A newly published and original KRRNN vs kqrr mate in 3 chess problem generated autonomously by a computer 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. There is also no proven limit to the quantity or type of legal compositions that can be automatically generated. This position contains a total of 9 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 3
Chesthetica v10.82 : Selangor, Malaysia
2018.12.8 6:58:38 AM
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? 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.
Main Line of the Solution (Skip to 0:35)
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