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Applying scale-invariant dynamics to improve consensus achievement of agents in motion

Ilja Rausch (UGent) , Yara Khaluf (UGent) and Pieter Simoens (UGent)
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Abstract
In order to efficiently execute tasks, autonomous collective systems are required to rapidly reach accurate consensus, no matter how the group is distributed over the environment. Finding consensus in a group of agents that are in motion is a particularly great challenge, especially at larger scales and extensive environments. Nevertheless, numerous collective systems in nature reach consensus independently of scale, i.e. they are scale-free or scale-invariant. Inspired by these natural phenomena, the aim of our work is to improve consensus achievement in artificial systems by finding fundamental links between individual decision-making and scale-free collective behavior. For model validation we use physics-based simulations as well as a swarm robotic testbed.
Keywords
Consensus achievement, Scale invariance Swarm robotics

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Citation

Please use this url to cite or link to this publication:

MLA
Rausch, Ilja, et al. “Applying Scale-Invariant Dynamics to Improve Consensus Achievement of Agents in Motion.” DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, vol. 801, Springer, 2019, pp. 344–48.
APA
Rausch, I., Khaluf, Y., & Simoens, P. (2019). Applying scale-invariant dynamics to improve consensus achievement of agents in motion. In DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE (Vol. 801, pp. 344–348). Toledo, Spain: Springer.
Chicago author-date
Rausch, Ilja, Yara Khaluf, and Pieter Simoens. 2019. “Applying Scale-Invariant Dynamics to Improve Consensus Achievement of Agents in Motion.” In DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 801:344–48. Springer.
Chicago author-date (all authors)
Rausch, Ilja, Yara Khaluf, and Pieter Simoens. 2019. “Applying Scale-Invariant Dynamics to Improve Consensus Achievement of Agents in Motion.” In DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, 801:344–348. Springer.
Vancouver
1.
Rausch I, Khaluf Y, Simoens P. Applying scale-invariant dynamics to improve consensus achievement of agents in motion. In: DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE. Springer; 2019. p. 344–8.
IEEE
[1]
I. Rausch, Y. Khaluf, and P. Simoens, “Applying scale-invariant dynamics to improve consensus achievement of agents in motion,” in DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE, Toledo, Spain, 2019, vol. 801, pp. 344–348.
@inproceedings{8601107,
  abstract     = {In order to efficiently execute tasks, autonomous collective systems are required to rapidly reach accurate consensus, no matter how the group is distributed over the environment. Finding consensus in a group of agents that are in motion is a particularly great challenge, especially at larger scales and extensive environments. Nevertheless, numerous collective systems in nature reach consensus independently of scale, i.e. they are scale-free or scale-invariant. Inspired by these natural phenomena, the aim of our work is to improve consensus achievement in artificial systems by finding fundamental links between individual decision-making and scale-free collective behavior. For model validation we use physics-based simulations as well as a swarm robotic testbed.},
  author       = {Rausch, Ilja and Khaluf, Yara and Simoens, Pieter},
  booktitle    = {DISTRIBUTED COMPUTING AND ARTIFICIAL INTELLIGENCE},
  isbn         = {9783319996073},
  issn         = {2194-5357},
  keywords     = {Consensus achievement,Scale invariance Swarm robotics},
  language     = {eng},
  location     = {Toledo, Spain},
  pages        = {344--348},
  publisher    = {Springer},
  title        = {Applying scale-invariant dynamics to improve consensus achievement of agents in motion},
  url          = {http://dx.doi.org/10.1007/978-3-319-99608-0_42},
  volume       = {801},
  year         = {2019},
}

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