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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 03212

Here is a new ‘KRRBP vs krb’ chess problem generated autonomously 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. The position below contains 8 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.

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8/8/5B2/7R/3R2b1/5rkP/8/7K w – – 0 1
White to Play and Mate in 3
Chesthetica v12.19 (Selangor, Malaysia)
Generated on 16 Feb 2021 at 4:28:35 PM
Solvability Estimate = Moderate

Now, let’s see what else there is to say. Give me a moment. Try to solve this puzzle. Do try some of the others in the series as well before you go. Take some time to study the analysis and you might appreciate the puzzle a little more.

Solution

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 03211

Here is a ‘KQNN vs kpp’ mate in 4 chess puzzle created by the program, Chesthetica, 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.

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8/8/2Q5/3N4/5K2/2N5/2pp4/2k5 w – – 0 1
White to Play and Mate in 4
Chesthetica v12.19 (Selangor, Malaysia)
Generated on 15 Feb 2021 at 4:32:50 PM
Solvability Estimate = Difficult

Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. White has a decisive material advantage in this position but the winning sequence may not be immediately clear. 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 also help improve your game. If you’re bored of standard chess, though, why not try this?

Solution

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 03210

A newly published and original KQNNPP vs kqrrp forced mate in five 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 11 pieces goes even beyond that and was therefore composed without any such help.

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5q1N/8/8/3Q1P2/3K2kp/4P1Nr/6r1/8 w – – 0 1
White to Play and Mate in 5
Chesthetica v12.19 (Selangor, Malaysia)
Generated on 14 Feb 2021 at 3:44:45 PM
Solvability Estimate = Easy

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 actually has less material than Black. The white army is down by about 3 (Shannon) pawn units in value. Leave a comment below, if you like. Solving chess puzzles like this can also help improve your game. If you’re bored of standard chess, though, why not try this?

A Similar Problem by Chesthetica: 01979

Solution

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 03209

An original ‘KRBN vs krbnp’ three-move chess puzzle or problem (whichever you wish to call it) composed by the program, Chesthetica, using the approach known as the DSNS from the sub-field of AI, computational creativity. The program can compose problems that may otherwise take decades, centuries or even longer for human composers to think of, or to arise in a real game. 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. The position below contains 9 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.

image.png

8/6R1/3NK3/5n1k/6br/7p/8/1B6 w – – 0 1
White to Play and Mate in 3
Chesthetica v12.19 (Selangor, Malaysia)
Generated on 14 Feb 2021 at 9:31:13 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 actually has less material than Black. The white army is down by about 1 (Shannon) pawn units in value. Why not time yourself how long it took you to solve this? Over time, the tactics you see in these puzzles will help you improve your game.

Solution

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 03208

Published online for the first time, consider this KQRR vs kqrrn mate in 4 chess problem generated autonomously by the program, Chesthetica, using the ‘Digital Synaptic Neural Substrate’ computational creativity approach which does not use any kind of deep learning. The position below contains 9 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.

image.png

8/8/8/3rq3/1K6/8/1Q1R2rR/5kn1 w – – 0 1
White to Play and Mate in 4
Chesthetica v12.19 (Selangor, Malaysia)
Generated on 13 Feb 2021 at 8:34:17 AM
Solvability Estimate = Moderate

Now, let’s see what else there is to say. Give me a moment. Try to solve this puzzle. Do try some of the others in the series as well before you go. Take some time to study the analysis and you might appreciate the puzzle a little more.

Solution

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