Consider this 'KQNN vs kqrb' chess puzzle or problem (whichever you wish to call it) composed by a computer program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. The DSNS does not use endgame tablebases, neural networks or any kind of machine learning found in traditional artificial intelligence (AI). It also has nothing to do with deep learning. There is no known limit to the quantity or type of compositions that can be generated. The largest (Lomonosov) tablebase today is for 7 pieces which contains over 500 trillion positions. With each additional piece, the number of possible positions increases exponentially. It is therefore impossible that this problem with 8 pieces could have been taken from such a database.
White to Play and Mate in 3
Chesthetica v11.09 (Selangor, Malaysia)
Generated on 15 Apr 2019 at 11:52:05 AM
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. Okay, let me think for a minute if there's anything else to say here. Leave a comment below, if you like. Solving chess puzzles like this can be good for your health as it keeps your brain active. It may even delay or prevent dementia. 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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