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Modeling Large-Scale Adversarial Swarm Engagements using Optimal Control
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 adversarial component, where different...
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creator | Tsatsanifos, Theodoros Clark, Abram H. Walton, Claire Kaminer, Isaac Gong, Qi |
description | 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 adversarial 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. |
doi_str_mv | 10.1109/CDC45484.2021.9683410 |
format | conference_proceeding |
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Our results have relevance to an entire class of adversarial autonomy situations, where the positions of agents and their survival probabilities are both important.</description><subject>Autonomous systems</subject><subject>Numerical models</subject><subject>Optimal control</subject><subject>Probabilistic logic</subject><subject>Stochastic processes</subject><subject>Uncertain systems</subject><subject>Weapons</subject><issn>2576-2370</issn><isbn>9781665436595</isbn><isbn>166543659X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2021</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj8tKw0AYhUdBsNY-gQh5gcS5X5YlVitEuqiuy5_MPyGSS5mJim9vxa7O4nwcvkPIPaMFY9Q9lI-lVNLKglPOCqetkIxekJUzlmmtpNDKqUuy4MronAtDr8lNSh-UCuekWJDt6-Sx78Y2qyC2mO8b6DFb-y-MCWIHfbb_hjhkm7GFFgcc55R9pj9-d5y74dSX0zjHqb8lVwH6hKtzLsn70-at3ObV7vmlXFd5x6mYc69BQc0aE9CiwaCsZYJ57oUFLgNS71FYBIeGeXSKM-5r4MGrhgeotViSu__dDhEPx3hyiD-H83HxC6UJToM</recordid><startdate>20211214</startdate><enddate>20211214</enddate><creator>Tsatsanifos, Theodoros</creator><creator>Clark, Abram H.</creator><creator>Walton, Claire</creator><creator>Kaminer, Isaac</creator><creator>Gong, Qi</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>20211214</creationdate><title>Modeling Large-Scale Adversarial Swarm Engagements using Optimal Control</title><author>Tsatsanifos, Theodoros ; Clark, Abram H. ; Walton, Claire ; Kaminer, Isaac ; Gong, Qi</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i203t-d6a5ab1c7fe8e7ef588131d2d38a24fe0dde38ea9e71de95212dba2fd5c2fab63</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Autonomous systems</topic><topic>Numerical models</topic><topic>Optimal control</topic><topic>Probabilistic logic</topic><topic>Stochastic processes</topic><topic>Uncertain systems</topic><topic>Weapons</topic><toplevel>online_resources</toplevel><creatorcontrib>Tsatsanifos, Theodoros</creatorcontrib><creatorcontrib>Clark, Abram H.</creatorcontrib><creatorcontrib>Walton, Claire</creatorcontrib><creatorcontrib>Kaminer, Isaac</creatorcontrib><creatorcontrib>Gong, Qi</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Tsatsanifos, Theodoros</au><au>Clark, Abram H.</au><au>Walton, Claire</au><au>Kaminer, Isaac</au><au>Gong, Qi</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Modeling Large-Scale Adversarial Swarm Engagements using Optimal Control</atitle><btitle>2021 60th IEEE Conference on Decision and Control (CDC)</btitle><stitle>CDC</stitle><date>2021-12-14</date><risdate>2021</risdate><spage>1244</spage><epage>1249</epage><pages>1244-1249</pages><eissn>2576-2370</eissn><eisbn>9781665436595</eisbn><eisbn>166543659X</eisbn><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 adversarial 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. 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subjects | Autonomous systems Numerical models Optimal control Probabilistic logic Stochastic processes Uncertain systems Weapons |
title | Modeling Large-Scale Adversarial Swarm Engagements using Optimal Control |
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