Bio-inspired decision-making and control: From honeybees and neurons to network design

Vaibhav Srivastava, Naomi Ehrich Leonard

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

We present nonlinear deterministic models and linear stochastic models of decision-making between alternatives that connect biological groups as diverse as honeybees and neurons. Using these models we explain how biological groups, with decentralized control and limited sensing and communication, select the highest quality alternative, flip a coin for nearly equal alternatives, optimally balance speed and accuracy, maintain robustness in the face of uncertainty, and leverage heterogeneity. Motivated by these remarkable behaviors, we present a generalizable agent-based model for the design and control of network dynamics with the advantageous features observed in the biological groups.

Original languageEnglish (US)
Title of host publication2017 American Control Conference, ACC 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2026-2039
Number of pages14
ISBN (Electronic)9781509059928
DOIs
StatePublished - Jun 29 2017
Event2017 American Control Conference, ACC 2017 - Seattle, United States
Duration: May 24 2017May 26 2017

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Other

Other2017 American Control Conference, ACC 2017
CountryUnited States
CitySeattle
Period5/24/175/26/17

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

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    Srivastava, V., & Leonard, N. E. (2017). Bio-inspired decision-making and control: From honeybees and neurons to network design. In 2017 American Control Conference, ACC 2017 (pp. 2026-2039). [7963250] (Proceedings of the American Control Conference). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.23919/ACC.2017.7963250