Self-organization and artificial life

Carlos Gershenson*, Vito Trianni, Justin Werfel, Hiroki Sayama

*この研究の対応する著者

研究成果: Article査読

23 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)391-408
ページ数18
ジャーナルArtificial Life
26
3
DOI
出版ステータスPublished - 2020

ASJC Scopus subject areas

  • コンピュータ サイエンス(その他)
  • 生態、進化、行動および分類学
  • 生化学、遺伝学、分子生物学(その他)
  • 農業および生物科学(その他)

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