Emergent behavior in an adversarial synchronization and swarming model

McLennan-Smith, Timothy A.; Roberts, Dale; Sidhu, Harvinder

doi:10.1103/physreve.102.032607

Cited by 18 publications

(7 citation statements)

References 50 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…O'Keeffe et al introduced a model of 'swarmalators' [69] whose collective states have been realized in Nature and technology [21,25,26] and is being actively extended. The inclusion of noise [37], local coupling [38,39], periodic forcing [40], mixed sign interactions [41], and finite N effects [42] have been studied. The potential of swarmalators in bio-inspired computing has been explored [43], as has the well-posedness of N → ∞ solutions of the swarmalator model [44,45].…”

Section: Introductionmentioning

confidence: 99%

Collective behaviour of swarmalators on a 1D ring

O'Keeffe,

Ceron,

Petersen

2021

Preprint

View full text Add to dashboard Cite

We study the collective behavior of swarmalators, generalizations of phase oscillators that both sync and swarm, confined to move on a 1D ring. This simple model captures some of the essence of movement in 2D or 3D but has the benefit of being solvable: most of the collective states and their bifurcations can be specified exactly. The model also captures the behavior of real-world swarmalators which swarm in quasi-1D rings such as bordertaxic sperm and vinegar eels.

show abstract

Section: Introductionmentioning

confidence: 99%

Collective behaviour of swarmalators on a 1D ring

O'Keeffe,

Ceron,

Petersen

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…As shown in the summarizing lists in Supplementary Fig. 1 and Supplementary Table 1 , our model covers a wide variety of behaviors that qualitatively resemble many real-world collectives 5 , 10 – 12 , 31 , 40 , 47 , 49 – 58 and are only partially discovered in other active matter models 20 , 24 – 27 , 36 , 45 .…”

Section: Discussionmentioning

confidence: 92%

Diverse behaviors in non-uniform chiral and non-chiral swarmalators

2023

View full text Add to dashboard Cite

We study the emergent behaviors of a population of swarming coupled oscillators, dubbed swarmalators. Previous work considered the simplest, idealized case: identical swarmalators with global coupling. Here we expand this work by adding more realistic features: local coupling, non-identical natural frequencies, and chirality. This more realistic model generates a variety of new behaviors including lattices of vortices, beating clusters, and interacting phase waves. Similar behaviors are found across natural and artificial micro-scale collective systems, including social slime mold, spermatozoa vortex arrays, and Quincke rollers. Our results indicate a wide range of future use cases, both to aid characterization and understanding of natural swarms, and to design complex interactions in collective systems from soft and active matter to micro-robotics.

show abstract

“…The utility of surprising machines has historical roots: Gray Walter's physical machines (Walter, 1950) and Braitenberg's hypothetical machines were capable of startlingly complex behavior despite their extreme simplicity (Braitenberg, 1984). Today, robot swarms are often trained to exhibit useful "emergent behavior, " although the global behavior of the swarm may not be surprising, the irreducibility of swarm behavior to individual robot actions is a new concept to many roboticists (McLennan-Smith et al, 2020). Finally, the ubiquity of perverse instantiation -automatically trained or evolved robots often instantiate the requested, desired behavior in unexpected ways -in AI has been cited as a potentially useful way of designing machines (Lehman et al, 2020).…”

Section: Machines Are Predictable: Life Is Unpredictablementioning

confidence: 99%

Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior

Bongard

Levin

2021

Front. Ecol. Evol.

View full text Add to dashboard Cite

One of the most useful metaphors for driving scientific and engineering progress has been that of the “machine.” Much controversy exists about the applicability of this concept in the life sciences. Advances in molecular biology have revealed numerous design principles that can be harnessed to understand cells from an engineering perspective, and build novel devices to rationally exploit the laws of chemistry, physics, and computation. At the same time, organicists point to the many unique features of life, especially at larger scales of organization, which have resisted decomposition analysis and artificial implementation. Here, we argue that much of this debate has focused on inessential aspects of machines – classical properties which have been surpassed by advances in modern Machine Behavior and no longer apply. This emerging multidisciplinary field, at the interface of artificial life, machine learning, and synthetic bioengineering, is highlighting the inadequacy of existing definitions. Key terms such as machine, robot, program, software, evolved, designed, etc., need to be revised in light of technological and theoretical advances that have moved past the dated philosophical conceptions that have limited our understanding of both evolved and designed systems. Moving beyond contingent aspects of historical and current machines will enable conceptual tools that embrace inevitable advances in synthetic and hybrid bioengineering and computer science, toward a framework that identifies essential distinctions between fundamental concepts of devices and living agents. Progress in both theory and practical applications requires the establishment of a novel conception of “machines as they could be,” based on the profound lessons of biology at all scales. We sketch a perspective that acknowledges the remarkable, unique aspects of life to help re-define key terms, and identify deep, essential features of concepts for a future in which sharp boundaries between evolved and designed systems will not exist.

show abstract

Emergent behavior in an adversarial synchronization and swarming model

Cited by 18 publications

References 50 publications

Collective behaviour of swarmalators on a 1D ring

Collective behaviour of swarmalators on a 1D ring

Diverse behaviors in non-uniform chiral and non-chiral swarmalators

Living Things Are Not (20th Century) Machines: Updating Mechanism Metaphors in Light of the Modern Science of Machine Behavior

Contact Info

Product

Resources

About