Computer-Generated Chess Problem 03067
Consider this 'KQRBBNN vs kqbnpp' mate in 4 chess puzzle created by the program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn't use endgame tablebases, neural networks or any kind of machine learning found in traditional AI. There is no known limit to the quantity or type of compositions that can be generated. The largest endgame tablebase in existence today is for 7 pieces (Lomonosov) which contains over 500 trillion positions, most of which have not and never will be seen by human eyes. This problem with 13 pieces goes even beyond that and was therefore composed without any such help whatsoever.
![image.png](https://steemitimages.com/640x0/https://cdn.steemitimages.com/DQmUih4ebnTqV5rKWBUc1sCHyuRqQN6wCzb3SP84ixJSAgC/image.png)
White to Play and Mate in 4
Chesthetica v11.89 (Selangor, Malaysia)
Generated on 30 Sep 2020 at 12:00:45 AM
Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. Get a glimpse into the 'mind' of a computer composer. Try to solve this puzzle. Do try some of the others in the series as well before you go. Some of these problems may be trivial for you, especially if you're a club or master player but bear in mind that chess lovers can be found at all levels of play. So do check out some of the other problems. You can probably find something more to your taste.
Solution