Modeling and Control of Large-Scale Adversarial Swarm Engagements

Loading...
Thumbnail Image
Authors
Tsatsanifos, Theodoros
Clark, Abram H.
Walton, Claire
Kaminer, Isaac
Gong, Qi
Subjects
Advisors
Date of Issue
2021-08-04
Date
4 Aug 2021
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
We theoretically and numerically study the problem of optimal control of large-scale autonomous systems under explicitly adversarial conditions, including probabilistic destruction of agents during the simulation. Large-scale autonomous systems often include an adver sarial component, where different agents or groups of agents explicitly compete with one another. An important component of these systems that is not included in current theory or modeling frameworks is random destruction of agents in time. In this case, the modeling and optimal control framework should consider the attrition of agents as well as their position. We propose and test three numerical modeling schemes, where survival probabilities of all agents are smoothly and continuously decreased in time, based on the relative positions of all agents during the simulation. In particular, we apply these schemes to the case of agents defending a high-value unit from an attacking swarm. We show that these models can be successfully used to model this situation, provided that attrition and spatial dynamics are coupled. Our results have relevance to an entire class of adversarial autonomy situations, where the positions of agents and their survival probabilities are both important.
Type
Preprint
Description
Series/Report No
Department
Mechanical and Aerospace Engineering (MAE)
Physics
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
ONR SoA program
NPS CRUSER program
Funder
Format
7 p.
Citation
Tsatsanifos, Theodoros, et al. "Modeling and Control of Large-Scale Adversarial Swarm Engagements." arXiv preprint arXiv:2108.02311 (2021).
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
Collections