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Published online for the first time, consider this KQNPP vs kqbn mate in 4 chess puzzle created by the prototype computer program, Chesthetica, using the 'Digital Synaptic Neural Substrate' computational creativity method. It does not use endgame tablebases, artificial neural networks, machine learning or any kind of typical 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 (e.g. instructing it to compose something using a queen, rook and bishop vs. queen and two knights). (Read more about it on ChessBase: https://en.chessbase.com/tagged?tag=Chesthetica). The largest endgame tablebase in existence today is for 7 pieces (Lomonosov) which contains over 500 trillion positions, most of which have not been seen by human eyes. This problem with 9 pieces goes even beyond that and was therefore composed without any such help.
2nkb3/N2q4/3PP3/8/1K6/6Q1/8/8 w - - 0 1
White to Play and Mate in 4
Chesthetica v11.32 (Selangor, Malaysia)
Generated on 9 Aug 2019 at 9:31:57 PM
Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. Why not time yourself how long it took you to solve this? Note that not all the chess problems are like this. They cover quite the spectrum of solving ability and there are thousands published already.
Related Books: http://amazon.com/author/azlan_iqbal
Artwork licensed under Creative Commons (CC0).
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