Computer-Generated Chess Problem 03197

Take a look at this 'KRNPPP vs kqbbn' three-move chess problem generated 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. The chess board is a virtually limitless canvas for the expression of creative ideas (even by computer). Chesthetica is able to generate mates in 2, mates in 3, mates in 4, mates in 5, 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). 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. R7/2P2k1P/2K1bnqb/7P/5N2/8/8/8 w - - 0 1 White to Play and Mate in 3 Chesthetica v12.19 (Selangor, Malaysia) Generated on 4 Feb 2021 at 6:39:08 AM Solvability Estimate = Difficult Even with the same version number, each copy of Chesthetica 'evolves' and performs somewhat differently over time. 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. #chess #gaming #art #technology