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" Generally speaking, the way chess engines like IBM&amp;#039;s Deep Blue work is by brute forcing every single possible move, running all of the possibilities, before picking one. There&amp;#039;s no real evaluation of positions with these machines, no narrowing down of potential options to only those most fruitful. That&amp;#039;s where the chess engine called Giraffe comes in. Rather than use the brute force method, Giraffe uses a deep neural network to examine possible moves. This layered approach, which is meant to mimic the process of the human brain, evaluates the game as a whole, the game by piece, and the game by what moves those pieces can make. This is only possible because the man behind Giraffe, Matthew Lai, has used a specific set of data taken from real chess matches\u00A0to train it.\u00A0That doesn&amp;#039;t mean the chess engine\u00A0doesn&amp;#039;t have it&amp;#039;s own share of troublesome issues. &amp;quot;The biggest challenge is to train a neural network that generalizes well,&amp;quot; Lai says. &amp;quot;Generalization means it needs to be able to apply the knowledge learned from training positions to similar but different positions. That&amp;#039;s as opposed to rote memorization of rigid patterns, which won&amp;#039;t work for chess, because there are too many possible chess positions out there. &amp;quot; The data set used by a deep neural network determines whether it sinks or swims at any given task. If the data set is too limited, the machine will fall back on poor moves, either learning bad ones or just not learning how to perform the good ones.\u00A0To make sure Giraffe&amp;#039;s data set is extensive enough, Giraffe plays itself over and over, internalizing the best moves and decisions. The engine weighs\u00A0moves made by the winning side more favorably, as that&amp;#039;s a clear indication of &amp;quot;this was ultimately good.&amp;quot; While it can&amp;#039;t really compete against top-of-the-line engines, and sits somewhere in the middle rankings of the most active chess engines,\u00A0it does stack up well against contemporaries. &amp;quot;The cool thing is that Giraffe can actually beat many engines searching five to ten times\u00A0as fast as it does,&amp;quot; Lai says. &amp;quot;In human-speak, it plays more by intuition than accurate calculations. That means it will sometimes lose games in complex tactical positions, but it plays more like humans in terms of positional understanding.&amp;quot; As for the future of the chess engine, Lai&amp;#039;s still got goals in mind. &amp;quot;I want to bring it up to grandmaster level, which shouldn&amp;#039;t be too difficult.&amp;quot; And once that&amp;#039;s done? Well, then it&amp;#039;s time to conquer other games. Source: MIT Technology Review "^^<http://www.w3.org/2001/XMLSchema#string>
<http://www.popularmechanics.com/technology/robots/a17339/chess-engine-plays-against-itself/>