7

Calling it an "inaccuracy" is nothing more than the engine saying that it evaluates the position after one move to be a certain amount better than after another move. It doesn't necessarily mean a move is "bad". Both d-pawns cannot be kept no matter what Black does. After 1...Ne4, if White plays Nxe4, the recapture will leave the c4 ...


6

There were attempts back in the 1980s to write chess engines with knowledge bases that would pick candidate moves like humans, but they were unsuccessful. The problem is that human pattern matching is difficult to put into words, so creating the rules for the knowledge base was extremely difficult. Training a neural network to pick candidate moves seems ...


4

You might take a look at Giraffe which was recently in the news: https://thestack.com/iot/2015/09/14/neural-network-chess-computer-abandons-brute-force-for-selective-human-approach/ The hype is that in 3 days it taught itself the game and reached IM level. On the other hand the research is at http://arxiv.org/abs/1509.01549


3

Alpha-beta pruning simply means that if you find a line that turns out badly for you, you stop looking at that candidate move, and instead try others. It is a type of backward pruning meaning that you'll never miss a good move as a result. Forward pruning, by contrast, is based more on guesswork. Futility pruning, late move reductions and razoring are ...


3

I'd like add details to @Ian_Bush's answer on Giraffe. In @Ian_Bush's answer, it's noted that Giraffe doesn't use brute-force computation. This is not right, because Giraffe is still an alpha-beta (nega-max) engine. The only difference to a standard engine is that the evaluation function is tuned automatically by deep-learning. Therefore, the engine learns ...


2

Its sort of debatable if you can call a heuristic based search and evaluate approach as brute-force. Most of top-tier chess engines today follow a rules-based approach to evaluate a position and a rules based search function to prune moves. This is actually not guaranteed to pick the "global optimal" move, however these moves are good enough for purpose. In ...


2

Claude Shannon proposed two types of algorithms for creating chess engines. A "type A" engine examines all possible moves to some finite depth, minimaxes the tree, and then plays the move with the highest evaluation from the minimaxed tree (a.k.a. brute force). Type B engines limit their search to only a subset of possible moves based on some criteria. I ...


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