Now, this is a 'KRRBP vs kqr' mate in 5 chess problem generated autonomously by the prototype computer 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. 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. This position contains a total of 8 pieces. The largest endgame tablebase in existence today is for 7 pieces (containing over 500 trillion positions anyway) which means the problem could not have been taken from it regardless.
White to Play and Mate in 5
Chesthetica v10.63 : Selangor, Malaysia
2018.5.2 1:34:48 PM
Okay, let me think for a minute if there's anything else to say here. If this one is too easy or too difficult for you, try out some of the others. Note that not all the chess problems are like this. They cover quite the spectrum of solving ability and there are thousands published already.
Solution (Skip to 0:35)
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