The evolution of technology within a simple computer model

Arthur, W. Brian; Polak, Wolfgang

doi:10.1002/cplx.20130

Cited by 102 publications

(87 citation statements)

References 7 publications

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“…On the other hand, combination of elements into subsystems is a powerful source of technological innovation. New building blocks replacing key components can trigger cascades of replacements [38] or 'gales of destruction' [30]. The rise and fall of relative component abundances in technical documents (figure 3) is consistent with emergence of innovations and the extinction of obsolete technologies, e.g.…”

Section: Transition From Hardware To Softwarementioning

confidence: 61%

Major transitions in information technology

Valverde

2016

Phil. Trans. R. Soc. B

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One contribution of 13 to a theme issue 'The major synthetic evolutionary transitions'. When looking at the history of technology, we can see that all inventions are not of equal importance. Only a few technologies have the potential to start a new branching series (specifically, by increasing diversity), have a lasting impact in human life and ultimately became turning points. Technological transitions correspond to times and places in the past when a large number of novel artefact forms or behaviours appeared together or in rapid succession. Why does that happen? Is technological change continuous and gradual or does it occur in sudden leaps and bounds? The evolution of information technology (IT) allows for a quantitative and theoretical approach to technological transitions. The value of information systems experiences sudden changes (i) when we learn how to use this technology, (ii) when we accumulate a large amount of information, and (iii) when communities of practice create and exchange free information. The coexistence between gradual improvements and discontinuous technological change is a consequence of the asymmetric relationship between complexity and hardware and software. Using a cultural evolution approach, we suggest that sudden changes in the organization of ITs depend on the high costs of maintaining and transmitting reliable information.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

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Section: Transition From Hardware To Softwarementioning

confidence: 61%

Major transitions in information technology

Valverde

2016

Phil. Trans. R. Soc. B

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“…In this view, complex behavior emerges as evolution creatively expands through a growing space of ecological niches (Kauffman, 2000;Schluter, 2000;Kelly, 2010), driven by opportunistic exaptation (Gould and Vrba, 1982) or ecological pressures toward diversity such as competitive exclusion (Hardin, 1960). Empirically, this understanding is supported by studies showing that complex functionalities fail to evolve without the scaffolding of functionally simpler niches (Lenski et al, 2003;Arthur and Polak, 2004), that bacteria colonies tend naturally to generate and maintain vast phenotypic diversity (Saint-Ruf et al, 2014), and that biodiversity begets further biodiversity (Jousset et al, 2016). Furthermore, viewing evolution as an open-ended creative process aligns with a similar understanding of cultural processes such as technological growth (Arthur, 2009;Kelly, 2010;Stanley and Lehman, 2015).…”

Section: Evolvability In Evolutionary Roboticsmentioning

confidence: 99%

On the Critical Role of Divergent Selection in Evolvability

2016

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An ambitious goal in evolutionary robotics (ER) is to evolve increasingly complex robotic behaviors with minimal human design effort. Reaching this goal requires evolutionary algorithms that can unlock from genetic encodings their latent potential for evolvability. One issue clouding this goal is conceptual confusion about evolvability that often obscures important or desirable aspects of evolvability. The danger from such confusion is that it may establish unrealistic goals for evolvability that prove unproductive in practice. An important issue separate from conceptual confusion is the common misalignment between selection and evolvability in ER. While more expressive encodings can represent higher-level adaptations (e.g. sexual reproduction or developmental systems) that increase long-term evolutionary potential (i.e. evolvability), realizing such potential requires gradients of fitness and evolvability to align. In other words, selection is often a critical factor limiting increasing evolvability. Thus, drawing from a series of recent papers, this article seeks to both (1) clarify and focus the ways in which the term evolvability is used within artificial evolution and (2) argue for the importance of one type of selection, i.e. divergent selection, for enabling evolvability. The main argument is that there is a fundamental connection between divergent selection and evolvability (on both the individual and population level) that does not hold for typical goal-oriented selection. The conclusion is that selection pressure plays a critical role in realizing the potential for evolvability and that divergent selection in particular provides a principled mechanism for encouraging evolvability in artificial evolution.

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“…At one end of the spectrum are those physicists who believe that the creation of a ''social physics'' is highly feasible [13][14][15], and at the other end are those who reject the idea of society obeying the laws of physics but maintain that adaptive agents can be substituted for particles within the basic supply-side physics model [16][17][18]. In between these extremes are those working on the ''evolution'' of technology, who still see some advantage in focusing on the supply-side interaction between units of technology in the absence of agents [19]. While it is not difficult to refute the idea of social physics [20], the work of the agent-based modelers (ABM) requires further discussion here.…”

Section: The Supply-side Physics Approachmentioning

confidence: 99%