Neural Network Chess Computer Abandons Brute Force For "Human" Approach

An anonymous reader writes: A new chess AI utilizes a neural network to approach the millions of possible moves in the game without just throwing compute cycles at the problem the way that most chess engines have done since Von Neumann. 'Giraffe' returns to the practical problems which defeated chess researchers who tried to create less 'systematic' opponents in the mid-1990s, and came up against the (still present) issues of latency and branch resolution in search. Invented by an MSc student at Imperial College London, Giraffe taught itself chess and reached FIDE International Master level on a modern mainstream PC within three days.

Comments

like GnuChess

[phantomfive]

For comparison, GnuChess also plays at an International Master level. The article says this chess engine is much slower than GnuChess.

Humans are able to play chess at a high level because they are able to brutally prune the decision tree.....a grandmaster can quickly eliminate most moves as useless (although he/she will probably think of it in reverse terms: saying he/she quickly identified the important moves in the position). A computer that could combine that kind of pruning with the massive searching power would be ridiculously powerful. Better than our current computers by an order of magnitude.