Abstract

Open-ended evolutionary systems offer us the tantalising prospect of creating artificial life from simple precursors. One of the issues in designing open ended systems is that there exist few metrics for measuring their evolutionary activity. Current measures of evolutionary activity are only applicable to systems in which the fitness of a single component is defined by an explicit fitness function. However, this is not guaranteed in systems where a significant part of the fitness is intrinsic (for example caused by interactions between components). In this paper, we evaluate a new approach to the problem of measuring evolutionary activity that is applicable to systems exhibiting both explicit and intrinsic fitness pressures. To evaluate this measure, we ran 22,000 grid-based simulations of two automata chemistries, Tierra and Stringmol. Both of these systems have strong intrinsic fitness pressures. We examine the effect of varying the mutation rate in both systems, and demonstrate that the new measure identifies an optimal mutation rate.

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