Take a look at this 'KQBB vs kqbbp' study-like construct or chess problem generated by Chesthetica using the 'Digital Synaptic Neural Substrate' 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. Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces. 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 v11.62 (Selangor, Malaysia)
Generated on 27 Jan 2020 at 12:08:34 PM
Chesthetica, especially if running on multiple computers or operating system user accounts, is capable of generating far too many compositions than can be published in a timely fashion here. The newer ones will therefore only be published some time later. This is why the composition date above does not match today's date. White actually has less material than Black. The white army is down by about 1 (Shannon) pawn units in value. Why not time yourself how long it took you to solve this? Take some time to study the analysis and you might appreciate the puzzle a little more. Anyway, if standard chess isn't your thing, you might instead like SSCC.
Solution
<| Book | DTube | Facebook | Instagram | Twitter | Website |>