Towards the efficient evolution of particle-based computation in cellular automata
Dávid Iclănzan, Péter István Fülöp, Camelia Chira, Anca Andreica · 2011
A fast compression based technique is proposed, capable of detecting promising emergent space-time patterns of cellular automata (CA). This information can be used to automatically guide the evolutionary search toward more complex, better performing rules. Results are presented for the most widely studied CA computation problem, the Density Classification Task (DCT), where incorporation of the proposed method almost always pushes the search beyond the simple block-expanding rules.