LeelaFish: cómo usar una red neuronal para sustituir la mejor función de evaluación de ajedrez hecha a mano por programadores humanos
LeelaFish UCI chess playing engine derived from Stockfish and LeelaChess Zero: https://github.com/LeelaChessZero , https://github.com/official-stockfish/Stockfish Introduction This is a chess engine based in the Stockfish tree search but where we use the LCZero value head as evaluation function. So in this project we are just using the Stockfish code but replacing the human developed evaluation function for the neural network value head of the LeelaChess Zero project. This is a kind of experiment in which we try to figure out if the results are good even without the use of the MCTS LCZero does. Results Results are very promising and in a 1:1 ratio (when the number of nodes used by the original Stockfish or LCZero are forced to be equal to the number of nodes used by LeelaFish ) our development is able to beat both SF and LCZero. We used for these tests the LCZero network tesnet 10510. One thing is clear: the value head of the network is as good as the original manu