PLAY CHECKERS AGAINST REAL PEOPLE FREE CHECKERS GAMES

Play Checkers Against Real People Free Checkers Games

Improve your skills - Play free Checkers - Checkers game online, Play Draughts Online.Marion TinsleyвЂ”math professor, minister, and the best checkers player in the worldвЂ”sat across a game board from a computer, dying.GameColony offers free checkers games that are great for all skill levels, plus checkers tournaments for cash prizes. If stunning graphics are what you need to enrich your game experience, you'll find Checkers Free to be a bit simple.Play Checkers online against a computer opponent or a friend, multiplayer. Play against the computer, try 'pass the phone' mode with a friend, or play online with friends and strangers. Checkers Classic Online is a simple game, but sometimes the simplest things are the most pleasant.

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It hadn't lost a game in its last 125вЂ”and since theyвЂ™d come close to defeating Tinsley in 1992, SchaefferвЂ™s team had spent thousands of hours perfecting his machine.The night before the match, Tinsley dreamt that God spoke to him and said, вЂњI like Jonathan, too,вЂќ which had led him to believe that he might have lost exclusive divine backing.So, they sat in the now-defunct Computer Museum in Boston. Through obsessive work, Chinook had become very good. But this was a different sort of competition, the Man-Machine World Championship.His opponent was Chinook, a checkers-playing program programmed by Jonathan Schaeffer, a round, frizzy-haired professor from the University of Alberta, who operated the machine. It's possible no single person had ever dominated a competitive pursuit the way Tinsley dominated checkers.

The pain was keeping him up all night. And Schaeffer, though he was a bull-headed young man, had become the most effective promoter of TinsleyвЂ™s prowess and legacy.But there, in that hall, a quirk of human development was troubling Tinsley. He had volunteered to play friendly matches against the computer in the run-up to their two world championship matches. Having been so dominant against humans for so long, Tinsley seemed to thrill at finally having some entity that could give him a real game.

HeвЂ™d devoted years of his life to creating a program that could beat the best checkers player ever, and just as he was about to realize this dream, Tinsley quit. But Schaeffer was crushed. Chinook became the first computer program in history to win a human world championship. Tinsley understood his fate.He withdrew. But the next day, an X-ray revealed there was a lump on his pancreas. Schaeffer took him to the hospital.

People said to me, вЂYou could never have beaten Tinsley because he was perfect.вЂ™ Well, yes, we would have beaten Tinsley because he was only almost perfect. вЂњThe reason was simple: I wanted to get rid of the ghost of Marion Tinsley. The results would be published July 19, 2007, in Science with the headline: Checkers Is Solved.вЂњFrom the end of the Tinsley saga in вЂ™94вЂ“вЂ™95 until 2007, I worked obsessively on building a perfect checkers program,вЂќ Schaeffer told me. With Tinsley gone, the only way to prove that Chinook could have beaten the man was to beat the game itself.

In computer science, so he decided to build a chess-playing program. But he also loved computersвЂ”and had done a Ph.D. He was a chess player, first.

вЂњI would fantasize about the exhilaration that I would experience when Chinook finally defeated the Terrible Tinsley.вЂќAt the highest levels, checkers is a game of mental attrition. And it was there that he began to hear about Marion Tinsley, the great. Schaefer realized he would never build the world computer champion.A colleague suggested that perhaps he should try checkers, and thrillingly, with just a few months of work, his software was good enough to bring to the Computer Olympiad in London to compete against other checkers-playing bots. At the same time, the team that would form DeepBlue, the chess software that would eventually defeat Kasparov, was coming together. In 1989, he вЂњcrashed and burnedвЂќ at the World Computer Chess Championships, however.

That was certainly the idea back in the mid-1950s, when an IBM research scientist named Arthur Samuel began to experiment with getting a checkers-playing program to run on an IBM 704. The primary way to lose is to make a mistake that your opponent can jump on.This would seem to make checkers a game amenable to computer play. They play that out, then switch colors. Instead, a three-move opening is drawn from a stack of approved beginnings, which give some tiny advantage to one or the other player.

Samuel explained, does not think. In May 1958, several members of the Endicott Johnson Corporation Chess and Checkers Club trounced the computer, much to the delight of the Binghamton Press and Sun-Bulletin.вЂњThe human brain, sometimes lost sight of in an age of satellites, frozen foods, and electronic data processing machines, returned to former glories early today,вЂќ the paper said. But SamuelвЂ™s programs never had much success against actual humans. The descendants of that early work now promise to revolutionize whole industries and labor markets.

HeвЂ™d have to build a new system. As with so many of the currently hot AI techniques, he just did not have the computational horsepower or datasets that he needed to make the beautiful ideas work.So when Schaeffer began building his own software, he went straight back to Samuel, and found that he could not exactly follow SamuelвЂ™s path. And Sutton also happens to be one of SchaefferвЂ™s colleagues at the University of Alberta, where GoogleвЂ™s DeepMind AI shop recently announced it will set up its first international research office.While his techniques were groundbreaking, 10 years later Samuel had made, in his own words, вЂњlimited progressвЂќ on the problem, though heвЂ™d kept working at it at IBM, while visiting at the Massachusetts Institute of Technology, and then with a Department of Defense grant at Stanford University. One of the men who wrote the book Reinforcement Learning, Rich Sutton, called SamuelвЂ™s research the вЂњearliestвЂќ work thatвЂ™s вЂњnow viewed as directly relevantвЂќ to the current AI enterprise. Then it rejects choices which have turned out badly in the past and makes moves which turned out well.вЂќThis still would work pretty well as a description of whatвЂ™s known as вЂњreinforcement learning,вЂќ one of the basket of machine-learning techniques that has revitalized the field of artificial intelligence in recent years.

It started to be able to beat people. Back in the early вЂ™90s, it took vast amounts of computer time to be able to run all those calculations.But as Schaeffer and his team did more and more computation, Chinook got better and better. So, if there were six pieces leftвЂ”and as time went on, seven, then eightвЂ”SchaefferвЂ™s software knew every possible combination. The first is easy to understand: ItвЂ™s a вЂњbookвЂќ of complete computations of every possible checkers position with a certain small number of pieces on the board. As he described it in his 1997 book, вЂњSometimes, when I had difficulty getting to sleep, I would fantasize about the exhilaration that I would experience when Chinook finally defeated the Terrible Tinsley.вЂќ His wife would interrupt his reveries asking, вЂњYouвЂ™re thinking about him again, arenвЂ™t you?вЂќAs the software developed through the years, it retained two core components. *The work consumed Schaeffer.

Like many similar systems, Chinook would look ahead many possible moves and then try to score each permutationвЂ™s desirability. Chinook needed to search through possible moves beginning with the start of a match. The cup is each calculation.The second component of the system is a little trickier to grasp. The sea is the number of checkers possibilities. Schaeffer has an analogy to help people understand how ridiculous that is: Imagine draining the Pacific Ocean and then having to fill it back up with a tiny cup, one at a time.