A generalizable decentralised sequential assignment learning spiking neural network for a perimeter defense problem

In this paper, a generalizable Decentralized sequential multitask Assignment Learning Spiking neural network (DeALS) approach is presented for solving a Perimeter Defense Problem (PDP). In PDP, a team of defenders is considered to operate on the perimeter of the territory to be protected from incomi...

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Bibliographic Details
Main Authors: Mohammed Thousif, Shridhar Velhal, Suresh Sundaram, Shirin Dora, Narasimhan Sundararajan
Format: Default Article
Published: 2026
Subjects:
Engineering
Aerospace engineering
Communications engineering
Electronics, sensors and digital hardware
Geomatic engineering
Spiking neural networks
Shape
Spatiotemporal phenomena
Uncertainty
Robot kinematics
Protection
Training
Robot sensing systems
Observability
Multi-robot systems
Online Access:https://hdl.handle.net/2134/31389607.v1
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