For example, it'll take pieces hoping that the opponent doesn't take back, but if they do, you're in a worse position than if you had played something else. The problem with this kind of crude excitingness detector is that it basically will play forcing moves hoping the opponent doesn't find the easy-to-find best reply. En lo que tal vez sea el mayor avance de los módulos de ajedrez desde la aparición de AlphaZero, Stockfish (considerado hasta ahora como el motor más fuerte que existe) ha iniciado un nuevo proyecto basado en la absorción de NNUE, una potente Red Neuronal Artificial. You could start your heuristics with looking for lines where the top reply is bad for you up to some threshold (say -1.0 from your perspective), but all the other reasonable replies are good for you.
#Stockfish chess diable timers how to
So the key thing there is how to make the "excitingness" detector. To make your engine, you could 1) query stockfish for its top moves and the lines that result, 2) come up with your own heuristic metrics for which of the lines is most "exciting" or "tricky", and 3) output that move from your engine instead of the top move. You could also interact with the engine with plain shell scripting or really any language that is capable of starting a command-line process and reading/writing to its standard in/out streams.
It has interfaces to interact with standard UCI engines such as stockfish.
If you want to make your own engine that plays like this and you know some python, I'd suggest the python-chess package. In my experience, that is what people miss about the old way of playing in the pre-engine era, which is that you take risks (meaning your position is strictly worse with best play from your opponent) but you know that its very tricky to find the best replies. I think the kind of exciting chess you're talking about boils down to an engine that evaluates very accurately like Stockfish, but sometimes plays inaccurate lines which contain very favorable variations.
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