Abstract
Population dynamics in the evolution, extinction, and re-evolution of various logic-function performing organisms is studied in the artificial life system, Avida. Following the work of Yedid (2009), we design an experiment involving two extinction regimes, pulse-extinction (corresponding to a random-kill event) and press-extinction (corresponding to a prolonged episode of rare resources). In addition, we study the effect of environmental topology (toroidal grid and clique graph). In the study of population dynamics, logarithmic returns are generally applied. The resulting distributions display a fat tail form of the power law: the more complex the logic function (in terms of NAND components), the broader the full width at half a maximum of the histogram. The power law exponents were in sound agreement with those of “real-life” populations and distributions. The distributions of evolutionary times, as well as post-extinction recovery periods, were very broad, and presumably had no standard deviations. Using 100 runs of 200,000 updates for each of the four cases (about 1 month of central processing unit time), we established the dynamics of the average population, with the effect of world topology.
Highlights
The artificial life system, Avida (Lenski, Ofria, Pennock, & Adami, 2003), is a software platform in which digital organisms, namely computer programs from elements of a limited instruction set, selfreplicate, evolve, and compete for computational time on a model hardware
The following is a summary of the simulation results for the press extinction regime
The results varied widely, with standard deviation estimates exceeding the mean recovery times for each of the nine logic functions computed by the digital organisms
Summary
The artificial life system, Avida (Lenski, Ofria, Pennock, & Adami, 2003), is a software platform in which digital organisms, namely computer programs from elements of a limited instruction set, selfreplicate, evolve, and compete for computational time on a model hardware. The digital organisms are capable of performing various logic functions, such as NOT, NAND, AND, OR_N, OR, AND_N, NOR, XOR, and EQU (Adami, Ofria, & Collier, 2000). As the complexity of the logic function increases, organisms are rewarded with extra computational time, which allows them to make more offspring copies, and effectively reproduce. The reproduction phase includes a genetic operator of mutation, by which the particular program instruction may be changed randomly with a small probability, driving evolution within the system. Sexual reproduction has been introduced into Avida as an option (Covert III, Carlson-Stevermer, Derrberry, & Wilke, 2012), the default version used in this work did not include parental mating, and the cross-over operator was excluded in this study
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