Emergence of self-replicating structures in a cellular automata space

Past cellular automata models of self-replication have always been initialized with an original copy of the structure that will replicate, and have been based on a transition function that only works for a single, specific structure. This article demonstrates for the first time that it is possible to create cellular automata models in which a self-replicating structure emerges from an initial state having a random density and distribution of individual components. These emergent self-replicating structures employ a fairly general rule set that can support the replication of structures of different sizes and their growth from smaller to larger ones. This rule set also allows “random” interactions of self-replicating structures with each other and with other structures within the cellular automata space. Systematic simulations show that emergence and growth of replicants occurs often and is essentially independent of the cellular space size, initial random pattern of components, and initial density of components, over a broad range of these parameters. The number of replicants and the total number of components they incorporate generally approach quasi-stable values with time.     

A graph theory approach to subcontracting, machine duplication and intercell moves in cellular manufacturing

We address in this paper the problem of finding an optimal strategy for dealing with bottleneck machines and bottleneck parts in the cell formation process in group technology. Three types of economic decisions are considered: subcontracting, machine duplication and intercell moves. The problem is formulated as a minimum weighted node covering problem in a hypergraph, and we show that it can be solved in polynomial time by finding a maximum weighted stable set in a bipartite graph. We extend this result to cellular manufacturing systems in which the sequence of operations of each part is known in advance.     

Manufacturing cell formation using similarity coefficients and a parallel genetic TSP algorithm: Formulation and comparison

Many algorithms have been proposed to form manufacturing cells from component routings. However, many of these do not have the capability of solving large problems. We propose a procedure using similarity coefficients and a parallel genetic implementation of a TSP algorithm that is capable of solving large problems of up to 1000 parts and 1000 machines. In addition, we also compare our procedure with many existing procedures using nine well-known problems from the literature.

The results show that the proposed procedure compares well with the existing procedures and should be useful to practitioners and researchers.     

Xor on one‐defect systems

We present a network experiment that investigates the computational power of cellular automata on the simplest irregular lattice. One cellular automaton whose apparent complexity increased is Rule 60, the left neighbor Xor operator. It went from being nested to complex. That makes Xor a candidate for universal computational power. We present the evidence in terms of the size of cycle lengths, transients, and size of boolean expressions. © 2006 Wiley Periodicals, Inc. Complexity 12: 13–29, 2006     

Two-spin-majority cellular automaton as a model of 2D cluster and interface growth

A new probabilistic cellular automaton model is introduced to simulate cluster and interface growth in two dimensions. The dynamics of this model is an extension to higher dimensions of the compact directed percolation studied by Essam. Numerical results indicate that the two-dimensional cluster coarsening and growth can be described only approximately by the conventional cluster size scaling due to a crossover in the growth mode. The spreading of the initially flat interface follows a purely diffusional,t ^1/2, law.     

Cluster growth in particle-conserving cellular automata

A class of simple two-dimensional cellular automata with particle conservation is proposed for easy simulations of interacting particle systems. The automata are defined by the exchange of states of neighboring cells, depending on the configurations around the cells. By attributing an energy to a configuration of cells, we can select significant rules from the huge number of possible rules and classify them into several groups, based on the analogy with a binary alloy. By numerical calculations, cluster growth is found in two kinds of phases which reveal gas-solid coexistence and liquid droplets. Normalized scaling functions are obtained, and dynamical scaling is examined.     

On irreversibility of von Neumann additive cellular automata on grids

The von Neumann cellular automaton appears in many different settings in Operations Research varying from applications in Formal Languages to Biology. One of the major questions related to it is to find a general condition for irreversibility of a class of two-dimensional cellular automata on square grids (σ⁺-automata). This question is partially answered here with the proposal of a sufficient condition for the irreversibility of σ⁺-automata.     

Rigidity of Branch Groups Acting on Rooted Trees

Automorphisms of groups acting faithfully on rooted trees are studied. We find conditions under which every automorphism of such a group is induced by a conjugation from the full automorphism group of the rooted tree. These results are applied to known examples such as Grigorchuk groups, Gupta–Sidki group, etc.     

An efficient hydrodynamic cellular automata for simulating fluids with large viscosities

A hydrodynamic cellular automata (HDCA) for simulating two-dimensional fluids with large viscosities is proposed. The model is characterized by a mean free path which is of the same size as in the FHP-II model, but with a viscosity more than 10 times larger. This new model should make simulations of flows at low Reynolds number more efficient.     

Complex genetic evolution of artificial self‐replicators in cellular automata

It is widely believed that evolutionary dynamics of artificial self‐replicators realized in cellular automata (CA) are limited in diversity and adaptation. Contrary to this view, we show that complex genetic evolution may occur within simple CA. The evolving self‐replicating loops (“evoloops”) we investigate exhibit significant diversity in macro‐scale morphologies and mutational biases, undergoing nontrivial genetic adaptation by maximizing colony density and enhancing sustainability against other species. Nonmutable subsequences enable genetic operations that alter fitness differentials and promote long‐term evolutionary exploration. These results demonstrate a unique example of genetic evolution hierarchically emerging from local interactions between elements much smaller than individual replicators. © 2004 Wiley Periodicals, Inc. Complexity 10: 33–39, 2004