The multi-domain operations effect loop: From future concepts to research challenges

Tarek Abdelzaher, Adam Taliaferro, Paul Sullivan, Stephen Russell

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

Abstract

In a defense landscape driven by increasing automation, larger operation scale, higher opo, and tighter integrations across multiple domains, how do emerging advances in computing technology empower future defense concepts and operations? The paper overviews the notion of a multi-domain operations (MDO) effect loop as an organizing principle for military operations and information-driven decision processes. It then highlights recent advances in artificial intelligence, information theory, distributed sensing, and network optimization that significantly enhance the capabilities of different loop components, as illustrated by notional defense scenarios.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications II
EditorsTien Pham, Latasha Solomon, Katie Rainey
PublisherSPIE
ISBN (Electronic)9781510636033
DOIs
StatePublished - 2020
Externally publishedYes
EventArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications II 2020 - Virtual, Online, United States
Duration: Apr 27 2020May 8 2020

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume11413
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceArtificial Intelligence and Machine Learning for Multi-Domain Operations Applications II 2020
CountryUnited States
CityVirtual, Online
Period4/27/205/8/20

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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