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Simulation Results of a DQN Based AAV Testbed in Corner Environment: A Comparison Study for Normal DQN and TLS-DQN

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Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 279))

Abstract

The Deep Q-Network (DQN) is one of the deep reinforcement learning algorithms, which uses deep neural network structure to estimate the Q-value in Q-learning. In the previous work, we designed and implemented a DQN-based Autonomous Aerial Vehicle (AAV) testbed and proposed a Tabu List Strategy based DQN (TLS-DQN). In this paper, we consider corner environment as a new simulation scenario and carried out simulations for normal DQN and TLS-DQN for mobility control of AAV. Simulation results show that TLS-DQN performs better than normal DQN in the corner environment.

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Acknowledgements

This work was supported by JSPS KAKENHI Grant Number 20K19793.

Author information

Authors and Affiliations

  1. Graduate School of Engineering, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama, 700-0005, Japan

    Nobuki Saito & Aoto Hirata

  2. Department of Information and Computer Engineering, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama, 700-0005, Japan

    Tetsuya Oda & Kyohei Toyoshima

  3. Department of Information Science, Okayama University of Science (OUS), 1-1 Ridaicho, Kita-ku, Okayama, 700-0005, Japan

    Masaharu Hirota

  4. Department of Information and Communication Engineering, Fukuoka Institute of Technology, 3-30-1 Wajiro-higashi, Higashi-ku, Fukuoka, 811-0295, Japan

    Leonard Barolli

Authors
  1. Nobuki Saito
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  2. Tetsuya Oda
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  3. Aoto Hirata
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  4. Kyohei Toyoshima
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  5. Masaharu Hirota
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  6. Leonard Barolli
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Corresponding author

Correspondence to Tetsuya Oda .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Information Security Engineering, Soonchunhyang University, Asan, Korea (Republic of)

    Kangbin Yim

  3. Department of Computer Science and Information Engineering, Asia University, Taichung, Taiwan

    Hsing-Chung Chen

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Saito, N., Oda, T., Hirata, A., Toyoshima, K., Hirota, M., Barolli, L. (2022). Simulation Results of a DQN Based AAV Testbed in Corner Environment: A Comparison Study for Normal DQN and TLS-DQN. In: Barolli, L., Yim, K., Chen, HC. (eds) Innovative Mobile and Internet Services in Ubiquitous Computing. IMIS 2021. Lecture Notes in Networks and Systems, vol 279. Springer, Cham. https://doi.org/10.1007/978-3-030-79728-7_16

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