Now, this is a 'KQBN vs kbnnpp' study construct generated by a 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. 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 10 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. The analysis presented for this study may not be perfect as it depends on the engine used and time allocated to it. However, the key move should be right.
White to Play and Win
Chesthetica v11.04 (Selangor, Malaysia)
Generated on 4 Mar 2019 at 10:06:02 PM
Chess puzzles are ancient. Some are over a thousand years old but only in the 21st century have computers been able to compose original ones on their own like humans can. Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. Did you find this one interesting or have something else to say? Leave a comment below! Over time, the tactics you see in these puzzles will help you improve your game. Anyway, if standard chess isn't your thing, you might instead like SSCC.
Main Line of the Solution (Skip to 0:35)
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