Cellular Automata with Memory

2012 ◽  
pp. 382-406 ◽  
Author(s):  
Ramón Alonso-Sanz
2014 ◽  
Vol 24 (09) ◽  
pp. 1450116 ◽  
Author(s):  
Shigeru Ninagawa ◽  
Andrew Adamatzky ◽  
Ramón Alonso-Sanz

We study elementary cellular automata with memory. The memory is a weighted function averaged over cell states in a time interval, with a varying factor which determines how strongly a cell's previous states contribute to the cell's present state. We classify selected cell-state transition functions based on Lempel–Ziv compressibility of space-time automaton configurations generated by these functions and the spectral analysis of their transitory behavior. We focus on rules 18, 22, and 54 because they exhibit the most intriguing behavior, including computational universality. We show that a complex behavior is observed near the nonmonotonous transition to null behavior (rules 18 and 54) or during the monotonic transition from chaotic to periodic behavior (rule 22).


Complexity ◽  
2014 ◽  
Vol 20 (1) ◽  
pp. 49-56 ◽  
Author(s):  
Ramón Alonso-Sanz

2013 ◽  
Vol 23 (10) ◽  
pp. 1330035 ◽  
Author(s):  
GENARO J. MARTÍNEZ ◽  
ANDREW ADAMATZKY ◽  
RAMON ALONSO-SANZ

Since their inception at Macy conferences in later 1940s, complex systems have remained the most controversial topic of interdisciplinary sciences. The term "complex system" is the most vague and liberally used scientific term. Using elementary cellular automata (ECA), and exploiting the CA classification, we demonstrate elusiveness of "complexity" by shifting space-time dynamics of the automata from simple to complex by enriching cells with memory. This way, we can transform any ECA class to another ECA class — without changing skeleton of cell-state transition function — and vice versa by just selecting a right kind of memory. A systematic analysis displays that memory helps "discover" hidden information and behavior on trivial — uniform, periodic, and nontrivial — chaotic, complex — dynamical systems.


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