artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02633

Here is a ‘KQNP vs kqbp’ #3 chess problem generated autonomously by the program, Chesthetica, using the DSNS computational creativity approach which doesn’t use any kind of traditional AI. Chesthetica has the creative ability to compose positions that may otherwise take centuries to arise in an actual game, if ever. 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 8 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

1Q6/8/PNkb4/8/1p1K4/1q6/8/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.17 (Selangor, Malaysia)
Generated on 28 Apr 2019 at 2:04:59 AM
Solvability Estimate = Moderate

Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. Get a glimpse into the ‘mind’ of a computer composer. Try to solve this puzzle. Do try some of the others in the series as well before you go. As a whole, these problems are intended to cater to players of all skill levels. Anyway, if standard chess isn’t your thing, you might instead like SSCC.

Main Line of the Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02632

Consider this ‘KQRNP vs kqrrp’ #3 chess problem generated autonomously by the prototype computer program, Chesthetica, using the Digital Synaptic Neural Substrate AI computational creativity method. There is also no proven limit to the quantity or type of legal compositions that can be automatically generated. Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces.

image.png

5q2/5r2/3kP1K1/N6r/5p2/8/5Q2/4R3 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.17 (Selangor, Malaysia)
Generated on 27 Apr 2019 at 4:55:05 PM
Solvability Estimate = Difficult

Humans have been composing original chess problems for over a thousand years. Now a computer can do it too. Everything composed by Chesthetica is original. Do share and try out some of the others too. 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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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02631

A ‘KRNNP vs kqbnp’ #4 chess problem generated autonomously by a computer 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 10 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

6k1/qR6/3K4/3Np3/3N1b2/3nP3/8/8 w – – 0 1
White to Play and Mate in 4
Chesthetica v11.16 (Selangor, Malaysia)
Generated on 27 Apr 2019 at 12:58:39 PM
Solvability Estimate = Moderate

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. White actually has less material than Black. The white army is down by about 4 (Shannon) pawn units in value. If this one is too easy or too difficult for you, try out some of the others. As a whole, these problems are intended to cater to players of all skill levels.

Main Line of the Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02630

An original ‘KQBB vs krnp’ #3 chess problem generated 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 various types of mates and study-like constructs and also compose problems using specific combinations of pieces fed into it (e.g. compose something original using a knight versus three pawns). Learn more about it on ChessBase. 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

8/3B4/K2p4/2k5/8/1Q1nr3/8/4B3 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.16 (Selangor, Malaysia)
Generated on 24 Apr 2019 at 6:46:41 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 is over a rook’s worth in material but the precise win in this position still needs to be found. Leave a comment below, if you like. Solving chess puzzles like this can also help improve your game.

Main Line of the Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02629

A newly published and original KQB vs kqb mate in 3 chess puzzle created 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.

image.png

4K3/8/2Bq4/4bk2/7Q/8/8/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.17 (Selangor, Malaysia)
Generated on 23 Apr 2019 at 6:22:52 PM
Solvability Estimate = Moderate

Humans have been composing original chess problems for over a thousand years. Now a computer can do it too. Everything composed by Chesthetica is original. Did you find this one interesting or have something else to say? Leave a comment below! Note that not all the chess problems are like this. They cover quite the spectrum of solving ability and there are thousands published already.

A Similar Problem by Chesthetica: 00968

Main Line of the Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02628

Now, here we have a ‘KRNN vs kpp’ #5 chess puzzle created by a computer using the DSNS computational creativity approach which doesn’t use any kind of traditional AI. Chesthetica has the creative ability to compose positions that may otherwise take centuries to arise in an actual game, if ever. You can learn about how these constructs are selected here.

image.png

3N4/8/5p2/7R/k7/1N6/6p1/2K5 w – – 0 1
White to Play and Mate in 5
Chesthetica v11.17 (Selangor, Malaysia)
Generated on 23 Apr 2019 at 4:04:37 PM
Solvability Estimate = Easy

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 is over a rook’s worth in material but the precise win in this position still needs to be found. 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 is probably good for your health as it keeps your brain active. Nobody wants something like early-onset Alzheimer’s.

Similar Problems by Chesthetica: 00499 02032 02335

Main Line of the Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02627

Take a look at this ‘KQRBNN vs kqrnp’ chess construct composed autonomously 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. Any chess position with this many pieces could not possibly have been obtained from known endgame databases. Chesthetica is therefore the real McCoy.

image.png

8/4K3/1r3R2/p7/3n4/1N5N/4k3/1QB1q3 w – – 0 1
White to Play and Mate in 4
Chesthetica v11.16 (Selangor, Malaysia)
Generated on 23 Apr 2019 at 11:58:15 AM
Solvability Estimate = Moderate

Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. White is significantly ahead in material. Try to solve this as quickly as you can. If you like it, please share with your friends. Collectively, these puzzles are intended to cater to players of all levels. If you’re bored of standard chess, though, why not try this?

Main Line of the Solution (Skip to 0:35)

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