artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02931

A newly published and original KQBNP vs kbn #3 chess problem generated by a computer program, Chesthetica, using the ‘DSNS’ computational creativity approach which does not use any kind of machine or deep learning. You can learn more about the DSNS here. 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.

image.png

kBb1N3/1n6/1P5Q/8/8/8/8/6K1 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.69 (Selangor, Malaysia)
Generated on 23 May 2020 at 12:13:24 AM
Solvability Estimate = Difficult

Chesthetica, especially if running on multiple computers or operating system user accounts, is capable of generating far too many compositions than can be published in a timely fashion here. The newer ones will therefore only be published some time later. This is why the composition date above does not match today’s date. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. Leave a comment below, if you like. Solving chess puzzles like this can also help improve your game.

Solution

Facebook | Instagram | Twitter | Book | Website

artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02923

Here is a new ‘KRBP vs krbn’ #3 chess puzzle or problem (whichever you wish to call it) composed by a 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. You can learn more about the DSNS here. 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 8 pieces goes even beyond that and was therefore composed without any such help whatsoever.

image.png

k1rn4/b1R5/B1P5/8/8/8/K7/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.68 (Selangor, Malaysia)
Generated on 18 May 2020 at 12:00:30 PM
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 actually has less material than Black. The white army is down by about 2 (Shannon) pawn units in value. Do share and try out some of the others too. Over time, the tactics you see in these puzzles will help you improve your game.

Solution

Facebook | Instagram | Twitter | Book | Website

artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02921

Now, here we have a ‘KRBNP vs krn’ mate in 3 chess puzzle created by a computer using the ‘DSNS’ computational creativity approach which does not use any kind of machine or deep learning. Chesthetica is able to use the technology to express original creative thought in this domain. It also never had behind it a team of highly skilled programmers, consultants or the kind of hardware millions of IBM or Google dollars could buy. There is no known limit to the quantity or type of compositions that can be generated. 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.

image.png

8/n2R4/k1P5/1r6/4K3/1N6/4B3/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.68 (Selangor, Malaysia)
Generated on 16 May 2020 at 12:12:47 PM
Solvability Estimate = Difficult

If you notice an earlier version of Chesthetica listed with a newer problem, that simply means an earlier version may have been running on a different computer or OS user account. Everything composed by Chesthetica is original. Try to solve this as quickly as you can. If you like it, please share with others. Solving chess puzzles like this can also help improve your game.

Solution

Amazon | BitChute | Hive | Minds | Reddit | YouTube

artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02920

Published online for the first time, consider this KQRBBN vs krbp mate in 3 chess puzzle or problem (whichever you wish to call it) composed 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. 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 10 pieces goes even beyond that and was therefore composed without any such help whatsoever.

image.png
4K3/6p1/1Q2b1rk/6NB/4R3/4B3/8/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.69 (Selangor, Malaysia)
Generated on 15 May 2020 at 2:56:04 AM

Solvability Estimate = Difficult

Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. Chesthetica composes only unique or new constructs. If you have seen it before, cite the source and comment below because it is purely coincidental. If this one is too easy or too difficult for you, try out some of the others. Over time, the tactics you see in these puzzles will help you improve your game. If you’re bored of standard chess, though, why not try this?

Solution

Amazon | BitChute | Minds | Reddit | Steemit | YouTube

artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02918

Now, here we have a ‘KBBNN vs krrbpp’ chess problem generated by the prototype 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. Noteworthy here is that a chess position with over 7 pieces could not have been derived or taken from an endgame tablebase because 7 pieces is the present limit.

image.png

8/8/3r4/8/2N2pr1/5kp1/2BB2b1/3N2K1 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.69 (Selangor, Malaysia)
Generated on 13 May 2020 at 8:38:34 PM
Solvability Estimate = Difficult

The chess problems are published chronologically based on the composition date and time. However, later compositions may have an earlier version of Chesthetica listed because more than one computer (not all running the same version of the program) is used. Everything composed by Chesthetica is original. 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. Over time, the tactics you see in these puzzles will help you improve your game.

Solution

Facebook | Instagram | Twitter | Book | Website