DailyDirt: Computers Like To Sit In Front Of Computers And Play Games All Day, Too

from the urls-we-dig-up dept

Artificial intelligence software has been getting better and better over the years at beating humans at their own games. Games like Connect Four and Checkers are already solved, and while we humans might like to point out that there are games like Othello, Go, Diplomacy and Calvinball that still favor human players, it may only be a matter of time before computers outwit us at those games, too. Check out a few more games that algorithms are learning to play better than human brains.

• A specific version of Texas Hold 'em (heads-up limit Texas Hold ’em) will likely be dominated by computer players now that an algorithm has minimized a "regret" function for playing it. Poker hasn't been solved, but humans better watch out when playing online to make sure their opponents are actually other humans (if it's even possible to tell). [url]
• A computer simulating ant behavior has found almost half a million novel solutions to the "knight's tour" problem in chess. This isn't really a game, but it shows how AI can use some pretty wild strategies to solve game-related challenges. [url]
• The game of Go (aka wei qi) isn't going to be solved by a computer any time soon, but Go-playing software is getting better against human opponents. To make move decisions, advanced Go AI programs play randomized simulations of entire games to try to pick between move options. That's not quite how humans play the game, but apparently it's a somewhat winning strategy to use against human players. [url]

If you'd like to read more awesome and interesting stuff, check out this unrelated (but not entirely random!) Techdirt post via StumbleUpon.

Filed Under: ai, algorithms, artificial intelligence, chess, game algorithms, games, go, knight's tour, poker