Posted on 01/16/2022 12:22:41 PM PST by DUMBGRUNT
He needs the elaborate mathematics because he is trying to make sense of a very complex world: the game of poker. “Even the smallest variant of poker has a billion billion decision points,” he told me.
Their work hasn’t just been an academic exercise, however; it has transformed how poker professionals approach the game. In search of ways to improve their odds, pros began poaching Prof. Bowling’s talent. “I regularly get contacted by poker pros asking if I can help them with something. I would say every one of the top 10 pros in the world is paying a poker programmer to do something,” he said.
...In the summer of 2019, I sat down with my laptop on a sunny afternoon to play no-limit Hold ‘Em against DeepStack, a program that Prof. Bowling helped to develop.
... To my surprise, I managed to grind out some wins. I stopped the match when I had a lead of 15 to 14 games. Much as Kasparov did after playing Deep Blue for the first time, I stared at the ceiling for a long time after the match, relieved that I had beaten the machine.
The feeling didn’t last. Shortly after our match, Prof. Bowling sent me an email, debriefing my performance against his creation by analyzing which parts of my success came from skill and which parts had emerged from the thick fog of randomness inherent in no-limit poker. He wrote, “You should expect to win 42% (margin of error of 5%) of your matches against DeepStack. While you won 15 and lost 14, your play (after removing luck) suggests you should have won 12 matches and lost 17.”
Oh, well.
(Excerpt) Read more at wsj.com ...
The feeling didn’t last. Shortly after our match, Prof. Bowling sent me an email, debriefing my performance against his creation by analyzing which parts of my success came from skill and which parts had emerged from the thick fog of randomness inherent in no-limit poker. He wrote, “You should expect to win 42% (margin of error of 5%) of your matches against DeepStack. While you won 15 and lost 14, your play (after removing luck) suggests you should have won 12 matches and lost 17.”
It is a model.
Thanks for the Archive link so I could read all of the article and the comments. Good post - should keep me out of the poker rooms.
How long until DeepStack cuts a deal with the random-card generator?
I used to play semi-pro a couple decades ago when Poker was having its hey day. Won a few modest tournaments. Played a lot of high stakes limit poker and no-limit. Limit poker is a little more mechanical, and the most you can lose in a pot is limited to the bet size though with several players your position matters a lot since you can get raised in front of you and behind you if you don’t get the other players to fold. No limit, well, you can bet any amount at any point which makes it scarier when faced with a big bet decision.
Today the game is tougher. Cash games are truth or dare. Tournament games are as much about not getting knocked out out of the tournament as they are accumulating chips. So tournaments are about saving chips as much as winning chips. Reading your opponents’ playing style and figuring out which kinds of hands they are likely to raise or call with, and then reading the board to see if those hands are likely to have hit or miss or give him/her a drawing chance. Which of course means opponents have to vary their starting hands and style a bit just to make them harder to read over the long haul. A lot of bluffing and semi-bluffing due to that psychology.
You mean like the DeepState and the non-partisan Presidential Debate Commission?
That's a pretty lame interpretation.
The computer is getting luck, too, unless this model cheats all the time.
I read a book by a guy who was a PhD mathematician who made a living for a while playing on-line poker. He said when he first got into it, it was easy pickings, there were a lot of terrible players, suckers, throwing away money. But over time, the suckers got tired of losing and the sharks were playing each other. It got harder and harder to win and eventually, he started losing and dropped out. It went from easy money and better than a paycheck to a dry hole in about year.
“It went from easy money and better than a paycheck to a dry hole in about year.”
sounds exactly like the evolutionary course of any new arbitrage discovery ...
Heh, that too!
I installed the "nathan-149/hover-paywalls-browser-extension" extension from GitHub into Google Chrome to get around WSJ (and other) paywalls.
Poker Ping
When the machine can learn to get drunk, get distracted by the waitress, get gun shy or overconfident, and have an overwhelming urge to take a pee, I’ll believe in AI. Until then, it’s just math, not poker.
—”I installed the “nathan-149/hover-paywalls-browser-extension”
Have you had much luck with Hover?
This was interesting...
Hover v2.2.8 8-29-2020
Giving up on trying to get on Chrome Store (removed due to paywall policies)
Hover v2.2.7 8-27-2020
Re-add adblocker
Reword to avoid bypassing paywalls
Hover v2.2.6 8-25-2020
Remove unused permissions from manifest
Cleanup paywall scripts code (install and update listeners)
Hover v2.2.5 8-24-2020
Remove Adblock Functionality (Chrome Store does not allow multiple features in tool)
Hover v2.2.4 8-23-2020
Remove Adblock Settings (Chrome Store does not allow multiple features in tool)
Hover v2.2.3 8-11-2020
Edit manifest.json and metadata.
Hover v2.2.2 8-1-2020
Add paywall bypass on theathletic.com.
Hover v2.2.1 7-30-2020
Add “Report Bug” Button.
Hover v2.2.0 7-25-2020
Full functionality on Chrome Web Store.
I read it was removed from the Google App Store. Go directly to GitHub to get it. Installation is very simple.
—”I read it was removed from the Google App Store.”
Yes, you can see in the readme, the app store did not want him there.
This was the first time I installed and used it. Worked like a charm.
I support your opinion
Disclaimer: Opinions posted on Free Republic are those of the individual posters and do not necessarily represent the opinion of Free Republic or its management. All materials posted herein are protected by copyright law and the exemption for fair use of copyrighted works.