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41677.pdf (5.26 MB)
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Abstract Header
Skirmish-Level Tactics via Game-Theoretic Analysis
Author Info
Von Moll, Alexander
ORCID® Identifier
http://orcid.org/0000-0002-7661-5752
Permalink:
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649761592413518
Abstract Details
Year and Degree
2022, PhD, University of Cincinnati, Engineering and Applied Science: Electrical Engineering.
Abstract
Supremacy in armed conflict comes not merely from superiority in capability or numbers but from how assets are used, down to the maneuvers of individual vehicles and munitions. This document outlines a research plan focused on skirmish-level tactics to militarily relevant scenarios. Skirmish-level refers to both the size of the adversarial engagement -- generally one vs. one, two vs. one, and/or one vs. two -- as well as the fact that the goal or objective of each team is well-established. The problem areas include pursuit-evasion and target guarding, either of which may be considered as sub-problems within military missions such as air-to-air combat, suppression/defense of ground-based assets, etc. In most cases, the tactics considered are comprised of the control policy of the agents (i.e., their spatial maneuvers), but may also include role assignment (e.g, whether to act as a decoy or striker) as well as discrete decisions (e.g., whether to engage or retreat). Skirmish-level tactics are important because they can provide insight into how to approach larger scale conflicts (many vs. many, many objectives, many decisions). Machine learning approaches such as reinforcement learning and neural networks have been demonstrated to be capable of developing controllers for large teams of agents. However, the performance of these controllers compared to the optimal (or equilibrium) policies is generally unknown. Differential Game Theory provides the means to obtain a rigorous solution to relevant scenarios in the form of saddle-point equilibrium control policies and the min/max (or max/min) cost / reward in the case of zero-sum games. When the equilibrium control policies can be obtained analytically, they are suitable for onboard / real-time implementation. Some challenges associated with the classical Differential Game Theory approach are explored herein. These challenges arise mainly due to the presence of singularities, which may appear in even the simplest differential games. The utility of skirmish-level solutions is demonstrated in (i) the multiple pursuer, single evader differential games, (ii) multi-agent turret defense scenarios, and (iii) engage or retreat scenarios. In its culmination, this work contributes differential game and optimal control solutions to novel scenarios, numerical techniques for computing singular surfaces, approximations for computationally-intensive solutions, and techniques for addressing scenarios with multiple stages or outcomes.
Committee
Zachariah Fuchs, Ph.D. (Committee Member)
David Casbeer, Ph.D. (Committee Member)
Dieter Vanderelst, Ph.D. (Committee Member)
Meir Pachter, Ph.D. (Committee Member)
John Gallagher, Ph.D. (Committee Member)
Pages
441 p.
Subject Headings
Electrical Engineering
Keywords
Differential games
;
Optimal control
;
Cooperative control
;
pursuit-evasion
;
turret defense
Recommended Citations
Refworks
EndNote
RIS
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Citations
Von Moll, A. (2022).
Skirmish-Level Tactics via Game-Theoretic Analysis
[Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649761592413518
APA Style (7th edition)
Von Moll, Alexander.
Skirmish-Level Tactics via Game-Theoretic Analysis.
2022. University of Cincinnati, Doctoral dissertation.
OhioLINK Electronic Theses and Dissertations Center
, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649761592413518.
MLA Style (8th edition)
Von Moll, Alexander. "Skirmish-Level Tactics via Game-Theoretic Analysis." Doctoral dissertation, University of Cincinnati, 2022. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1649761592413518
Chicago Manual of Style (17th edition)
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Document number:
ucin1649761592413518
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Copyright Info
© 2022, all rights reserved.
This open access ETD is published by University of Cincinnati and OhioLINK.