artificial intelligence, chess, games, puzzles, Uncategorized

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.

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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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artificial intelligence, chess, games, puzzles, Uncategorized

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.

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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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artificial intelligence, chess, games, puzzles, Uncategorized

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.

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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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artificial intelligence, chess, games, puzzles, Uncategorized

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.

image.png

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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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02796

A newly published and original KRBBN vs kr three-move chess construct composed autonomously by the prototype computer program, Chesthetica, using the computational creativity approach which doesn’t use any kind of traditional AI or even deep learning. Chesthetica has the creative ability to compose positions on an 8×8 canvas that may otherwise take centuries to arise in an actual game, if ever. Learn about how these puzzles are selected here.

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4N1K1/4k2B/8/B7/1r6/8/6R1/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.55 (Selangor, Malaysia)
Generated on 16 Nov 2019 at 5:33:07 PM
Solvability Estimate = Difficult

Humans have been composing original chess problems for over a thousand years. Now a computer can do it too. 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. 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 02793

Now, here we have a ‘KRBBP vs kb’ mate in 3 chess puzzle or problem (whichever you wish to call it) composed by the prototype computer program, Chesthetica, using the approach known as the DSNS from the sub-field of AI, computational creativity. There is no known limit to the quantity or type of compositions that can be generated.

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8/6K1/RB6/6k1/2b5/6P1/6B1/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.54 (Selangor, Malaysia)
Generated on 13 Nov 2019 at 12:04:22 PM
Solvability Estimate = Difficult

Humans have been composing original chess problems for over a thousand years. Now a computer can do it too. White is over a rook’s worth in material but the precise win in this position still needs to be found. 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.

Solution

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02792

Here is a new ‘KQBNN vs kqrb’ mate in 3 chess problem generated by a computer using the approach known as the DSNS from the sub-field of AI, computational creativity. There is no known limit to the quantity or type of compositions that can be generated. This position contains a total of 9 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.

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8/8/4Q3/4NN2/3K4/5B2/3b1k1q/6r1 w – – 0 1
White to Play and Mate in 3
Chesthetica v11.54 (Selangor, Malaysia)
Generated on 11 Nov 2019 at 8:31:11 PM
Solvability Estimate = Difficult

Composing a chess puzzle or problem requires creativity and it’s not easy even for most humans. Chesthetica composes everything autonomously (no human intervention) and even chooses the main line of the solution to show you. Why not time yourself how long it took you to solve this? Feel free to copy the position into a chess engine and discover even more variations of the solution. If you’re bored of standard chess, though, why not try this?

Solution

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