The Digital Synaptic Neural Substrate: Size and Quality Matters
This work addresses an incremental improvement for researchers in computational creativity seeking to enhance DSNS-based puzzle generation.
The study tackled the problem of improving output quality in the Digital Synaptic Neural Substrate (DSNS) computational creativity approach by investigating the impact of image size and quality, finding that larger and clearer images lead to better results, though the reasons are not well-understood.
We investigate the 'Digital Synaptic Neural Substrate' (DSNS) computational creativity approach further with respect to the size and quality of images that can be used to seed the process. In previous work we demonstrated how combining photographs of people and sequences taken from chess games between weak players can be used to generate chess problems or puzzles of higher aesthetic quality, on average, compared to alternative approaches. In this work we show experimentally that using larger images as opposed to smaller ones improves the output quality even further. The same is also true for using clearer or less corrupted images. The reasons why these things influence the DSNS process is presently not well-understood and debatable but the findings are nevertheless immediately applicable for obtaining better results.