A newly published and original KRNNNPP vs k chess problem generated 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 mates in 3, mates in 4, mates in 5, study-like constructs and also compose problems using specific combinations of pieces fed into it. Read more about it on ChessBase. This position contains a total of 8 pieces. The largest endgame tablebase in existence today is for 7 pieces (containing over 500 trillion positions anyway) which means the problem could not have been taken from it regardless.
White to Play and Mate in 4
Chesthetica v10.57 : Selangor, Malaysia
2018.1.6 4:02:33 AM
If you notice an earlier version of Chesthetica listed with a newer problem, that simply means an earlier version may have been running on a different computer or OS user account. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Do you think you could have composed something better with these pieces? Share in the comments and let us know how long it took you. Feel free to copy the position into a chess engine and discover even more variations of the solution.
Solution (Skip to 0:35)
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