Introduction to Recent Developments in Living Technology

McCaskill, John S.; Packard, Norman H.; Parke, Emily C.; Rasmussen, Steen

doi:10.1162/artl_e_00121

Cited by 17 publications

(19 citation statements)

References 17 publications

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“…Self-organization has been used directly in living technologies within a variety of domains (Bedau et al, 2013), from protocells (Rasmussen et al, 2008) to cities (Gershenson, 2013), and also several methodologies that use self-organization have been proposed in engineering (Frei and Di Marzo Serugendo, 2011). A major leap forward can be expected when principled design methodologies are laid down, and a better understanding of self-organization for ALife can be at the forefront of the development of such methods.…”

Section: Wet Alifementioning

confidence: 99%

Self-Organization and Artificial Life: A Review

Gershenson

Trianni

Werfel

et al. 2018

The 2018 Conference on Artificial Life

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Self-organization can be broadly defined as the ability of a system to display ordered spatio-temporal 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 to 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 life-like 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. Finally, we discuss the usefulness of selforganization within ALife studies, point to perspectives for future research, and list open questions.

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Section: Wet Alifementioning

confidence: 99%

Self-Organization and Artificial Life: A Review

Gershenson

Trianni

Werfel

et al. 2018

The 2018 Conference on Artificial Life

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“…There have been hundreds of papers published on applications of ALife (Kim and Cho, 2006). More recently, the term "living technology" has been used to describe technology that is based on the core features of living systems (Bedau et al, , 2013. Living technology is adaptive, robust, autonomous, and self-organizing.…”

Section: Living Technologymentioning

confidence: 99%

“…These and other questions have been asked within the ALife community. Bedau et al (2000) distilled a list of 14 open problems:…”

Section: The Futurementioning

confidence: 99%

The Past, Present, and Future of Artificial Life

et al. 2014

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For millennia people have wondered what makes the living different from the non-living. Beginning in the mid-1980s, artificial life has studied living systems using a synthetic approach: build life in order to understand it better, be it by means of software, hardware, or wetware. This review provides a summary of the advances that led to the development of artificial life, its current research topics, and open problems and opportunities. We classify artificial life research into 14 themes: origins of life, autonomy, self-organization, adaptation (including evolution, development, and learning), ecology, artificial societies, behavior, computational biology, artificial chemistries, information, living technology, art, and philosophy. Being interdisciplinary, artificial life seems to be losing its boundaries and merging with other fields.

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“…Nevertheless, the above studies all focus on simulating the behavior, habit, reproduction and growth of natural life individuals from the perspective of natural life individual. None of them explores the life behaviors and characteristics of artificial life population made up of multiple artificial life individuals [7]. Of course, some models have been developed to explore the life behaviors and characteristics of artificial life population, namely the "L System" of Linder Mayer [8], the "BOLD" of C. Reynolds [9], and the "Xiaoyuan's Fish" of Tu Xiaoyuan [10].…”

Section: Introductionmentioning

confidence: 99%

The evolution of artificial ecosystem based on the ecological chain algorithm

Feng¹,

Chen²

2017

AMA_B

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Aiming at expanding the research scope of artificial life, this paper studies the evolution of artificial ecosystem consisting of five simulated ecological layers, four influence programs and one evolution program. The concurrent execution of all influence and evolution programs is known as the ecological chain algorithm. The author carries out the artificial ecosystem evolution experiment using a set of simulated climate data. It is found that the law that the artificial ecosystem evolves with the simulated climate change is consistent with that of the natural ecosystem. Therefore, the study extends the research scope of artificial life, and provides an alternative to the evolution of natural ecosystem.

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Introduction to Recent Developments in Living Technology

Cited by 17 publications

References 17 publications

Self-Organization and Artificial Life: A Review

Self-Organization and Artificial Life: A Review

The Past, Present, and Future of Artificial Life

The evolution of artificial ecosystem based on the ecological chain algorithm

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