A ‘KQBNN vs krbnp’ mate in 3 chess puzzle or problem (whichever you wish to call it) composed by the prototype computer program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn’t use endgame tablebases, neural networks or any kind of machine learning found in traditional AI. Chesthetica is able to generate various types of mates and study-like constructs and also compose problems using specific combinations of pieces fed into it (e.g. instructing it to compose something original using only a queen vs. rook, knight and bishop). Learn more about it on ChessBase. Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces.
8/8/3Q4/8/2N2p2/NB5K/1b6/kr2n3 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 20 Nov 2019 at 11:10:16 AM
Solvability Estimate = Difficult
Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. What was the machine ‘thinking’ when it came up with this? If this one is too easy or too difficult for you, try out some of the others. Feel free to copy the position into a chess engine and discover even more variations of the solution.