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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02144

Consider this ‘KRRNNPPP vs kqqbppp’ #5 chess puzzle created by 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. 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 15 pieces which means it simply could not have been derived even from an existing endgame tablebase which is presently limited to 7 pieces.

q5k1/3PK3/4b1P1/3NPRR1/8/1q6/1ppp4/4N3 w – – 0 1
White to Play and Mate in 5
Chesthetica v10.67 : Selangor, Malaysia
2018.6.12 10:29:00 PM
Solvability Estimate = Easy

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 is probably good for your health as it keeps your brain active. Nobody wants something like early-onset Alzheimer’s.

Solution (Skip to 0:35)

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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02143

Take a look at this ‘KRR vs kb’ #4 chess problem generated autonomously by a computer 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. There is no known limit to the quantity or type of compositions that can be generated.

k7/8/8/K4b2/4R3/8/1R6/8 w – – 0 1
White to Play and Mate in 4
Chesthetica v10.67 : Selangor, Malaysia
2018.6.12 6:34:51 PM
Solvability Estimate = Difficult

White is over a rook’s worth in material but the precise win in this position still needs to be found. If this one is too easy or too difficult for you, try out some of the others. Collectively, these puzzles are intended to cater to players of all levels. If you’re bored of standard chess, though, why not try this?

Solution (Skip to 0:35)

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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02142

This is an original ‘KQRBNNP vs kqrrbbn’ study-like construct or chess problem generated by the prototype computer program, Chesthetica, using the ‘Digital Synaptic Neural Substrate’ computational creativity approach which does not use any kind of deep learning. After years of development, Chesthetica is able to use the technology to express original creative thought in this domain. Note that it also never had millions of IBM or Google dollars behind it. There is no known limit to the quantity or type of compositions that can be generated. The largest (Lomonosov) tablebase today is for 7 pieces which contains over 500 trillion positions. With each additional piece, the number of possible positions increases exponentially. It is therefore impossible that this problem with 14 pieces could have been taken from such a database. The analysis presented for this study may not be perfect as it depends on the engine used and time allocated to it. However, the key move should be right.

1K1R4/4b3/1k6/1N6/3r3q/2P1B3/2nN2r1/3Q3b w – – 0 1
Chesthetica v10.67 : Selangor, Malaysia
White to Play and Win : 2018.6.12 5:10:13 PM

Some of the earliest chess problems by humans are over 10 centuries old but original ones by computer are very recent. Now, let’s see what else there is to say. Give me a moment. Try to solve this as quickly as you can. If you like it, please share with others. Collectively, these puzzles are intended to cater to players of all levels.

Solution (Skip to 0:35)

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artificial intelligence, chess, games, puzzles, Uncategorized

Computer-Generated Chess Problem 02141

Contemplate this ‘KQBNN vs kqn’ chess problem generated by Chesthetica using the computational creativity approach which doesn’t use any kind of traditional AI or even deep learning. 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.

8/4N2q/6N1/B1K5/7n/5k2/8/6Q1 w – – 0 1
White to Play and Mate in 5
Chesthetica v10.67 : Selangor, Malaysia
2018.6.12 3:27:29 PM
Solvability Estimate = Moderate

Humans have been composing original chess problems for over a thousand years. Now a computer can do it too. Remarkably, Chesthetica never composes duplicate problems using its DSNS technology. Try to solve this as quickly as you can. If you like it, please share with your friends. Feel free to copy the position into a chess engine and discover even more variations of the solution.

Solution (Skip to 0:35)

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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02140

A new if not unique KRBNPP vs krbnpp chess puzzle created by a computer using the Digital Synaptic Neural Substrate AI computational creativity method. There is no known limit to the quantity or type of compositions that can be generated. This position contains a total of 12 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.

3B4/7b/2K1k3/P7/2p2RPn/6r1/3Np3/8 w – – 0 1
Chesthetica v10.67 : Selangor, Malaysia
White to Play and Win : 2018.6.12 7:20:17 AM

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. Material is even. The white and black armies also have the same pieces, which is rare for a computer composition. 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 (Skip to 0:35)

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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02139

Consider this ‘KQRRBNPP vs kqrrbnnp’ study construct 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. 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.

6n1/5K2/R7/1kr5/3n4/PN2PQpR/1b1B4/3q2r1 w – – 0 1
Chesthetica v10.67 : Selangor, Malaysia
White to Play and Win : 2018.6.11 8:31:51 PM

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. Now, let’s see what else there is to say. Give me a moment. Try to solve this as quickly as you can. If you like it, please share with others. Collectively, these puzzles are intended to cater to players of all levels.

Solution (Skip to 0:35)

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Uncategorized, chess, artificial intelligence, games, puzzles

Computer-Generated Chess Problem 02138

This is an original ‘KRRP vs knn’ five-move chess puzzle or problem (whichever you wish to call it) composed 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. You can learn more about the DSNS here.

1Rn2n2/8/8/8/2K5/8/RP6/2k5 w – – 0 1
White to Play and Mate in 5
Chesthetica v10.67 : Selangor, Malaysia
2018.6.11 5:23:43 PM
Solvability Estimate = Moderate

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 as quickly as you can. If you like it, please share with others. 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 (Skip to 0:35)

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