Computer-Generated Chess Problem 04060

in #chess3 years ago

Published online for the first time, consider this KQRPP vs kqrbp chess construct composed autonomously by 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. You can learn more about the DSNS here. Any chess position over seven pieces would likely not have been derived from an endgame tablebase which today is limited to seven pieces. Work has only recently begun on one for eight pieces.

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k7/rqP5/8/pb2R3/3P4/2KQ4/8/8 w - - 0 1
White to Play and Mate in 5
Chesthetica v12.65 (Selangor, Malaysia)
Generated on 11 Apr 2023 at 10:24:35 PM
Solvability Estimate = Moderate

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. White has a pawn for Black's bishop. If this one is too easy or too difficult for you, try out some of the others. Collectively, these puzzles are intended to cater to players of all levels. Anyway, if standard chess isn't your thing, you might instead like SSCC.

Solution

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