Spiking Nonlinear Opinion Dynamics (S-NOD) for Agile Decision-Making

Adaptive systems; biologically-inspired methods; decision-making; excitable dynamics; robotics; Adaptive response; Agile decision makings; Biologically inspired methods; Decisions makings; Excitable dynamics; Fast response; In contexts; Opinion dynamics; Two-dimensional; Unpredictable changes; Control and Systems Engineering; Control and Optimization

Abstract :

[en] We present, analyze, and illustrate a first-of-its-kind model of two-dimensional excitable (spiking) dynamics for decision-making over two options. The model, Spiking Nonlinear Opinion Dynamics (S-NOD), provides superior agility, characterized by fast, flexible, and adaptive response to rapid and unpredictable changes in context, environment, or information received about available options. S-NOD derives through the introduction of a single extra term to the previously presented Nonlinear Opinion Dynamics (NOD) for fast and flexible multi-agent decision-making behavior. The extra term is inspired by the fast-positive, slow-negative mixed-feedback structure of excitable systems. The agile behaviors brought about by the new excitable nature of decision-making driven by S-NOD are analyzed in a general setting and illustrated in an application to multi-robot navigation around human movers.

Disciplines :

Engineering, computing & technology: Multidisciplinary, general & others

Author, co-author :

Cathcart, Charlotte ; Princeton University, Mechanical and Aerospace Engineering, Princeton, United States

Belaustegui, Ian Xul ; Princeton University, Mechanical and Aerospace Engineering, Princeton, United States

Franci, Alessio ; Université de Liège - ULiège > Département d'électricité, électronique et informatique (Institut Montefiore) > Brain-Inspired Computing ; WEL Research Institute, Wavre, Belgium

Leonard, Naomi Ehrich ; Princeton University, Mechanical and Aerospace Engineering, Princeton, United States

Language :

English

Title :

Spiking Nonlinear Opinion Dynamics (S-NOD) for Agile Decision-Making

Publication date :

2024

Journal title :

IEEE Control Systems Letters

eISSN :

2475-1456

Publisher :

Institute of Electrical and Electronics Engineers Inc.

Volume :

Pages :

3267 - 3272

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://xplorestaging.ieee.org/ielx8/7782633/10411713/10817538.pdf?arnumber=10817538

Funders :

ONR - Office of Naval Research

Funding text :

This work was supported by Office of Naval Research (ONR) under Grant N00014-19-1-2556.

Available on ORBi :

since 18 June 2025

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