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2008-07-04 9:15 AM Poker: Human vs. AI Previous Entry :: Next Entry Read/Post Comments (1) Having defeated humans at chess, AI programmers are looking for other game domains that require more human-like skills. Good candidates are Go, Bridge, and Poker.
Right now there's a human vs. computer poker competition taking place:
They tried this last year, and the program did reasonably well, but didn't win. The reason poker might be a better benchmark for AI is that in involves making decisions with incomplete information (e.g., your opponents hands). It also requires probabilistic reasoning (unlike chess, which is completely deterministic). Also, it has been shown that any optimal strategy in poker requires some bluffing, which makes sense. If you can gain an advantage by misrepresenting your strength (either under- or over-representing) you're going to lead opponents into giving you more of their chips. But knowing when and how to bluff is difficult. So it's an interesting story, but I thought this quotation near the end was pretty dumb:
I ran into this same fallacy when I read a paper about Tic-Tac-Toe several years back, in which they argued that a program that never loses at Tic-Tac-Toe is "playing optimally". Well, no. If you want to define it that way, good for you, but it's a very poor definition. To play "optimally" or "perfectly" doesn't just mean that you avoid losing, but that you maximize wins against weaker opponents. I don't think we'd call a poker player that never lost money but just barely made money a "perfect" player. Read/Post Comments (1) Previous Entry :: Next Entry Back to Top |
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