Until recently, this has helped man beat the machine. Aside from computing the odds of holding the winning hand, where a computer would obviously have an advantage, the key to winning in poker is bluffing, and figuring out when your opponent is bluffing. But in some sense, none of these are really interesting they’re all games of fact. There have been a few “firsts” in AI-versus-human gaming lately, and the computers are now beating us at trivia, chess and Go. Video after the break.Ĭontinue reading “PokerBot Uses FPGA For Card Calculating Horsepower” → Posted in FPGA Tagged bruce land, fpga, poker It’s another great example of a project from Bruce Land’s classes, which are somewhat of a hotbed of development each year. The strong statistical calculations help to make the computer players engaging and realistic to play against. The team report that the FPGA’s processing power brought a 10x speed up compared to their C++ program running on an Intel i7-6700HQ. This same calculation method is then used to make decisions for the computer players in the game, too. By accelerating these calculations on an FPGA, the pokerbot is able to calculate 300,000 possible hands in just 150 ms, and present a probability of winning to the human player. Calculating the entire set of possible hands is impractical, so in a Monte Carlo simulation a sample is calculated instead. The bot uses the principle of Monte Carlo simulation to calculate the probabilities of an individual winning a hand of Limit Texas Hold’em. In this vein, a group of students from Cornell’s ECE 5760 class built a pokerbot on an FPGA. That doesn’t mean there aren’t certain mathematical ways to aid your decision making based on probabilities. Played against humans, Poker is a game as much about reading your opponent as it is about the cards you’re dealt.
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