Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming
In human-computer gaming scenarios, the autonomous decision-making problem of an unmanned combat air vehicle (UCAV) is a complex sequential decision-making problem involving multiple decision-makers. In this paper, an autonomous maneuver decision-making method for UCAV that considers the partially o...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-02-01
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| Series: | Drones |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2504-446X/7/3/157 |
| _version_ | 1797612322089336832 |
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| author | Shouyi Li Qingxian Wu Bin Du Yuhui Wang Mou Chen |
| author_facet | Shouyi Li Qingxian Wu Bin Du Yuhui Wang Mou Chen |
| author_sort | Shouyi Li |
| collection | DOAJ |
| description | In human-computer gaming scenarios, the autonomous decision-making problem of an unmanned combat air vehicle (UCAV) is a complex sequential decision-making problem involving multiple decision-makers. In this paper, an autonomous maneuver decision-making method for UCAV that considers the partially observable states of Human (the adversary) is proposed, building on a game-theoretic approach. The maneuver decision-making process within the current time horizon is modeled as a game of Human and UCAV, which significantly reduces the computational complexity of the entire decision-making process. In each established game decision-making model, an improved maneuver library that contains all possible maneuvers (called the continuous maneuver library) is designed, and each of these maneuvers corresponds to a mixed strategy of the established game. In addition, the unobservable states of Human are predicted via the Nash equilibrium strategy of the previous decision-making stage. Finally, the effectiveness of the proposed method is verified by some adversarial experiments. |
| first_indexed | 2024-03-11T06:39:39Z |
| format | Article |
| id | doaj.art-3078a125f1ac409c8b74c59fa4943d89 |
| institution | Directory Open Access Journal |
| issn | 2504-446X |
| language | English |
| last_indexed | 2024-03-11T06:39:39Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Drones |
| spelling | doaj.art-3078a125f1ac409c8b74c59fa4943d892023-11-17T10:39:15ZengMDPI AGDrones2504-446X2023-02-017315710.3390/drones7030157Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer GamingShouyi Li0Qingxian Wu1Bin Du2Yuhui Wang3Mou Chen4College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaCollege of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, ChinaIn human-computer gaming scenarios, the autonomous decision-making problem of an unmanned combat air vehicle (UCAV) is a complex sequential decision-making problem involving multiple decision-makers. In this paper, an autonomous maneuver decision-making method for UCAV that considers the partially observable states of Human (the adversary) is proposed, building on a game-theoretic approach. The maneuver decision-making process within the current time horizon is modeled as a game of Human and UCAV, which significantly reduces the computational complexity of the entire decision-making process. In each established game decision-making model, an improved maneuver library that contains all possible maneuvers (called the continuous maneuver library) is designed, and each of these maneuvers corresponds to a mixed strategy of the established game. In addition, the unobservable states of Human are predicted via the Nash equilibrium strategy of the previous decision-making stage. Finally, the effectiveness of the proposed method is verified by some adversarial experiments.https://www.mdpi.com/2504-446X/7/3/157human-computer gamingautonomous maneuver decision-makingincomplete informationcontinuous maneuver librarygame theory |
| spellingShingle | Shouyi Li Qingxian Wu Bin Du Yuhui Wang Mou Chen Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming Drones human-computer gaming autonomous maneuver decision-making incomplete information continuous maneuver library game theory |
| title | Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming |
| title_full | Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming |
| title_fullStr | Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming |
| title_full_unstemmed | Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming |
| title_short | Autonomous Maneuver Decision-Making of UCAV with Incomplete Information in Human-Computer Gaming |
| title_sort | autonomous maneuver decision making of ucav with incomplete information in human computer gaming |
| topic | human-computer gaming autonomous maneuver decision-making incomplete information continuous maneuver library game theory |
| url | https://www.mdpi.com/2504-446X/7/3/157 |
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