A Multi-Agent organizational modeling at the backend of a metaversity
Resumo
Advances on Artificial Intelligence (AI) have inspired the design of innovative applications for education. However, its poorly planned use has led to a number of pitfalls mapped in literature, along with recommendations towards responsible AI. We are currently investigating how Multi-Agent Systems (MAS) can enhance higher education. In this paper, we introduce a MAS organizational modeling of typical campus, at the backend of a decentralized metaverse platform. The model is proposed to be scalable and refinable, such as to fit specific requirements of institutions eventually reusing it, and serve as a sand-box for teaching/research AI for education (and education for AI). Model dissemination and instantiation should provide empirical evidence for further analysis.
Referências
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Behr, A., Cascalho, J., Mendes, A., Guerra, H., Cavique, L., Trigo, P., Coelho, H., and Vicari, R. (2022). Bringing underused learning objects to the light: a multi-agent based approach. In EPIA Conference on Artificial Intelligence, pages 751–763. Springer.
Bez, M. R., Flores, C. D., Fonseca, J. M., Maroni, V., Barros, P. R., and Vicari, R. M. (2012). Influence diagram for selection of pedagogical strategies in a multi-agent system learning. In Advances in Artificial Intelligence–IBERAMIA 2012: 13th Ibero-American Conference on AI, Cartagena de Indias, Colombia, November 13-16, 2012. Proceedings 13, pages 621–630. Springer.
Born, M. B., de Aguiar, M. S., and Adamatti, D. F. (2023). Modelagem da estrutura organizacional do sistema multiagente associado a um jogo rpg no contexto de recursos hídricos. In Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações (WESAAC), pages 136–147. SBC.
Chebout, M. S., Marir, T., and Gupta, V. (2023). Noragr: a normative agent groupe role model for organizational centered open multi-agent systems. In 2023 Third International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), pages 1–5. IEEE.
Chu, Z., Wang, S., Xie, J., Zhu, T., Yan, Y., Ye, J., Zhong, A., Hu, X., Liang, J., Yu, P. S., et al. (2025). LLM agents for education: Advances and applications. arXiv preprint arXiv:2503.11733.
de Barros Costa, E., Lopes, M. A., and Ferneda, E. (1995). Mathema: A learning environment based on a multi-agent architecture. In Advances in Artificial Intelligence: 12th Brazilian Symposium on Artificial Intelligence SBIA’95, Campinas, Brazil, October 10–12, 1995 Proceedings 12, pages 141–150. Springer.
Ferber, J., Gutknecht, O., and Michel, F. (2003). From agents to organizations: an organizational view of multi-agent systems. In International workshop on agent-oriented software engineering, pages 214–230. Springer.
Giraffa, L. M., Viccari, R. M., and Self, J. (1998). Multi-agent based pedagogical games. In Intelligent Tutoring Systems: 4th International Conference, ITS’98 San Antonio, Texas, USA, August 16–19, 1998 Proceedings 4, pages 607–607. Springer.
Han, J., Liu, G., and Gao, Y. (2023). Learners in the metaverse: A systematic review on the use of roblox in learning. Education Sciences, 13(3):296.
Hasibuan, M. and Nugroho, L. (2016). Detecting learning style using hybrid model. In 2016 IEEE Conference on e-Learning, e-Management and e-Services (IC3e), pages 107–111. IEEE.
Hassanzadeh, M. (2022). Metaverse, metaversity, and the future of higher education. Sciences & Techniques of Information Management, 8(2).
Hooshyar, D., Šír, G., Yang, Y., Kikas, E., Hämäläinen, R., Kärkkäinen, T., Gašević, D., and Azevedo, R. (2025). Towards responsible ai for education: Hybrid human-ai to confront the elephant in the room. arXiv preprint arXiv:2504.16148.
Johnson, W. L. and Lester, J. C. (2018). Pedagogical agents: back to the future. AI Magazine, 39(2):33–44.
Lane, H. C. and Schroeder, N. L. (2022). Pedagogical agents. In The handbook on socially interactive agents: 20 years of research on embodied conversational agents, intelligent virtual agents, and social robotics volume 2: Interactivity, platforms, application, pages 307–330.
Laurens-Arredondo, L. A. (2024). Metaversity as the learning ecology in the age of the metaverse: A systematic review. Comunicar, 33(79):10–22.
Lee, L.-H., Hosio, S., Braud, T., and Zhou, P. (2024). A roadmap toward metaversity: Recent developments and perspectives in education. Application of the Metaverse in Education, pages 73–95.
Li, Q., Xie, Y., Chakravarty, S., and Lee, D. (2024). EduMAS: A novel LLM-Powered Multi-Agent Framework for Educational Support. In 2024 IEEE International Conference on Big Data (BigData), pages 8309–8316. IEEE.
Lin, H., Wan, S., Gan, W., Chen, J., and Chao, H.-C. (2022). Metaverse in education: Vision, opportunities, and challenges. In 2022 IEEE International Conference on Big Data (Big Data), pages 2857–2866. IEEE.
Mansour, E., Sambra, A. V., Hawke, S., Zereba, M., Capadisli, S., Ghanem, A., Aboulnaga, A., and Berners-Lee, T. (2016). A demonstration of the solid platform for social web applications. In Proceedings of the 25th international conference companion on world wide web, pages 223–226.
Mohamedhen, A. S., Alfazi, A., Arfaoui, N., Ejbali, R., and Nanne, M. F. (2024). Towards multi-agent system for learning object recommendation. Heliyon, 10(20):e39088.
Nkambou, R., Brisson, J., Tato, A., and Robert, S. (2023). Learning logical reasoning using an intelligent tutoring system: a hybrid approach to student modeling. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 37, pages 15930–15937.
Nóbrega, G., Pains, A., and Cruz, F. (2024). Uma sociedade de companions inteligentes na metaversidade para incrementar a aprendizagem ao longo da vida. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 3085–3096. SBC.
Ottenheimer, D. (2025). Secure AI with data wallets: Privacy-preserving solid architecture for personal data llms. In 3rd Privacy Personal Data Management Session @ Solid Symposium 2025.
Roussille, H., Gürcan, Ö., and Michel, F. (2021). AGR4BS: a generic multi-agent organizational model for blockchain systems. Big Data and Cognitive Computing, 6(1):1.
Ruwodo, V., Pinomaa, A., Vesisenaho, M., Ntinda, M., and Sutinen, E. (2022). Enhancing software engineering education in africa through a metaversity. In 2022 IEEE Frontiers in Education Conference (FIE), pages 1–8. IEEE.
Silveira, R. A. and Vicari, R. M. (2002). Improving interactivity in e-learning systems with multi-agent architecture. In Adaptive Hypermedia and Adaptive Web-Based Systems: Second International Conference, AH 2002 Málaga, Spain, May 29–31, 2002 Proceedings 2, pages 466–471. Springer.
Slabbinck, W., Dedecker, R., Rojas Melendez, J. A., and Verborgh, R. (2023). A rule-based software agent on top of personal data stores. In ISWC2023: the International Semantic Web Conference, volume 3632. CEUR.
Sutikno, T. and Aisyahrani, A. I. B. (2023). Non-fungible tokens, decentralized autonomous organizations, web 3.0, and the metaverse in education: From university to metaversity. Journal of Education and Learning (EduLearn), 17(1):1–15.
Wang, M., Yu, H., Bell, Z., and Chu, X. (2022). Constructing an edu-metaverse ecosystem: A new and innovative framework. IEEE Transactions on Learning Technologies, 15(6):685–696.
Wilensky, U. (1999). Netlogo. [link] Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
Wißner, M., Beek, W., Lozano, E., Mehlmann, G., Linnebank, F., Liem, J., Häring, M., Bühling, R., Gracia, J., Bredeweg, B., et al. (2012). Increasing learners’ motivation through pedagogical agents: The cast of virtual characters in the dynalearn ile. In Agents for Educational Games and Simulations: International Workshop, AEGS 2011, Taipei, Taiwan, May 2, 2011. Revised Papers, pages 151–165. Springer.
Bartoletti, M., Benetollo, L., Bugliesi, M., Crafa, S., Sasso, G. D., Pettinau, R., Pinna, A., Piras, M., Rossi, S., Salis, S., Spanò, A., Tkachenko, V., Tonelli, R., and Zunino, R. (2025). Smart contract languages: A comparative analysis. Future Generation Computer Systems, 164:107563.
Bazzanella, E., Barros, M. M., and Santos, F. (2024). Refatoraçao da extensao netlogo de aprendizagem por reforço para integraçao com a biblioteca burlap. In Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações (WESAAC), pages 51–62. SBC.
Behr, A., Cascalho, J., Mendes, A., Guerra, H., Cavique, L., Trigo, P., Coelho, H., and Vicari, R. (2022). Bringing underused learning objects to the light: a multi-agent based approach. In EPIA Conference on Artificial Intelligence, pages 751–763. Springer.
Bez, M. R., Flores, C. D., Fonseca, J. M., Maroni, V., Barros, P. R., and Vicari, R. M. (2012). Influence diagram for selection of pedagogical strategies in a multi-agent system learning. In Advances in Artificial Intelligence–IBERAMIA 2012: 13th Ibero-American Conference on AI, Cartagena de Indias, Colombia, November 13-16, 2012. Proceedings 13, pages 621–630. Springer.
Born, M. B., de Aguiar, M. S., and Adamatti, D. F. (2023). Modelagem da estrutura organizacional do sistema multiagente associado a um jogo rpg no contexto de recursos hídricos. In Workshop-Escola de Sistemas de Agentes, seus Ambientes e Aplicações (WESAAC), pages 136–147. SBC.
Chebout, M. S., Marir, T., and Gupta, V. (2023). Noragr: a normative agent groupe role model for organizational centered open multi-agent systems. In 2023 Third International Conference on Theoretical and Applicative Aspects of Computer Science (ICTAACS), pages 1–5. IEEE.
Chu, Z., Wang, S., Xie, J., Zhu, T., Yan, Y., Ye, J., Zhong, A., Hu, X., Liang, J., Yu, P. S., et al. (2025). LLM agents for education: Advances and applications. arXiv preprint arXiv:2503.11733.
de Barros Costa, E., Lopes, M. A., and Ferneda, E. (1995). Mathema: A learning environment based on a multi-agent architecture. In Advances in Artificial Intelligence: 12th Brazilian Symposium on Artificial Intelligence SBIA’95, Campinas, Brazil, October 10–12, 1995 Proceedings 12, pages 141–150. Springer.
Ferber, J., Gutknecht, O., and Michel, F. (2003). From agents to organizations: an organizational view of multi-agent systems. In International workshop on agent-oriented software engineering, pages 214–230. Springer.
Giraffa, L. M., Viccari, R. M., and Self, J. (1998). Multi-agent based pedagogical games. In Intelligent Tutoring Systems: 4th International Conference, ITS’98 San Antonio, Texas, USA, August 16–19, 1998 Proceedings 4, pages 607–607. Springer.
Han, J., Liu, G., and Gao, Y. (2023). Learners in the metaverse: A systematic review on the use of roblox in learning. Education Sciences, 13(3):296.
Hasibuan, M. and Nugroho, L. (2016). Detecting learning style using hybrid model. In 2016 IEEE Conference on e-Learning, e-Management and e-Services (IC3e), pages 107–111. IEEE.
Hassanzadeh, M. (2022). Metaverse, metaversity, and the future of higher education. Sciences & Techniques of Information Management, 8(2).
Hooshyar, D., Šír, G., Yang, Y., Kikas, E., Hämäläinen, R., Kärkkäinen, T., Gašević, D., and Azevedo, R. (2025). Towards responsible ai for education: Hybrid human-ai to confront the elephant in the room. arXiv preprint arXiv:2504.16148.
Johnson, W. L. and Lester, J. C. (2018). Pedagogical agents: back to the future. AI Magazine, 39(2):33–44.
Lane, H. C. and Schroeder, N. L. (2022). Pedagogical agents. In The handbook on socially interactive agents: 20 years of research on embodied conversational agents, intelligent virtual agents, and social robotics volume 2: Interactivity, platforms, application, pages 307–330.
Laurens-Arredondo, L. A. (2024). Metaversity as the learning ecology in the age of the metaverse: A systematic review. Comunicar, 33(79):10–22.
Lee, L.-H., Hosio, S., Braud, T., and Zhou, P. (2024). A roadmap toward metaversity: Recent developments and perspectives in education. Application of the Metaverse in Education, pages 73–95.
Li, Q., Xie, Y., Chakravarty, S., and Lee, D. (2024). EduMAS: A novel LLM-Powered Multi-Agent Framework for Educational Support. In 2024 IEEE International Conference on Big Data (BigData), pages 8309–8316. IEEE.
Lin, H., Wan, S., Gan, W., Chen, J., and Chao, H.-C. (2022). Metaverse in education: Vision, opportunities, and challenges. In 2022 IEEE International Conference on Big Data (Big Data), pages 2857–2866. IEEE.
Mansour, E., Sambra, A. V., Hawke, S., Zereba, M., Capadisli, S., Ghanem, A., Aboulnaga, A., and Berners-Lee, T. (2016). A demonstration of the solid platform for social web applications. In Proceedings of the 25th international conference companion on world wide web, pages 223–226.
Mohamedhen, A. S., Alfazi, A., Arfaoui, N., Ejbali, R., and Nanne, M. F. (2024). Towards multi-agent system for learning object recommendation. Heliyon, 10(20):e39088.
Nkambou, R., Brisson, J., Tato, A., and Robert, S. (2023). Learning logical reasoning using an intelligent tutoring system: a hybrid approach to student modeling. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 37, pages 15930–15937.
Nóbrega, G., Pains, A., and Cruz, F. (2024). Uma sociedade de companions inteligentes na metaversidade para incrementar a aprendizagem ao longo da vida. In Simpósio Brasileiro de Informática na Educação (SBIE), pages 3085–3096. SBC.
Ottenheimer, D. (2025). Secure AI with data wallets: Privacy-preserving solid architecture for personal data llms. In 3rd Privacy Personal Data Management Session @ Solid Symposium 2025.
Roussille, H., Gürcan, Ö., and Michel, F. (2021). AGR4BS: a generic multi-agent organizational model for blockchain systems. Big Data and Cognitive Computing, 6(1):1.
Ruwodo, V., Pinomaa, A., Vesisenaho, M., Ntinda, M., and Sutinen, E. (2022). Enhancing software engineering education in africa through a metaversity. In 2022 IEEE Frontiers in Education Conference (FIE), pages 1–8. IEEE.
Silveira, R. A. and Vicari, R. M. (2002). Improving interactivity in e-learning systems with multi-agent architecture. In Adaptive Hypermedia and Adaptive Web-Based Systems: Second International Conference, AH 2002 Málaga, Spain, May 29–31, 2002 Proceedings 2, pages 466–471. Springer.
Slabbinck, W., Dedecker, R., Rojas Melendez, J. A., and Verborgh, R. (2023). A rule-based software agent on top of personal data stores. In ISWC2023: the International Semantic Web Conference, volume 3632. CEUR.
Sutikno, T. and Aisyahrani, A. I. B. (2023). Non-fungible tokens, decentralized autonomous organizations, web 3.0, and the metaverse in education: From university to metaversity. Journal of Education and Learning (EduLearn), 17(1):1–15.
Wang, M., Yu, H., Bell, Z., and Chu, X. (2022). Constructing an edu-metaverse ecosystem: A new and innovative framework. IEEE Transactions on Learning Technologies, 15(6):685–696.
Wilensky, U. (1999). Netlogo. [link] Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL.
Wißner, M., Beek, W., Lozano, E., Mehlmann, G., Linnebank, F., Liem, J., Häring, M., Bühling, R., Gracia, J., Bredeweg, B., et al. (2012). Increasing learners’ motivation through pedagogical agents: The cast of virtual characters in the dynalearn ile. In Agents for Educational Games and Simulations: International Workshop, AEGS 2011, Taipei, Taiwan, May 2, 2011. Revised Papers, pages 151–165. Springer.
Publicado
29/09/2025
Como Citar
NÓBREGA, Germana; SERRANO, Milene; SERRANO, Maurício; CRUZ, Fernando; FREITAS, Fred.
A Multi-Agent organizational modeling at the backend of a metaversity. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 19. , 2025, Fortaleza/CE.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 183-194.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2025.37534.
