Increasing Efficiency and Quality in the Automatic Composition of Three-Move Mate Problems

In this article, we demonstrate the use of composing ‘experience’ in the form of piece location probability values derived from a database of matein-3 chess problems. This approach was compared against a ‘random’ one. Comparisons were made using ‘experiences’ derived from three different databases, i.e. problems by human composers (HC), computer-generated compositions that used the HC experience (CG), and mating ‘combinations’ taken from tournament games between humans (TG). Each showed a reasonable and statistically significant increase in efficiency compared to the random one but not each other. Aesthetically, the HC and CG were better than the others. The results suggest that composing efficiency and quality can be improved using simple probability information derived from human compositions, and unexpectedly even from the computer-generated compositions that result. Additionally, these improvements come at a very low computational cost. They can be used to further aid and entertain human players and composers.