Now, this is a 'KRNPPPP vs krbbppp' study-like construct or problem (whichever you wish to call it) composed 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. to compose something using a rook, bishop, knight and three pawns vs. a queen and a rook). Read more about it on ChessBase. This position contains a total of 14 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. The solution shown for this study may not be the best line possible because it depends on the engine that was used and how much time it had to analyze. Regardless, the first move and overall evaluation (e.g. win, draw) should be right.
Chesthetica v10.69 : Selangor, Malaysia
White to Play and Draw : 2018.8.6 7:31:35 PM
Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. Do you think you could have composed something better with these pieces? Share in the comments and let us know how long it took you. Solving chess puzzles like this can be good for your health as it keeps your brain active. It may even delay or prevent dementia.
Main Line of the Solution (Skip to 0:35)
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