Contemplate this 'KQRBN vs krn' mate in three chess problem generated autonomously by a computer using the DSNS computational creativity method. It does not use endgame tablebases, artificial neural networks, machine learning or any kind of typical AI. The chess board is a virtually limitless canvas for the expression of creative ideas (even by computer). 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 eight pieces. The largest complete endgame tablebase in existence today is for seven pieces (containing over 500 trillion positions anyway) which means the problem could not have been taken from it regardless.
White to Play and Mate in 3
Chesthetica v12.50 (Selangor, Malaysia)
Generated on 15 Mar 2022 at 9:44:20 PM
Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Try to solve this as quickly as you can. If you like it, please share with others. Over time, the tactics you see in these puzzles will help you improve your game.
A Similar Chess Problem by Chesthetica: 00299