Here is a new 'KRRNPPP vs kqrp' mate in 4 chess problem generated by a computer 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. The largest endgame tablebase in existence today is for 7 pieces (Lomonosov) which contains over 500 trillion positions, most of which have not been seen by human eyes. This problem with 11 pieces goes even beyond that and was therefore composed without any such help.
White to Play and Mate in 4
Chesthetica v10.74 : Selangor, Malaysia
2018.8.5 7:44:57 PM
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 has a slight material advantage over Black. Did you find this one interesting or have something else to say? Leave a comment below! Note that not all the chess problems are like this. They cover quite the spectrum of solving ability and there are thousands published already. Anyway, if standard chess isn't your thing, you might instead like SSCC.
Main Line of the Solution (Skip to 0:35)
<| Amazon | BitChute | Minds | WordPress | YouTube |>