We present a new self-reproducing cellular automaton capable of construction and computation beyond self-reproduction. Our automaton makes use of some of the concepts developed by Langton for his self-reproducing automaton, but provides the added advantage of being able to perform independent constructional and computational tasks alongside self-reproduction. Our automaton is capable, like Langton's automaton and with comparable complexity, of simple self-replication, but it also provides (at the cost, naturally, of increased complexity) the option of attaching to the automaton an executable program which will be duplicated and executed in each of the copies of the automaton. After describing in some detail the self-reproduction mechanism of our automaton, we provide a non-trivial example of its constructional capabilities. 1 Introduction The history of self-reproducing cellular automata basically begins with John von Neumann's research in the field of complex self-reproducing machi...

Self-reproducing, cellular automata-based systems developed to date broadly fall under two categories; the first consists of machines which are capable of performing elaborate tasks, yet are too complex to simulate, while the second consists of extremely simple machines which can be entirely implemented, yet lack any additional functionality aside from self-reproduction. In this paper we present a self-reproducing system which is completely realizable, while capable of executing any desired program, thereby exhibiting universal computation. Our starting point is a simple self-reproducing loop structure onto which we "attach" an executable program (Turing machine) along with its data. The three parts of our system (loop, program, data) are all reproduced, after which the program is run on the given data. The system reported in this paper has been simulated in its entirety; thus, we attain a viable, self-reproducing machine with programmable capabilities. 1 Introduction The study of art...

Some of the major outstanding problems in biology are related to issues of emergence and evolution. These include: (1) how do populations of organisms traverse their adaptive landscapes? (2) what is the relation between adaptedness and fitness? (3) the formation of multi-cellular organisms from basic units or cells. In this paper we study these issues using a model which is both general and simple. The system, derived from the CA (cellular automata) model, consists of a two-dimensional grid of interacting organisms which may evolve over time. We first present designed multi-cellular organisms which display several interesting behaviors including: reproduction, growth, mobility. We then turn our attention to evolution in various environments, including: an environment in which competition for space occurs, an IPD (Iterated Prisoner's Dilemma) environment, an environment of spatial niches, and an environment of temporal niches. One of the advantages of AL models is the opportunities they...

We discuss the cellular automata approach and its extensions, the lattice Boltzmann and multiparticle methods. The potential of these techniques is demonstrated in the case of modeling complex systems. In particular, we consider applications taken from various fields of physics, such as reaction-diffusion systems, pattern formation phenomena, fluid flows, fracture processes and road traffic models.

Introduction Spatial heterogeneity in abiotic factors and biotic processes often generates patterns in population dynamics and the resulting attributes of ecological communities. Despite a long-standing recognition of the significance of spatial variation, analytical and computational models of spatially explicit, multispecies interactions have only recently influenced community theory (e.g. Hastings, 1990; Kareiva, 1990). We develop a spatially explicit model for the epidemiological landscape of a vector-borne disease. We focus on the "ecological stencil", the local area where ecological interactions govern the species composition at any specific location. Simulation of the local transition probabilities defining the stencil will predict large-scale spatio-temporal patterns of the model community. We first mention a few examples of vector-borne disease. Then we present a model for the dispersal-mortality dynamics of two competing host species, a pathogen that infects the hosts, and

I came to Caltech a scatterbrained but enthusiastic young scientist. Without the constant nurturing and tutelage of my PhD advisor, Erik Winfree, I can’t imagine what would have happened. Erik’s gifts are many – a generous spirit, stratospheric intellectual standards, a razor-sharp intuition for the truth, and a boundless imagination. It has been a pleasure and a privilege to work with him, to hear his constant feedback on my own imperfect thoughts. I hope in the future I can honor a tiny portion of his gifts to me by teaching others. As a PhD student I have been privileged to stand on the shoulders of other both brilliant and kind intellectual giants, without whom this work would never have been. First and foremost, my thesis work owes an unpayable intellectual debt to the work of Graham Cairns-Smith. His unconventional thoughts about the first life on earth were the catalyst for this work on self-replication. I am flattered and grateful for his continued support in the form of visits, talks, and letters during his retirement. No one was more honest about the rigors of the PhD process and a life in science than Paul Rothemund. As human and as good a friend as Paul has been, he also been someone to aspire to be like. Simply, Paul is a whiz, and a big friendly intellectual giant. I am excited about everything

Building on the work of Von Neumann, Langton, and Sayama among others, we introduce the rst examples of evolution in populations of self-reproducing con gurations in asynchronous cellular automata. Reliance on a global synchronous update signal has been a limitation of all solutions since the problem of achieving self-production in cellular automata was rst attacked by Von Neumann half a century ago. Results of the author obviate the need for this restriction.

We succeeded for the first time in constructing evolutionary systems on a simple 9-state 5-neighbor cellular automata (CA) space by utilizing Langton's self-reproducing loop. CA are deterministic dynamical systems capable of representing extremely complex nonlinear phenomena, where time, space and states of sites are all discrete. Many CA models of self-reproductive behavior of theoretical organisms have so far been energetically studied, but the evolutionary process of organisms driven by variation and natural selection has never been realized on CA space yet. In this dissertation, we added three improvements into Langton's loop, i.e., to realize a kind of death by introducing a new dissolving state `8' into the set of states of the CA, to enhance the adaptability (a degree of the variety of situations in which the structures in the CA space can operate regularly) of the selfreproductive mechanism described by the state-transition rules of the CA, and to modify the initial structure o...

A new self-replicating cellular automata (CA) model is proposed as a latest effort toward the realization of an artificial evolutionary system on CA where structural complexity of self-replicators can increase in some cases. I utilize the idea of `shape encoding' proposed by Morita and Imai (Morita & Imai 1996b) and make the state-transition rules of the model allow organisms to transmit genetic information to others when colliding against each other. Simulations with random initial configuration demonstrate that it is possible that the average length of organisms and the average frequency of brancing per organism both increase, with decreasing self-replication fidelity, and saturate at some constant level. The saturation is caused in part by the fixation of place and shape of organisms onto particular sites. This implies the necessity of introducing some fluidity of site arrangements into the model for further development of evolutionary models using CA-like artificial medi...

In this article, we present the BioWall, a giant reconfigurable computing tissue developed to implement machines according to the principles of our Embryonics (embryonic electronics) project. The BioWall’s size and features are designed for public exhibition, but at the same time it represents an invaluable research tool, particularly since its complete programmability and cellular structure are extremely well adapted to the implementation of many different kinds of bio-inspired systems. To illustrate these capabilities, we present a set of applications that range over many diverse sources of biological inspiration, from the ontogenetic systems, through epigenetic artificial neural networks, to phylogenetic evolving hardware. All these applications have been fully implemented and tested in hardware on the BioWall. 1