Computer-Generated Chess Problem 02615 A 'KQRRN vs kqbnpp' four-move chess problem generated autonomously 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. (Learn more about the DSNS by googling 'Digital Synaptic Neural Substrate'). Any chess position over 7 pieces could not possibly have been derived from an endgame tablebase which today is limited to 7 pieces. https://www.youtube.com/watch?v=cJcV_I32QOs 2k3b1/8/3R1p2/1N5K/5R2/Qn5p/8/7q w - - 0 1 White to Play and Mate in 4 Chesthetica v11.17 (Selangor, Malaysia) Generated on 19 Apr 2019 at 2:49:14 PM Solvability Estimate = Difficult The chess problems are published chronologically based on the composition date and time. However, later compositions may have an earlier version of Chesthetica listed because more than one computer (not all running the same version of the program) is used. White is significantly ahead in material. Why not time yourself how long it took you to solve this? Collectively, these puzzles are intended to cater to players of all levels. #chess #gaming #art #technology
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