摘要
The bird-oid object (Boids) model proposes a control algorithm to make the positions between agents achieve cooperative stability. By changing the parameters of cohesion and repulsion in the algorithm, the agents in the swarm can be made to converge to different positions, causing expansion and contraction of the formation. But it is often more difficult to select the appropriate parameters to form the ideal formation. Therefore, this paper proposes a method to improve the cohesive and repulsive parameters in the Boids model based on Q-learning network to achieve a simulation scenario with continuous obstacle avoidance and maximum coverage of space.
源语言 | 英语 |
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主期刊名 | 2023 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023 |
出版商 | Institute of Electrical and Electronics Engineers Inc. |
页 | 62-67 |
页数 | 6 |
ISBN(电子版) | 9798350342239 |
DOI | |
出版状态 | 已出版 - 2023 |
活动 | 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023 - Nanjing, 中国 期限: 2 7月 2023 → 4 7月 2023 |
出版系列
姓名 | 2023 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023 |
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会议
会议 | 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023 |
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国家/地区 | 中国 |
市 | Nanjing |
时期 | 2/07/23 → 4/07/23 |
指纹
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Wu, Q., Liu, G., Liu, K., & Chen, L. (2023). Parameter Optimization via Reinforcement Learning for the Regulation of Swarms. 在 2023 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023 (页码 62-67). (2023 9th International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCSS58421.2023.10270800