette, flip it onto the plate, throw the eggshells in the trash unless it's too full (and take the trash out if it is) and wash the chopping board and pan with…

We make up for hand weakness with hand dexterity, slow vision processing with incredibly rich feature sets and powerful cameras, and reliable actions with previsioning and prediction on every task.

The human system is pretty incredible.

Re: CMU's Libratus builds substantial lead in Brains vs. AI competition

#90

Post by otoburb » Mon, Jan 23, 2017, 4:54 PM UTC

mrkgnao wrote: post #43

How would someone with no knowledge of the game learn to play poker? Any good books that stress the mathematical/probabilistic(/game theoretic...?) side of things?

Poker enthusiasts hang out at the TwoPlusTwo forums[1]. After reading up on combinatorics and learning the rules for numerous poker variants, diving into the forum posts will give you better insight into how players view the game, the situations they get into, and how they learn to analyze and read hands and other players.

[1] http://www.twoplustwo.com/