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Computer-Generated Chess Problem 02303

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First published at 23:18 UTC on September 11th, 2019.

Chesthetica

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What we have here is a 'KRRBBN vs kbn' mate in 4 chess problem generated by the 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. Depending on the type and complexity of the problem desired, a single instance of Chesthetica running on a desktop computer can probably generate anywhere between one and ten problems per hour. 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.

8/1K1RR3/8/N7/3B4/1B1b4/3k4/6n1 w - - 0 1
White to Play and Mate in 4
Chesthetica v10.77 : Selangor, Malaysia
2018.9.29 8:04:41 PM

Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. 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.

Artwork licensed under Creative Commons (CC0).

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