They all seem to use improved versions of min-max/alpha-beta. What if you could more easily set an engine to find forced draws in certain lines, or tailor an engine to find tricky lines that a particular opponent is less likely to follow correctly, or find and optimise for certain endgame structures an opponent is weak at? Doing this in ChessBase (a truly awful but necessary piece of software) is quite painful.Ĭhess programming is fascinating but it seems for me that it has somewhat stalled in creativity in terms of classical (non DNN) engines. I also think engines as tools for match preparation could be much better. This is especially relevant to engines when making strategic moves rather than calculating short term tactics. For example, many people are working on explainability in machine learning, but I think in many applications you want to go even further and actually optimise a model to _teach humans_ not just explain its predictions. I strongly suspect you could teach an entire CS degree never stepping outside of chess.Įven now there are so many rich directions you could go in. There's no surprise to me that many of the greats have turned their eye to representing and solving chess, from Turing to Knuth. So much fundamental computer science is covered, from extremely low level CPU instructions to high level data structures and algorithms. I think chess engines are an amazing thing to study.
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