A Fast Method for Classification of Emergent Dynamics in Cellular Automata Based on Uncertainty Profiles
- Authors
-
-
Radu Dogaru
Dept. of Applied Electronics and Information Engineering, University "Politehnica" of Bucharest, Bvd. Iuliu Maniu 1-3, Romania
-
- Abstract
- A new and efficient method to classify cellular automata is presented and exemplified here for the case of elementary cellular automata (ECA) with 3 cells neighborhood. The approach has an important advantages over other methods: It is extremely fast since it does not require the simulation of the cellular automaton dynamics, instead all classification process is based on a uncertainty profile computed rapidly for a given cell logic and neighborhood. The method may be easily generalized to more complex cellular neighborhoods. A comparison with another recent ECA classification method (based on a completely different approach, namely on the iterated maps theory in nonlinear dynamics) reveals a strong overlap between results.
- References
- Downloads
- Published
- 2009-12-10
- Issue
- Vol. 11 No. 4 (2009)
- Section
- Articles