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• W2892613488 abstract "We examine whether the process of technological innovation is an evolutionary process, in the sense that information that determines entities in the past is transmitted to entities in the future. We compare citation and PageRank statistics applied to data from the US patent record with data produced by certain non-evolutionary processes, captured by three classes of models that are driven respectively by what we term random, preferential, and a priori attachment. We make qualitative and quantitative comparisons of the cumulative citation curves produced by the patents and the three models, and find that random, a priori, and preferential attachment processes fail to explain certain significant patterns observed in the patent record—a result that corroborates the hypothesis that technological innovation is an evolutionary process. Is technological innovation evolutionary? The advent of massive-scale systematic mining of aggregated social data, e.g., Michel et al. (2011), is transforming study of the evolution of science and technology. Earlier empirical study of the diffusion of innovations through social and economic markets (Rogers, 2003) can now be wedded with narrative theories the evolution of technology, e.g., Arthur (2009), and the analysis of innovation networks revealed in patent citation data (Jaffe and Trajtenberg, 2002). Interest in this topic rose sharply with the discovery that the growth and evolution of many kind of networks, including those consisting of citations among scientific papers (Redner, 1998; Barabasi and Albert, 1999; Lehmann et al., 2005) and patents (Valverde et al., 2007), exhibit power law behavior that can be modeled by various preferential attachment models. Here we take another look at this issue, and ask whether the characteristic dynamics of patent citations is well explained by three natural classes of models of the growth of patent citation networks. There are a variety of reasons why those in artificial life might be interested in the evolution of technology. The process is driven by innovation, and understanding the role of innovation is essential to understand evolution, both in artificial life and in biology. If the technosphere—the set of all technological artifacts—displays a nontrivial form of evolution, it might itself be considered a sort living system, or a form of living technology (Bedau et al., 2010b,a). The term “evolution” is usually used to describe the change of biological organisms over very long time periods, through a process that includes genetic variation of organisms from one generation to the next and natural selection based on survival of the fittest. This narrow biological view of evolution has been broadened to include long term changes in other non-biological systems; in recent literature one may find references to evolution of computer algorithms, evolutionary psychology, evolutionary history, cultural evolution, social evolution, sociocultural evolution, and technological evolution. But one may question the use of the term in all these contexts. A system may change over the long run, but when is that change properly termed evolution? Is there a well defined and empirically discernible difference between evolutionary change and non-evolutionary change? Our view is that there is indeed a difference between evolutionary change and non-evolutionary change. For a system to evolve, it must be comprised of a population of entities, with a process for continual creation of new entities (the entities are analogs of biological organisms). The entities must be determined, at least in part, by some set of information (analog of an organism’s genome). And finally, there must be some process of selection taking place so that different entities are present to greater or lesser degree. We hold that such a system undergoes evolutionary change if and only if some of the information used in determining past entities persists and affects the determination of present and future entities (a form of heritability). If the present state of the population is substantially causally disconnected from all the determining information of previous populations, we would say that change is non-evolutionary. Biological evolution meets our definition of evolutionary change because the genetic information specifying present entities is copied from the genetic information from previous entities, perhaps modified by certain kinds of random mutations. Note that evolutionary change in the sense defined here covers both random genetic drift and darwinian evolution by natural se-" @default.
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• W2892613488 date "2011-01-01" @default.
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• W2892613488 title "Evidence in the patent record for the evolution of technology using citation and PageRank statistics." @default.
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