International Journal of Crowd Science 2023, 7(4): 158-167 https://doi.org/10.26599/IJCS.2023.9100023

Open Access | Issue | Published: 22 December 2023

Computational Experiments: Virtual Production and Governance Tool for Metaverse

Show Author's Information Hide Author's Information Chao Peng^¹, Xiangning Yu^¹, Wanpeng Ma^², Hayata Kaneko^³, Lin Meng^³, Yingyue Zhao^⁴, Xiao Xue^¹(

)

1College of Intelligence and Computing, Tianjin University, Tianjin 300072, China

2Army Aviation Research Institute, Beijing 101121, China

3College of Science and Engineering, Ritsumeikan University, Kusatsu 525-0058, Japan

4School of Civil Engineering, Central South University, Changsha 410083, China

Keywords:

metaverse, computational experiments, virtual production and governance

Cite this article:

Peng C, Yu X, Ma W, et al. Computational Experiments: Virtual Production and Governance Tool for Metaverse. International Journal of Crowd Science, 2023, 7(4): 158-167. https://doi.org/10.26599/IJCS.2023.9100023

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Abstract

The metaverse, as an extension of the physical world, can be described as a highly immersive digital realm constructed with technologies such as mixed reality and digital modeling. It is rooted in decentralized principles and features novel economic forms, individual identities, and institutional systems. In this architecture, the entire social landscape is redefined under the logic of service, gradually becoming a service ecosystem operated and cooperated by numerous intelligent entities. To achieve sustainable and healthy development of the metaverse ecology, this paper first analyzes the operating logic of the metaverse from the perspective of the fusion of the cyber-physical-social tripartite world and the three typical complexity characteristics faced by it: evolutionary complexity, cognitive complexity, and regulatory complexity. Next, the paper focuses on introducing the idea and technical system of computational experiments as an analysis and governance tool for the metaverse service ecosystem. Then, it explores the integration of computational experiments and metaverse technology, including how computational experiments can be applied to the metaverse and how the metaverse can support computational experiments. Finally, the paper introduces the metaverse applications of computational experiments, covering fields such as industrial design, health care, social governance, and military reform.

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Computational Experiments: Virtual Production and Governance Tool for Metaverse

Show Author's information Hide Author's Information Chao Peng^¹, Xiangning Yu^¹, Wanpeng Ma^², Hayata Kaneko^³, Lin Meng^³, Yingyue Zhao^⁴, Xiao Xue^¹(

)

1College of Intelligence and Computing, Tianjin University, Tianjin 300072, China

2Army Aviation Research Institute, Beijing 101121, China

3College of Science and Engineering, Ritsumeikan University, Kusatsu 525-0058, Japan

4School of Civil Engineering, Central South University, Changsha 410083, China

Abstract

Keywords: metaverse, computational experiments, virtual production and governance

References(37)

[1]

Y. Duan, G. Fu, N. Zhou, X. Sun, N. C. Narendra, and B. Hu, Everything as a service (XaaS) on the cloud: Origins, current and future trends, in Proc. 2015 IEEE 8^th Int. Conf. Cloud Computing, New York, NY, USA, 2015, pp. 621–628.

DOI

[2]

H. Wang, H. Ning, Y. Lin, W. Wang, S. Dhelim, F. Farha, J. Ding, and M. Daneshmand, A survey on the metaverse: The state-of-the-art, technologies, applications, and challenges, IEEE Internet Things J., vol. 10, no. 16, pp. 14671–14688, 2023.

DOI Google Scholar

[3]

H. Huang, Q. Zhang, T. Li, Q. Yang, Z. Yin, J. Wu, Z. Xiong, J. Zhu, J. Wu, and Z. Zheng, Economic systems in metaverse: Basics, state of the art, and challenges, arXiv preprint arXiv: 2212.05803, 2022.

[4]

L. Ante, C. Fischer, and E. Strehle, A bibliometric review of research on digital identity: Research streams, influential works and future research paths, J. Manuf. Syst., vol. 62, pp. 523–538, 2022.

DOI Google Scholar

[5]

S. Ghirmai, D. Mebrahtom, M. Aloqaily, M. Guizani, and M. Debbah, Self-sovereign identity for trust and interoperability in the metaverse, arXiv preprint arXiv: 2303.00422, 2023.

DOI

[6]

N. Schneider, P. D. Filippi, S. Frey, J. Z. Tan, and A. X. Zhang, Modular politics: Toward a governance layer for online communities, Proc. ACM Hum. Comput. Interact., vol. 5, no. CSCW1, p. 16, 2021.

DOI Google Scholar

[7]

C. B. Fernandez and P. Hui, Life, the metaverse and everything: An overview of privacy, ethics, and governance in metaverse, in Proc. 2022 IEEE 42^nd Int. Conf. Distributed Computing Systems Workshops (ICDCSW), Bologna, Italy, 2022, pp. 272–277.

DOI

[8]

X. Xue, X. N. Yu, D. Y. Zhou, C. Peng, X. Wang, Z. B. Zhou, and F. Y. Wang, Computational experiments: Past, present and perspective, Acta Automatica Sinica, vol. 49, no. 2, pp. 246–271, 2023.

Google Scholar

[9]

F. Y. Wang, Computational experiments for behavior analysis and decision evaluation of complex systems, J. System Simulation, vol. 16, no. 5, pp. 893–897, 2004.

Google Scholar

[10]

X. Xue, S. Wang, L. Zhang, Z. Feng, and Y. Guo, Social learning evolution (SLE): Computational experiment-based modeling framework of social manufacturing, IEEE Trans. Ind. Inform., vol. 15, no. 6, pp. 3343–3355, 2019.

DOI Google Scholar

[11]

L. Li, X. Wang, K. Wang, Y. Lin, J. Xin, L. Chen, L. Xu, B. Tian, Y. Ai, J. Wang, et al., Parallel testing of vehicle intelligence via virtual-real interaction, Sci. Robot., vol. 4, no. 28, p. eaaw4106, 2019.

DOI Google Scholar

[12]

X. F. Hu, Z. Q. Li, J. Y. Yang, G. Y. Si, and P. Luo, Some key issues of war gaming & simulation, J. System Simulation, vol. 22, no. 3, pp. 549–553, 2010.

Google Scholar

[13]

L. Tesfatsion, Agent-based computational economics: Modeling economies as complex adaptive systems, Information Sciences, vol. 149, no. 4, pp. 262–268, 2003.

DOI Google Scholar

[14]

M. F. Acevedo, J. B. Callicott, M. Monticino, D. Lyons, J. Palomino, J. Rosales, L. Delgado, M. Ablan, J. Davila, G. Tonella, et al., Models of natural and human dynamics in forest landscapes: Cross-site and cross-cultural synthesis, Geoforum, vol. 39, no. 2, pp. 846–866, 2008.

DOI Google Scholar

[15]

K. M. Carley, D. B. Fridsma, E. Casman, A. Yahja, N. Altman, L. C. Chen, B. Kaminsky, and D. Nave, BioWar: Scalable agent-based model of bioattacks, IEEE Trans. Syst. Man Cybern. Part A Syst. Hum., vol. 36, no. 2, pp. 252–265, 2006.

DOI Google Scholar

[16]

C. Cioffi-Revilla and M. Rouleau, MASON RebeLand: An agent-based model of politics, environment, and insurgency, Int. Stud. Rev., vol. 12, no. 1, pp. 31–52, 2010.

DOI Google Scholar

[17]

X. Xue, D. Zhou, F. Chen, X. Yu, Z. Feng, Y. Duan, L. Meng, and M. Zhang, From SOA to VOA: A shift in understanding the operation and evolution of service ecosystem, IEEE Trans. Serv. Comput., vol. 16, no. 1, pp. 315–329, 2023.

DOI Google Scholar

[18]

X. Xue, G. Li, D. Zhou, Y. Zhang, L. Zhang, Y. Zhao, Z. Feng, L. Cui, Z. Zhou, X. Sun, et al., Research roadmap of service ecosystems: A crowd intelligence perspective, International Journal of Crowd Science, vol. 6, no. 4, pp. 195–222, 2022.

DOI Google Scholar

[19]

F. Wang and L. Guo, Research on system complexity of the digital society, (in Chinese), Management World, vol. 38, no. 9, pp. 208–220, 2022.

Google Scholar

[20]

X. Xue, X. Yu, and F. Y. Wang, ChatGPT chats on computational experiments: From interactive intelligence to imaginative intelligence for design of artificial societies and optimization of foundational models, IEEE/CAA J. Autom. Sin., vol. 10, no. 6, pp. 1357–1360, 2023.

DOI Google Scholar

[21]

S. Boschert and R. Rosen, Digital twin—The simulation aspect, in Mechatronic Futures: Challenges and Solutions for Mechatronic Systems and Their Designers, P. Hehenberger and D. Bradley, eds. Cham, Switzerland: Springer, 2016, pp. 59–74.

DOI

[22]

F. Y. Wang, Parallel system methods for management and control of complex systems, (in Chinese), Control and Decision, vol. 19, no. 5, pp. 485–489&514, 2004.

Google Scholar

[23]

X. Xue, Computational Experiment Methods for Complex Systems: Principles, Models and Cases, (in Chinese). Beijing, China: Beijing Science Press, 2020.

[24]

X. Xue, F. Chen, D. Zhou, X. Wang, M. Lu, and F. Y. Wang, Computational experiments for complex social systems—Part I: The customization of computational model, IEEE Trans. Comput. Soc. Syst., vol. 9, no. 5, pp. 1330–1344, 2022.

DOI Google Scholar

[25]

M. Lu, S. Chen, X. Xue, X. Wang, Y. Zhang, Y. Zhang, and F. Y. Wang, Computational experiments for complex social systems—Part II: The evaluation of computational models, IEEE Trans. Comput. Soc. Syst., vol. 9, no. 4, pp. 1224–1236, 2022.

DOI Google Scholar

[26]

X. Xue, X. Yu, D. Zhou, C. Peng, X. Wang, D. Liu, and F. Y. Wang, Computational experiments for complex social systems—Part III: The docking of domain models, IEEE Trans. Comput. Soc. Syst., doi: 10.1109/TCSS.2023.3243894.

DOI

[27]

I. Prigogine and I. Stengers, Order Out of Chaos: Man’s New Dialogue with Nature. London, UK: Heinemann, 1984.

[28]

X. Xue, S. Wang, B. Gui, and Z. Hou, A computational experiment-based evaluation method for context-aware services in complicated environment, Inf. Sci., vol. 373, pp. 269–286, 2016.

DOI Google Scholar

[29]

X. Wang, M. Kang, H. Sun, P. D. Reffye, and F. Y. Wang, DeCASA in AgriVerse: Parallel agriculture for smart villages in metaverses, IEEE/CAA J. Autom. Sin., vol. 9, no. 12, pp. 2055–2062, 2022.

DOI Google Scholar

[30]

M. Kang, X. Wang, H. Wang, J. Hua, P. D. Reffye, and F. Y. Wang, The development of AgriVerse: Past, present, and future, IEEE Trans. Syst. Man Cybern, Syst., vol. 53, no. 6, pp. 3718–3727, 2023.

DOI Google Scholar

[31]

J. Gu, J. Wang, X. Guo, G. Liu, S. Qin, and Z. Bi, A metaverse-based teaching building evacuation training system with deep reinforcement learning, IEEE Trans. Syst. Man Cybern. Syst., vol. 53, no. 4, pp. 2209–2219, 2023.

DOI Google Scholar

[32]

F. Y. Wang, Parallel intelligence in metaverses: Welcome to Hanoi! IEEE Intell. Syst., vol. 37, no. 1, pp. 16–20, 2022.

DOI

[33]

H. Duan, J. Li, S. Fan, Z. Lin, X. Wu, and W. Cai, Metaverse for social good: A university campus prototype, in Proc. 29^th ACM Int. Conf. Multimedia, Virtual Event, China, 2021, pp. 153–161.

DOI

[34]

M. A. I. Mozumder, M. M. Sheeraz, A. Athar, S. Aich, and H. C. Kim, Overview: Technology roadmap of the future trend of metaverse based on IoT, blockchain, AI technique, and medical domain metaverse activity, in Proc. 2022 24^th Int. Conf. Advanced Communication Technology (ICACT), PyeongChang, Republic of Korea, 2022, pp. 256–261.

DOI

[35]

H. J. Kwon, A. E. Azzaoui, and J. H. Park, Metaq: A quantum approach for secure and optimized metaverse environment, Hum.-Cent. Comput. Inf. Sci., vol. 12, p. 42, 2022.

Google Scholar

[36]

Z. Allam, A. Sharifi, S. E. Bibri, D. S. Jones, and J. Krogstie, The metaverse as a virtual form of smart cities: Opportunities and challenges for environmental, economic, and social sustainability in urban futures, Smart Cities, vol. 5, no. 3, pp. 771–801, 2022.

DOI Google Scholar

[37]

M. M. Inceoglu and B. Ciloglugil, Use of metaverse in education, in Proc. Int. Conf. Computational Science and its Applications, Malaga, Spain, 2022, pp. 171–184.

DOI

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Received: 20 June 2023

Revised: 30 July 2023

Accepted: 07 September 2023

Published: 22 December 2023

Issue date: December 2023

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