Computer-Generated Chess Problem 02803

Here is a ‘KQRP vs kn’ #4 chess puzzle or problem (whichever you wish to call it) composed by Chesthetica using the Digital Synaptic Neural Substrate AI computational creativity method. There is no known limit to the quantity or type of compositions that can be generated.

8/3k1P2/3n4/8/1R6/4Q3/1K6/8 w – – 0 1
White to Play and Mate in 4
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 27 Nov 2019 at 10:08:34 PM
Solvability Estimate = Difficult

Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. It looks like the solution might involve a pawn promotion. Why not time yourself how long it took you to solve this? Solving chess puzzles like this is probably good for your health as it keeps your brain active. Nobody wants something like early-onset Alzheimer’s. If you’re bored of standard chess, though, why not try this?

Solution

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Computer-Generated Chess Problem 02802

Consider this ‘KQBNP vs knp’ chess construct composed autonomously 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. 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 8 pieces goes even beyond that and was therefore composed without any such help.

8/8/K4N2/5nkB/4Q2p/8/5P2/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 27 Nov 2019 at 12:42:47 AM
Solvability Estimate = Difficult

If you notice any version of Chesthetica ‘skipped’ from one problem to the next, that simply means additional (minor) changes were made to the program before it was set to run again. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Try to solve this as quickly as you can. If you like it, please share with others. As a whole, these problems are intended to cater to players of all skill levels.

Solution

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Computer-Generated Chess Problem 02801

Published online for the first time, consider this KQBBNPP vs kqrbnnppp study-like chess problem generated by a computer using the ‘Digital Synaptic Neural Substrate’ computational creativity method. It does not use endgame tablebases, artificial neural networks, machine learning or any kind of typical AI. The position below contains 16 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces. The accuracy of the main line presented for this study in the solution depends on the engine used and analysis time. The constructed position shown is nevertheless original.

2BKb3/1r4N1/2p2Qpk/8/1n6/5p2/1P1P2n1/2B2q2 w – – 0 1
White to Play and Win
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 25 Nov 2019 at 2:38:36 AM

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. Okay, let me think for a minute if there’s anything else to say here. Try to solve this as quickly as you can. If you like it, please share with others. Take some time to study the analysis and you might appreciate the puzzle a little more.

Solution

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Computer-Generated Chess Problem 02800

Here is a new ‘KRBN vs krn’ mate in 3 chess problem generated autonomously by the prototype computer program, Chesthetica, using the ‘Digital Synaptic Neural Substrate’ computational creativity approach which does not use any kind of deep learning. There is no known limit to the quantity or type of compositions that can be generated.

8/8/7B/8/8/2K1n3/8/R1Nkr3 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 22 Nov 2019 at 12:18:36 PM
Solvability Estimate = Difficult

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. 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.

A Similar Problem by Chesthetica: 00794

Solution

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Computer-Generated Chess Problem 02799

A ‘KQBNN vs krbnp’ mate in 3 chess puzzle 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. It doesn’t use endgame tablebases, neural networks or any kind of machine learning found in traditional AI. Chesthetica is able to generate various types of mates and study-like constructs and also compose problems using specific combinations of pieces fed into it (e.g. instructing it to compose something original using only a queen vs. rook, knight and bishop). Learn more about it on ChessBase. Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces.

8/8/3Q4/8/2N2p2/NB5K/1b6/kr2n3 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 20 Nov 2019 at 11:10:16 AM
Solvability Estimate = Difficult

Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. What was the machine ‘thinking’ when it came up with this? If this one is too easy or too difficult for you, try out some of the others. Feel free to copy the position into a chess engine and discover even more variations of the solution.

Solution

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Computer-Generated Chess Problem 02798

Here is a ‘KBN vs kpp’ #4 chess problem generated autonomously by the program, Chesthetica, using the relatively new computational creativity approach called the ‘DSNS’. There is also no proven limit to the quantity or type of legal compositions that can be automatically generated.

8/3p4/8/8/8/8/p7/BkNK4 w – – 0 1
White to Play and Mate in 4
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 19 Nov 2019 at 1:02:27 AM
Solvability Estimate = Easy

These chess puzzles are published in order based on the composition date and time stamp above. Due to the sheer volume of compositions generated, the latest ones may therefore only be published later on. Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. If this one is too easy or too difficult for you, try out some of the others. Take some time to study the analysis and you might appreciate the puzzle a little more.

Similar Problems by Chesthetica: 00273 01215

Solution

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Computer-Generated Chess Problem 02797

An original ‘KQRBNN vs kqp’ chess construct composed autonomously by a computer program, Chesthetica, using the Digital Synaptic Neural Substrate (DSNS) computational creativity approach. It doesn’t use endgame tablebases, deep learning or any kind of traditional AI. There is no known limit to the quantity or type of compositions that can be generated.

B5K1/4N2p/8/5N1k/7q/2Q5/2R5/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 17 Nov 2019 at 1:01:19 AM
Solvability Estimate = Difficult

Chess puzzles are ancient. Some are over a thousand years old but only in the 21st century have computers been able to compose original ones on their own like humans can. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Try to solve this as quickly as you can. If you like it, please share with your friends. 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

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