Now, here we have a 'KRBNPP vs krpp' chess problem generated autonomously by Chesthetica using the 'Digital Synaptic Neural Substrate' computational creativity approach which does not use any kind of deep learning. Chesthetica is able to generate mates in 3, mates in 4, mates in 5, study-like constructs and also compose problems using specific combinations of pieces fed into it (e.g. to compose something using a rook, bishop, knight and three pawns vs. a queen and a rook). Read more about it on ChessBase. Noteworthy here is that a chess position with over 7 pieces could not have been derived or taken from an endgame tablebase because 7 pieces is the present limit.
White to Play and Mate in 4
Chesthetica v10.69 : Selangor, Malaysia
2018.7.8 11:14:52 PM
Chess puzzles are ancient. Some are over a thousand years old but only in the 21st century have computers been able to compose original ones on their own like humans can. White is over a rook's worth in material but the precise win in this position still needs to be found. Why not time yourself how long it took you to solve this? Over time, the tactics you see in these puzzles will help you improve your game.
Main Line of the Solution (Skip to 0:35)
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