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A Defender-Aware Attacking Guidance Policy for the TAD Differential Game

English, Jacob T
http://rave.ohiolink.edu/etdc/view?acc_num=ohiou160579737158944

Abstract Details

2020, Master of Science (MS), Ohio University, Electrical Engineering & Computer Science (Engineering and Technology).
Deep reinforcement learning was used to train an agent within the framework of a Markov Decision Process (MDP) to pursue a target, while avoiding a defender, for the Target-Attacker-Defender (TAD) differential game of pursuit and evasion. The aim of this work was to explore the games where the previous attacking guidance methods found in literature failed to capture the Target. The reward function of the MDP presented by this work allowed for an attacking agent to learn a policy that expanded the number of cases where the target is captured beyond the former limit of success through the application of the Twin Delayed Deep Deterministic Policy Gradient algorithm (TD3). The strategy developed using artificial intelligence expands the target capture guidance approach to consider the long-term goal, rather than an instantaneous optimal heading. Initial Target positions within a limited set were considered with fixed values for agent velocities and Attacker and Defender initial positions to evaluate the Attacker’s learned behavior in comparison with the optimal point capture guidance laws for target capture in the TAD game.
Jay Wilhelm, PhD. (Advisor)
65 p.
Computer Science
reinforcement learning; guidance; differential games

Recommended Citations

Citations

  • English, J. T. (2020). A Defender-Aware Attacking Guidance Policy for the TAD Differential Game [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou160579737158944

    APA Style (7th edition)

  • English, Jacob. A Defender-Aware Attacking Guidance Policy for the TAD Differential Game. 2020. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou160579737158944.

    MLA Style (8th edition)

  • English, Jacob. "A Defender-Aware Attacking Guidance Policy for the TAD Differential Game." Master's thesis, Ohio University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou160579737158944

    Chicago Manual of Style (17th edition)

ohiou160579737158944
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