Comparing the effects of mutualism and competition on industrial districts

Knight, Christopher J. K.; Penn, Alexandra S.; Hoyle, Rebecca B.

doi:10.1016/j.physa.2014.09.001

Cited by 3 publications

(2 citation statements)

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“…Independent of whether ALife is credited or not, the question is whether ALife research will be able to contribute to the solution of problems that otherwise would not be solvable. There are promising examples and successful case studies (e.g., [30,109]), but broader adoption and dissemination are required to make a difference.…”

Section: Open Questionsmentioning

confidence: 99%

Self-Organization and Artificial Life

et al. 2020

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Self-organization can be broadly defined as the ability of a system to display ordered spatiotemporal patterns solely as the result of the interactions among the system components. Processes of this kind characterize both living and artificial systems, making self-organization a concept that is at the basis of several disciplines, from physics to biology and engineering. Placed at the frontiers between disciplines, artificial life (ALife) has heavily borrowed concepts and tools from the study of self-organization, providing mechanistic interpretations of lifelike phenomena as well as useful constructivist approaches to artificial system design. Despite its broad usage within ALife, the concept of self-organization has been often excessively stretched or misinterpreted, calling for a clarification that could help with tracing the borders between what can and cannot be considered self-organization. In this review, we discuss the fundamental aspects of self-organization and list the main usages within three primary ALife domains, namely “soft” (mathematical/computational modeling), “hard” (physical robots), and “wet” (chemical/biological systems) ALife. We also provide a classification to locate this research. Finally, we discuss the usefulness of self-organization and related concepts within ALife studies, point to perspectives and challenges for future research, and list open questions. We hope that this work will motivate discussions related to self-organization in ALife and related fields.

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Section: Open Questionsmentioning

confidence: 99%

Self-Organization and Artificial Life

et al. 2020

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“…An agent based model proposed by Romero and Ruiz [196], based on a modelling framework previously developed in [197], evaluates potential cooperative relationships and incorporates game theory concepts. Repercussions of mutualism and competitive systems with respect to firm survival were investigated using ABM by Knight et al [198] on Marshallian and hub-and-spoke type districts. One of the few found developments with respect to the electrical grid in eco-industrial parks has been an application of ABM.…”

Section: Motivational Modelsmentioning

confidence: 99%