artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02619

Consider this ‘KRBB vs kp’ mate in 3 chess problem generated autonomously by Chesthetica 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 chess board is a virtually limitless canvas for the expression of creative ideas (even by computer).

8/8/8/B7/8/1p6/6B1/3k1K1R w – – 0 1
White to Play and Mate in 3
Chesthetica v11.17 (Selangor, Malaysia)
Generated on 20 Apr 2019 at 5:01:26 PM
Solvability Estimate = Moderate

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

Similar Problems by Chesthetica: 00296 00342 00525 01664 01924 02162

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02424

Now, here we have a ‘KRRBBBPP vs kqrbpp’ mate in 4 chess problem generated 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. 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 14 pieces goes even beyond that and was therefore composed without any such help.

5r2/BR6/2Pk4/5b2/K3pP2/1B3R2/B2p2q1/8 w – – 0 1
White to Play and Mate in 4
Chesthetica v10.82 : Selangor, Malaysia
2018.12.9 8:35:57 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. 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.

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02354

Contemplate this ‘KQQN vs krrnp’ chess problem generated autonomously by a computer program, Chesthetica, using the relatively new computational creativity approach called the ‘DSNS’. Chesthetica is capable of composing positions that may otherwise take centuries or longer to arise in an actual game; so you can enjoy them right now instead.

6k1/2r2p2/r4Q2/6NK/8/2n5/8/2Q5 w – – 0 1
White to Play and Mate in 4
Chesthetica v10.82 : Selangor, Malaysia
2018.11.5 4:25:55 AM
Solvability Estimate = Difficult

Okay, let me think for a minute if there’s anything else to say here. 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.

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02353

A new if not unique KRBNN vs kbpp chess problem generated by the 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 mates in 3, mates in 4, mates in 5, study-like constructs and also compose problems using specific combinations of pieces fed into it (such as using only a queen vs. rook and knight). Read more about it on ChessBase.

8/8/4b3/8/1R6/Kp6/B4pN1/k3N3 w – – 0 1
White to Play and Mate in 5
Chesthetica v10.78 : Selangor, Malaysia
2018.11.5 12:38:46 AM
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 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. 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?

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02352

Contemplate this ‘KQB vs kqq’ #4 chess puzzle created by a computer using the ‘DSNS’ computational creativity approach which does not use any kind of machine or deep learning.

8/1K6/8/B5q1/8/3Q4/8/q6k w – – 0 1
White to Play and Mate in 4
Chesthetica v10.82 : Selangor, Malaysia
2018.11.4 1:19:38 PM
Solvability Estimate = Moderate

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. Okay, let me think for a minute if there’s anything else to say here. 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.

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02351

Contemplate this ‘KQPPP vs kqbp’ #5 chess puzzle created by the 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. 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 9 pieces goes even beyond that and was therefore composed without any such help.

8/1q4Pp/4P2k/8/2K5/5QPb/8/8 w – – 0 1
White to Play and Mate in 5
Chesthetica v10.82 : Selangor, Malaysia
2018.11.3 9:44:28 AM
Solvability Estimate = Easy

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 yet still wins. The white army is down by about 1 (Shannon) pawn units in value. Leave a comment below, if you like. Take some time to study the analysis and you might appreciate the puzzle a little more.

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

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02350

Take a look at this ‘KBNPPP vs kbnn’ chess problem generated autonomously by a 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. 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.

5b2/3PknB1/2Pn1N2/6P1/5K2/8/8/8 w – – 0 1
White to Play and Mate in 3
Chesthetica v10.82 : Selangor, Malaysia
2018.11.2 11:42:08 PM
Solvability Estimate = Moderate

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. Get a glimpse into the ‘mind’ of a computer composer. 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. Collectively, these puzzles are intended to cater to players of all levels.

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

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