Computer-Generated Chess Problem 01864
A new if not unique KQRN vs krrbppp mate in 3 chess problem generated autonomously by 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. The position below contains 11 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.
White to Play and Mate in 3
Chesthetica v10.59 : Selangor, Malaysia
2018.1.24 1:37:08 AM
White has a slight material advantage over Black. Leave a comment below if you like. Collectively, these puzzles are intended to cater to players of all levels.
Solution (Skip to 0:35)
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