What we have here is a 'KRR vs kr' three-move chess problem generated autonomously by 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. 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.
White to Play and Mate in 3
Chesthetica v10.62 : Selangor, Malaysia
2018.3.5 7:15:08 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. White is significantly ahead in material. Did you find this one interesting or have something else to say? Leave a comment below! Collectively, these puzzles are intended to cater to players of all levels.
Solution (Skip to 0:35)
< | Facebook | Twitter | Get the Book | Website | Reddit| >