Enumeration of Tsume-Shogi Diagrams by the Reverse Method
ICKS '08 Proceedings of the International Conference on Informatics Education and Research for Knowledge-Circulating Society (icks 2008)
Evaluation of Economy in a Zero-sum Perfect Information Game
The Computer Journal
A corpus-based hybrid approach to music analysis and composition
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
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CG'06 Proceedings of the 5th international conference on Computers and games
Artificial Dreams: The Quest for Non-Biological Intelligence
Artificial Dreams: The Quest for Non-Biological Intelligence
IEEE Spectrum
Conceptualizing Birkhoff's aesthetic measure using Shannon entropy and Kolmogorov complexity
Computational Aesthetics'07 Proceedings of the Third Eurographics conference on Computational Aesthetics in Graphics, Visualization and Imaging
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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.