Haven't heard of him. But using neural nets at that time is pretty cool. All that backgammon makes me recall is that it was an example of a game that had been solved even though it has chance in it. The search tree was adequately small.
But seeing them use equations for game solving just reminded me of something. I have a vague but enthousiastic plan of doing a doctorate, and a russian friend of mine (who actually won prizes with his doctorate and further papers on HVAC systems) suggested I should use poker as my domain of practical application because I know so much of it. So while browsing popular scientific papers of poker I came across an interesting one. The name was already cool, in my world at least: An evolutionary game-theoretic analysis of poker strategies. And one of the authors I actually know! I played go for about 3 months in college, when a friend dragged me into it. But after I reached the same level as artificial intelligence can muster in this short time, I lost interest. Or more honestly, I beat this one fellow student that played for many years that I just wanted to beat really badly, and after that I quit. But at the time I played I joined this go club and this guy was there. And when lateron I went on to do an AI assignment to optimize go search trees by pruning, lo and behold it was under this guy. And now he's investigating poker apparently. If I can get something worked out in the machine learning aspect of poker I'll definitely have to contact him again.
You can't just find this normally but I think it's ok to link it, the epitome of boringness, a scientific paper on poker:
http://ofideasandmen.com/FTR/j.entcom.2009.09.00.pdf
No poker in the commune, but hardcore poker math like this is pretty random though right?
Here they datamined a whole bunch of online poker games (they don't specify what stake though sadly) and then plugged it into their equations and came up with some interesting stuff. Most interesting:
- Poker players don't play rationally.
- Poker players are better modeled by a combination of playing rationally and playing exploratory. It's still not quite there yet but it's already a step forward from assuming pure rational play.
- They divided strategies into 4 categories (shark VPIP<25 AF>1, rock VPIP<25 AF<1, fish VPIP>25 AF<1 and gambler VPIP>25 AF>1) and found that as expected the shark strategy is the winning strategy, except for when you're playing with only sharks, fishes and gamblers at the table. No rocks. Then a gambler strategy is markedly superior. And when we correct for the fact that our opponents aren't expected to play rationally, the gambler strategy is the one that gains the most in importance.
- aggressive play postflop >>> passive play postflop. No surprise but now science provedz it!