Whether or not the field of artificial life has succeeded in doing what its name suggests, namely synthesizing life from non-living components, is a matter of contention. Clearly, this journal covers a broad range of topics related to the synthesis and simulation of living systems, but only a few articles go so far as to unabashedly study wholly artificial forms of life. The field of digital evolution is an exception: Artificial life forms, in the form of self-replicating computer code inhabiting specially prepared areas of a standard computer, have been used to learn about fundamental aspects of the evolutionary process since Tom Ray introduced us to them [23]. In this issue, we present experiments using digital organisms of the Avida variety (that is, implemented with the Avida software described in this issue [20]), but there are a number of other implementations of digital evolution that have been used for experimental evolution (see, e.g., [31, 32, 22, 5]). Whether or not these digitals are truly alive is ultimately of no concern to us as researchers: We use them because we are interested in complicated and vexing questions of evolutionary biology, and digitals offer us the possibility to attack them. Digital evolution is currently undergoing a boom phase, and public perception of this discipline is steadily increasing [21]. This boom can be traced back in part to a maturation of the Avida software used in the majority of digital evolution experiments, in part to a perceived need for rigor in evolution experiments [7], and in part to the adoption of digitals as experimental organisms alongside bacteria and viruses by a growing number of microbiologists (see, e.g., [16]). Although work in digital evolution of the past decade has been reviewed by us recently [29], the versatility of the Avida software to conduct evolution experiments has never been displayed in the manner we have the opportunity to do in this special issue. One of us (C.A.) has been teaching artificial life and evolution to advanced undergraduates and beginning graduate students at the California Institute of Technology since 1995 [1], and digital life has been a cornerstone of this class from the very beginning. The Avida software used in teaching this class, and developed expressly for research in evolutionary biology, was first written by C. Titus Brown and then by Charles Ofria in 1993 [19]. Since then, it has gone through many versions and revisions, with code contributions from a growing number of people, and a growing user base. But it is with the students taking CNS 175 (Artificial Life) and, since 2002, CNS 178 (Evolution and Biocomplexity) at Caltech that Avida has had its most lasting relationship. Each term, the students have to solve a number of problem sets, and at term’s end, instead of a final examination, the students are asked to turn in a final project that uses Avida to perform an experiment in evolution. But while for CNS 175 the students could choose one of three carefully selected projects, for CNS 178 we decided to take a different approach. We would not only let the students answer a question, we would let them pose it, too. So, when final project time approached, the students were asked via a
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