Towards a Visual Programming Framework for BDI Agents
Resumo
Visual programming frameworks can lower the barrier to entry for agent-based development by allowing users to design agent behaviours through graphical abstractions rather than code. However, it remains unclear which agent architectures and visual programming paradigms have been most commonly explored in this area. To address this gap, this paper presents a systematic mapping study of visual programming frameworks for agent-based development, categorising relevant studies by agent architecture and visual programming paradigm. The results show a predominance of reactive agents and flow-based models, with most frameworks targeting computer science laypeople and robotics applications. Based on these findings, the paper also presents a prototype visual programming framework for Belief-Desire-Intention agents.Referências
Bratman, M. E., Israel, D. J., and Pollack, M. E. (1988). Plans and resource-bounded practical reasoning. Computational Intelligence, 4(4):349–355.
Chan, K. H., Zilberman, S., and Cheng, B. H. C. (2026). Savvidriver: model-based framework for game-based testing of autonomous vehicles in diverse multi-agent traffic scenarios: Savvidriver: model-based framework for game-based testing... Softw. Syst. Model., 25(1):135–161.
Chen, J., Horn, M., and Wilensky, U. (2024). Interactive constructionist scaffolds for agent-based modeling and programming in netlogo. In Proceedings of FabLearn / Constructionism 2023: Full and Short Research Papers, FLC ’23, New York, NY, USA. Association for Computing Machinery.
Chen, J., Zhao, L., Horn, M., and Wilensky, U. (2023). The pocketworld playground: Engaging online, out-of-school learners with agent-based programming. In Proceedings of the 22nd Annual ACM Interaction Design and Children Conference, IDC ’23, page 267–277, New York, NY, USA. Association for Computing Machinery.
Cohen, P. R. and Levesque, H. J. (1990). Intention is choice with commitment. Artificial Intelligence, 42(2–3):213–261.
Godfrey, T. (2021). Domain-specific modelling languages for participatory agent-based modelling in healthcare. In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), pages 654–659.
Harel, D. (1987). Statecharts: A visual formalism for complex systems. Science of Computer Programming, 8(3):231–274.
Hayes, B. E. (2008). Measuring customer satisfaction and loyalty: survey design, use, and statistical analysis methods. ASQ Quality Press.
Kitchenham, B. A. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.
Kuhail, M. A., Farooq, S., Hammad, R., and Bahja, M. (2021). Characterizing visual programming approaches for end-user developers: A systematic review. IEEE Access, 9:14181–14202.
Mellado, A. L. L., Pinz Borges, A., and Alves, G. V. (2026). Maspy: A python-based framework for developing bdi multi-agent systems. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Computational Social Science: The PAAMS Collection, pages 216–227, Cham. Springer Nature Switzerland.
Nielsen, J. (2024). 10 usability heuristics for user interface design.
Porfirio, D., Roberts, M., and Hiatt, L. M. (2024). Goal-oriented end-user programming of robots. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’24, page 582–591, New York, NY, USA. Association for Computing Machinery.
Poursoltan, M., Pinède, N., Vallespir, B., and Traore, M. K. (2022). A new modeling framework for cyber-physical and human systems. In 2022 Annual Modeling and Simulation Conference (ANNSIM), pages 90–101.
Sartori, A. and Schlette, C. (2021). Visual programming of a human-machine interface for a multi-robot support system. pages 387–392.
Tezel, B. T. and Kardas, G. (2025). Debugging in the domain-specific modeling languages for multi-agent systems. J. Comput. Lang., 83:101325.
Wiesmayr, B., Zoitl, A., and Hästbacka, D. (2024). Modeling service choreographies and collaborative tasks for autonomous mixed-fleet systems. In Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, MODELS Companion ’24, page 234–244, New York, NY, USA. Association for Computing Machinery.
Williams, R., Ali, S., Alcantara, R., Burghleh, T., Alghowinem, S., and Breazeal, C. (2024). Doodlebot: An educational robot for creativity and ai literacy. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’24, page 772–780, New York, NY, USA. Association for Computing Machinery.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. Wiley.
Chan, K. H., Zilberman, S., and Cheng, B. H. C. (2026). Savvidriver: model-based framework for game-based testing of autonomous vehicles in diverse multi-agent traffic scenarios: Savvidriver: model-based framework for game-based testing... Softw. Syst. Model., 25(1):135–161.
Chen, J., Horn, M., and Wilensky, U. (2024). Interactive constructionist scaffolds for agent-based modeling and programming in netlogo. In Proceedings of FabLearn / Constructionism 2023: Full and Short Research Papers, FLC ’23, New York, NY, USA. Association for Computing Machinery.
Chen, J., Zhao, L., Horn, M., and Wilensky, U. (2023). The pocketworld playground: Engaging online, out-of-school learners with agent-based programming. In Proceedings of the 22nd Annual ACM Interaction Design and Children Conference, IDC ’23, page 267–277, New York, NY, USA. Association for Computing Machinery.
Cohen, P. R. and Levesque, H. J. (1990). Intention is choice with commitment. Artificial Intelligence, 42(2–3):213–261.
Godfrey, T. (2021). Domain-specific modelling languages for participatory agent-based modelling in healthcare. In 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), pages 654–659.
Harel, D. (1987). Statecharts: A visual formalism for complex systems. Science of Computer Programming, 8(3):231–274.
Hayes, B. E. (2008). Measuring customer satisfaction and loyalty: survey design, use, and statistical analysis methods. ASQ Quality Press.
Kitchenham, B. A. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001, Keele University and Durham University Joint Report.
Kuhail, M. A., Farooq, S., Hammad, R., and Bahja, M. (2021). Characterizing visual programming approaches for end-user developers: A systematic review. IEEE Access, 9:14181–14202.
Mellado, A. L. L., Pinz Borges, A., and Alves, G. V. (2026). Maspy: A python-based framework for developing bdi multi-agent systems. In Advances in Practical Applications of Agents, Multi-Agent Systems, and Computational Social Science: The PAAMS Collection, pages 216–227, Cham. Springer Nature Switzerland.
Nielsen, J. (2024). 10 usability heuristics for user interface design.
Porfirio, D., Roberts, M., and Hiatt, L. M. (2024). Goal-oriented end-user programming of robots. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’24, page 582–591, New York, NY, USA. Association for Computing Machinery.
Poursoltan, M., Pinède, N., Vallespir, B., and Traore, M. K. (2022). A new modeling framework for cyber-physical and human systems. In 2022 Annual Modeling and Simulation Conference (ANNSIM), pages 90–101.
Sartori, A. and Schlette, C. (2021). Visual programming of a human-machine interface for a multi-robot support system. pages 387–392.
Tezel, B. T. and Kardas, G. (2025). Debugging in the domain-specific modeling languages for multi-agent systems. J. Comput. Lang., 83:101325.
Wiesmayr, B., Zoitl, A., and Hästbacka, D. (2024). Modeling service choreographies and collaborative tasks for autonomous mixed-fleet systems. In Proceedings of the ACM/IEEE 27th International Conference on Model Driven Engineering Languages and Systems, MODELS Companion ’24, page 234–244, New York, NY, USA. Association for Computing Machinery.
Williams, R., Ali, S., Alcantara, R., Burghleh, T., Alghowinem, S., and Breazeal, C. (2024). Doodlebot: An educational robot for creativity and ai literacy. In Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction, HRI ’24, page 772–780, New York, NY, USA. Association for Computing Machinery.
Wooldridge, M. (2009). An Introduction to MultiAgent Systems. Wiley.
Publicado
19/10/2026
Como Citar
RENTSCHLER, Helena; NERES, Gabriel G.; CARDOSO, Rafael C.; BORGES, André Pinz; ALVES, Gleifer Vaz.
Towards a Visual Programming Framework for BDI Agents. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 20. , 2026, Cuiabá/MT.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 204-215.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2026.31746.
