Here is a new 'KRRBBN vs kqbn' 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 position below contains 10 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.
White to Play and Mate in 4
Chesthetica v10.64 : Selangor, Malaysia
2018.5.13 6:57:56 PM
A seemingly earlier version of Chesthetica on a problem composed later (based on the date and time stamp) simply means that version may have been running on a different computer or operating system user account. White is significantly ahead in material. 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.
Solution (Skip to 0:35)
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