Consider this 'KQRR vs krrbnnp' chess problem generated autonomously by the prototype 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. Chesthetica is able to generate mates in 3, mates in 4, mates in 5, study-like constructs and also compose problems using specific combinations of pieces fed into it (e.g. composing something original using only three pawns vs. a knight). Read more about it on ChessBase.
White to Play and Mate in 3
Chesthetica v10.82 : Selangor, Malaysia
2018.10.19 10:58:24 AM
The chess problems are published chronologically based on the composition date and time. However, later compositions may have an earlier version of Chesthetica listed because more than one computer (not all running the same version of the program) is used. White actually has less material than Black yet still wins. 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? Solving chess puzzles like this can be good for your health as it keeps your brain active. It may even delay or prevent dementia. If you're bored of standard chess, though, why not try this?
Main Line of the Solution (Skip to 0:35)
<| Book | DTube | Facebook | Reddit | Twitter | Website |>