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How poker and other games help artificial intelligence evolve

#artificialintelligence

When he was growing up in Ohio, his parents were avid card players, dealing out hands of everything from euchre to gin rummy. Meanwhile, he and his friends would tear up board games lying around the family home and combine the pieces to make their own games, with new challenges and new markers for victory. Bowling has come far from his days of playing with colourful cards and plastic dice. He has three degrees in computing science and is now a professor at the University of Alberta. But, in his heart, Bowling still loves playing games.


How poker and other games help artificial intelligence evolve

#artificialintelligence

Michael Bowling has always loved games. When he was growing up in Ohio, his parents were avid card players, dealing out hands of everything from euchre to gin rummy. Meanwhile, he and his friends would tear up board games lying around the family home and combine the pieces to make their own games, with new challenges and new markers for victory. Bowling has come far from his days of playing with colourful cards and plastic dice. He has three degrees in computing science and is now a professor at the University of Alberta.


Review of One Jump Ahead: Challenging Human Supremacy in Checkers

AI Magazine

CHINOOK that I also highly recommend. AI Magazine Volume 20 Number 1 (1999) ( AAAI) vided more than a glimpse of the intense process it described. One Jump Ahead was written by the person most involved in the process. Thus, it provides us with a direct view of Schaeffer's maturation--a maturation that we should all hope to have. Schaeffer does not pull any punches in his book; we see many of his elations, his disappointments, and his flaws.


Articles

AI Magazine

Samuel's successes included a victory by his program over a master-level player. In fact, the opponent was not a master, and Samuel himself had no illusions about his program's strength. This single event, a milestone in AI, was magnified out of proportion by the media and helped to create the impression that checkers was a solved game. Nevertheless, his work stands as a major achievement in machine learning and AI. Since 1950, the checkers world has been dominated by Tinsley.


1109

AI Magazine

This work remains a milestone in AI research. Samuel's program reportedly beat a master and "solved" the game of checkers. Both journalistic claims were false, but they created the impression that there was nothing of scientific interest left in the game (Samuel himself made no such claims). Consequently, most subsequent game-related research turned to chess. Other than a program from Duke University in the 1970s (Truscott 1979), little attention was paid to achieving a world championship-caliber checker program.


How Checkers Was Solved

The Atlantic - Technology

So, they sat in the now-defunct Computer Museum in Boston. The room was large, but the crowd numbered in the teens. The two men were slated to play 30 matches over the next two weeks. The year was 1994, before Garry Kasparov and Deep Blue or Lee Sedol and AlphaGo. Contemporary accounts played the story as a Man vs. Machine battle, the quick wits of a human versus the brute computing power of a supercomputer.


A short history of AI schooling humans at their own games

PBS NewsHour

Garry Kasparov plays a move against Deep Blue in their first game in Feb. 1996. Twenty-one years ago today, IBM computer Deep Blue famously beat chess world champion Garry Kasparov at his own game. While Deep Blue would go on to lose the full match, the event launched a long line of victories by artificial intelligence (AI) over humans in gaming. Since Deep Blue's initial triumph, many computer systems have challenged humans in other complicated games, like Go and poker. Games might seem a trivial way to measure AI.


Computer can't lose checkers - USATODAY.com

AITopics Original Links

"The program can achieve at least a draw against any opponent, playing either the black or white pieces," the researchers say in this week's online edition of the journal Science. "Clearly ... the world is not going to be revolutionized" by this, said Jonathan Schaeffer, chairman of the department of computing science at the University of Alberta. The important thing is the approach, he said. In the past, game-playing programs have used rules of thumb -- which are right most of the time, he said -- to make decisions. "What we've done is show that you can take non-trivial problems, very large problems, and you can do the same kind of reasoning with perfection.


Cracking the draughts code - Technology - smh.com.au

AITopics Original Links

The perfect game of draughts ends as a draw, Canadian computer scientists reported on Thursday. The team at the University of Alberta said they had "solved" draughts, the 5000-year-old popular board game also known as chequers (or checkers). Their computer program, Chinook, spent more than 18 years playing out the 500 billion possible positions, they report in the journal Science. "This paper announces that checkers is now solved: Perfect play by both sides leads to a draw," Jonathan Schaeffer and colleagues wrote in their report. "That checkers is a draw is not a surprise; grandmaster players have conjectured this for decades."


Computers Solve Checkers—It's a Draw

AITopics Original Links

And now, after putting dozens of computers to work night and day for 18 years--jump, jump, jump--he says he has solved the game--king me!. "The starting position, assuming no side makes a mistake, is a draw," he says. Schaeffer's proof, described today in Science (and freely available here for others to verify), would make checkers the most complex game yet solved by machines, beating out the checker-stacking game Connect Four in difficulty by a factor of a million. "It's a milestone," says Murray Campbell, a computer scientist at IBM's T. J. Watson Research Center in Hawthorne, N.Y., and co-inventor of the chess program Deep Blue. "He's stretched the state of the art." Although technological limits prohibit analyzing each of the 500 billion billion possible arrangements that may appear on an eight-by-eight checkerboard, Schaeffer and his team identified moves that guaranteed the game would end in a draw no matter how tough the competition.