Complex Dynamics Emerging in Rule 30 with Majority Memory

In cellular automata with memory, the unchanged maps of the conventional cellular automata are applied to cells endowed with memory of their past states in some specified interval. We implement Rule 30 automata with a majority memory and show that using the memory function we can transform quasi-chaotic dynamics of classical Rule 30 into domains of travelling structures with predictable behaviour. We analyse morphological complexity of the automata and classify dynamics of gliders (particles, self-localizations) in memory-enriched Rule 30. We provide formal ways of encoding and classifying glider dynamics using de Bruijn diagrams, soliton reactions and quasi-chemical representations.

[1]  S. Amoroso,et al.  The Garden-of-Eden theorem for finite configurations , 1970 .

[2]  Juan Carlos Seck Tuoh Mora,et al.  Gliders in Rule 110 , 2006, Int. J. Unconv. Comput..

[3]  Ramón Alonso-Sanz,et al.  Cellular Automata with Memory , 2009, Encyclopedia of Complexity and Systems Science.

[4]  B. Voorhees Computational Analysis of One-Dimensional Cellular Automata , 1995 .

[5]  K. Steiglitz,et al.  Soliton-like behavior in automata , 1986 .

[6]  Stephen Wolfram,et al.  Cellular Automata And Complexity , 1994 .

[7]  Juan Carlos Seck Tuoh Mora,et al.  Calculating Ancestors In One-Dimensional Cellular Automata , 2004 .

[8]  N. Boccara,et al.  Particlelike structures and their interactions in spatiotemporal patterns generated by one-dimensional deterministic cellular-automaton rules. , 1991, Physical review. A, Atomic, molecular, and optical physics.

[9]  James P. Crutchfield,et al.  A Genetic Algorithm Discovers Particle-Based Computation in Cellular Automata , 1994, PPSN.

[10]  A. Wuensche Classifying Cellular Automata Automatically , 1998 .

[11]  Andrew Adamatzky Collision-Based Computing , 2002, Springer London.

[12]  Kenneth Steiglitz,et al.  Computing with Solitons: A Review and Prospectus , 2002, Collision-Based Computing.

[13]  Andrew Wuensche,et al.  Complexity in One-D Cellular Automata: Gliders, Basins of Attraction and the Z Parameter , 1994 .

[14]  Yaneer Bar-Yam,et al.  Dynamics Of Complex Systems , 2019 .

[15]  Genaro Juárez Martínez,et al.  On the Representation of Gliders in Rule 54 by De Bruijn and Cycle Diagrams , 2008, ACRI.

[16]  C. Robinson Dynamical Systems: Stability, Symbolic Dynamics, and Chaos , 1994 .

[17]  Andrew Adamatzky,et al.  Phenomenology of excitation in 2-D cellular automata and swarm systems , 1998 .

[18]  Stephen A. Billings,et al.  The Identification of Cellular Automata , 2006, J. Cell. Autom..

[19]  Seck Tuoh Mora,et al.  A note about the regular languaje of Rule 110 and its general machine: the scalar subset diagram. , 2007 .

[20]  Stephen Wolfram One-dimensional Cellular Automata , .

[21]  Juan Carlos Seck Tuoh Mora,et al.  Procedures for calculating reversible one-dimensional cellular automata , 2005 .

[22]  Moshe Sipper,et al.  Evolution of Parallel Cellular Machines: The Cellular Programming Approach , 1997 .

[23]  Maurice Margenstern Cellular Automata in Hyperbolic Spaces , 2009, Encyclopedia of Complexity and Systems Science.

[24]  Ramón Alonso-Sanz,et al.  Elementary Cellular Automata with Memory , 2003, Complex Syst..

[25]  Matthew Cook,et al.  Universality in Elementary Cellular Automata , 2004, Complex Syst..

[26]  Kenneth Steiglitz,et al.  Embedding Computation in One-Dimensional Automata by Phase Coding Solitons , 1988, IEEE Trans. Computers.

[27]  Mike Mannion,et al.  Complex systems , 1997, Proceedings International Conference and Workshop on Engineering of Computer-Based Systems.

[28]  John von Neumann,et al.  Theory Of Self Reproducing Automata , 1967 .

[29]  Eric S. Rowland Local Nested Structure in Rule 30 , 2006, Complex Syst..

[30]  Karel Culik,et al.  Undecidability of CA Classification Schemes , 1988, Complex Syst..

[31]  Nino Boccara,et al.  Number-conserving cellular automaton rules , 1999, Fundam. Informaticae.

[32]  Stephen Wolfram,et al.  A New Kind of Science , 2003, Artificial Life.

[33]  Stuart A. Kauffman,et al.  The origins of order , 1993 .

[34]  Andrew Adamatzky,et al.  Phenomenology of glider collisions in cellular automaton Rule 54 and associated logical gates , 2006 .

[35]  Mark Newman,et al.  Complex Systems Theory and Evolution , 2002 .

[36]  Andrew Wuensche,et al.  The global dynamics of cellular automata : an atlas of basin of attraction fields of one-dimensional cellular automata , 1992 .

[37]  David Eppstein,et al.  Searching for Spaceships , 2000, ArXiv.

[38]  Juan Carlos Seck Tuoh Mora,et al.  Determining a regular language by glider-based structures called phases fi_1 in Rule 110 , 2007, 0706.3348.

[39]  Andrew Wuensche,et al.  Classifying cellular automata automatically: Finding gliders, filtering, and relating space-time patterns, attractor basins, and the Z parameter , 1998, Complex..

[40]  Katsunobu Imai,et al.  A Logically Universal Number-Conserving Cellular Automaton with a Unary Table-Lookup Function , 2004, IEICE Trans. Inf. Syst..