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Researchers Create a Statistical Guide To Gambling
New submitter yukiloo writes "An early Christmas treat for the ordinary Joe who is stuck with a Christmas list that he cannot afford and is running out of time comes from two mathematicians (Evangelos Georgiadis, MIT, and Doron Zeilberger, Rutgers) and a computer scientist (Shalosh B. Ekhad). In their paper 'How to gamble if you're in a hurry,' they present algorithmic strategies and reclaim the world of gambling, which they say has up till recently flourished on the continuous Kolmogorov paradigm by some sugary discrete code that could make us hopefully richer, if not wiser. It's interesting since their work applies an advanced version of what seems to be the Kelly criterion."
Half this submission makes no sense, grammatically or otherwise.
The three authors completely agree on the mathematics, but they have somewhat different views about the
significance of this project. Here they are.
Evangelos Georgiadis’ Conclusion
We provided a playful yet algorithmic glimpse to a field that has up till recently flourished on the Kolmogorov,
measure-theoretic paradigm [as evidenced by the work of Dubins and Savage [4] (see [7] for more recent
developments]. The advent and omnipresence of computers, however, ushered an era of symbol crunching
and number crunching, where a few lines of code can give rise to powerful algorithms. And it is the ouput
of algorithms that usually provides insight (and inspiration) for conjectures and theorems. Those, in turn,
can then be proven in their respective measure-theoretic settings. Additionally, a computational approach
lends itself easily to more complex scenarios that would otherwise be considered pathological phenomena
(and would be fiendishly time-consuming to prove – even for immortals like Kolmogorov and von Neumann).
Doron Zeilberger’s Conclusion
Traditional mathematicians like Dubins and Savage use traditional proof-based mathematics, and also work
in the framework of continuous probability theory using the pernicious Kolmogorov, measure-theoretic, par-
adigm. This approach was fine when we didn’t have computers, but we can do so much more with both
symbol-crunching and number-crunching, in addition to naive simulation, and develop algorithms and write
software, that ultimately is a much more useful (and rewarding) activity than “proving” yet-another-theorem
in an artificial and fictional continuous, measure-theoretic, world, that is furthermore utterly boring.
Shalosh B. Ekhad’s Conclusion
These humans, they are so emotional! That’s why they never went very far.
I'm not sure if the original submitter had his tongue in cheek by describing the co-author Ekhad as a "computer scientist." Just in case he didn't, note that Shalosh B. Ekhad is actually Zeilberger's computer. Since most of Zeilberger's research depends heavily on computations, and (I think) as a nod to some of his philosophical positions, Zeilberger usually lists his computer as a coauthor on his papers. So I guess Ekhad is a computer scientist, but not quite in the way we usually mean. :)