An Informational Model for Cellular Automata Aesthetic Measure

摘要

This paper addresses aesthetic problem in cellular automata, taking a quantitative approach for aesthetic evaluation. Although the Shannon's entropy is dominant in computational methods of aesthetics, it fails to discriminate accurately structurally different patterns in two-dimensions. We have adapted an informational measure to overcome the shortcomings of entropic measure by using information gain measure. This measure is customised to robustly quantify the complexity of multi-state cellular automata patterns. Experiments are set up with different initial configurations in a two-dimensional multi-state cellular whose corresponding structural measures at global level are analysed. Preliminary outcomes on the resulting automata are promising, as they suggest the possibility of predicting the structural characteristics, symmetry and orientation of cellular automata generated patterns.