Anticipatory Thinking in Multi-Agent Contexts
Resumo
Anticipatory thinking allows agents to foresee and avoid future problems by exploiting their plan libraries. This paper extends previous work on anticipatory thinking for single agents to the domain of Multi-Agent Systems (MAS), where the environment’s evolution depends on the combined actions of multiple autonomous agents. We detail how an agent can simulate potential futures in a multi-agent context, considering the preferred policies of all participants, to anticipate and react to undesirable outcomes. Our proposed strategies enable an agent to either abandon a goal if a problem is inevitable or dynamically select an alternative plan to avoid anticipated problems. Experiments in a Bridge Scenario, a classic Multi-Agent Pathfinding problem, yield a critical insight: anticipatory thinking, in isolation, only resolves the conflict when exactly one agent exercises this foresight. When multiple agents independently reason about the future, the problem re-emerges, indicating a fundamental limitation of purely individualistic anticipation and stressing the importance of future research into integrated anticipatory thinking and coordination.
Referências
Amos-Binks, A. and Dannenhauer, D. (2019). Anticipatory thinking: A metacognitive capability. In Proc. of the Workshop on Cognitive Systems for Anticipatory Thinking.
Amos-Binks, A., Dannenhauer, D., and Gilpin, L. H. (2023). The anticipatory paradigm. AI Magazine, 44(2):133–143.
Baitiche, H., Bouzenada, M., and Saïdouni, D. E. (2017). Towards a generic predictive-based plan selection approach for bdi agents. Procedia Computer Science, 113:41–48. The 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2017) / The 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2017) / Affiliated Workshops.
Boissier, O., Bordini, R., Hübner, J. F., Ricci, A., and Santi, A. (2013). Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 78(6):747–761.
Bordini, R. H., Hübner, J. F., and Wooldrige, M. (2007). Programming Multi-Agent Systems in AgentSpeak using Jason. Wiley Series in Agent Technology. John Wiley & Sons, England.
Bordini, R. H., Visser, W., Fisher, M., Pardavila, C., and Wooldridge, M. (2003). Model checking multi-agent programs with CASP. In Pre-proceedings of Third Workshop on Automated Verification of Critical Systems (AVoCS 2003), 2–3 April, Southampton, U.K.
Bratman, M. E. (1987). Intention, Plans, and Practical Reason. Harvard University Press, Cambridge.
Cohen, P. R. and Levesque, H. J. (1987). Intention = choice + commitment. In Proceedings of the 6th National Conference on Artificial Intelligence, pages 410–415, Cambridge. Morgan Kaufmann.
da Rocha Costa, A. C., Hübner, J. F., and Bordini, R. H. (1994). On entering an open society. In Anais do XI Simpósio Brasileiro de Inteligência Artificial, pages 535–546, Fortaleza.
Dann, M., Thangarajah, J., and Li, M. (2023). Feedback-guided intention scheduling for bdi agents. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS’23, pages 1173–1181.
Dastani, M. (2008). 2APL: a practical agent programming language. Autonomous Agent and Multi-Agent Systems, 16:241–248.
Ferrando, A. and Cardoso, R. C. (2023). Failure handling in BDI plans via runtime enforcement. In Gal, K., Nowé, A., Nalepa, G. J., Fairstein, R., and Radulescu, R., editors, ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), volume 372 of Frontiers in Artificial Intelligence and Applications, pages 716–723. IOS Press.
Georgeff, M. P. and Lansky, A. L. (1987). Reactive reasoning and planning. In Proc. of the Sixth National Conference on Artificial Intelligence (AAAI 87), pages 677–682.
Ghallab, M., Nau, D., and Traverso, P. (2016). Automated Planning and Acting. Cambridge University Press, Cambridge.
Hindriks, K. V. (2009). Programming rational agents in GOAL. In Bordini, R. H., Dastani, M., Dix, J., and Seghrouchni, A. E. F., editors, Multi-Agent Programming, pages 119–157. Springer, Cham.
Hübner, J. F., Burattini, S., Ricci, A., and Mayer, S. (2025). Reflexive anticipatory reasoning by BDI agents. Auton. Agents Multi Agent Syst., 39(1):7.
Jones, S. J. and Laird, J. E. (2023). A cognitive architecture theory of anticipatory thinking. AI Magazine, 44(2):155–164.
Kamali, M., Dennis, L. A., McAree, O., Fisher, M., and Veres, S. M. (2017). Formal verification of autonomous vehicle platooning. Science of Computer Programming, 148:88 – 106. Special issue on Automated Verification of Critical Systems (AVoCS 2015).
Laird, J. E. (2019). The SOAR Cognitive Architecture. The MIT Press, Cambridge.
Logan, B., Thangarajah, J., and Yorke-Smith, N. (2017). Progressing intention progression: A call for a goal-plan tree contest. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, AAMAS’17, pages 768–772.
Meneguzzi, F. and De Silva, L. (2015). Planning in BDI agents: a survey of the integration of planning algorithms and agent reasoning. The Knowledge Engineering Review, 30(1):1–44.
Moan, R. A., McBeth, C., Morales, M., Amato, N. M., and Hauser, K. (2024). Experience-based multi-agent path finding with narrow corridors. In Robotics: Science and Systems.
Pokahr, A., Braubach, L., and Lamersdorf, W. (2005). Jadex: A BDI reasoning engine. In Bordini, R. H., Dastani, M., Dix, J., and El Fallah Seghrouchni, A., editors, Multi-Agent Programming: Languages, Platforms, and Applications, number 15 in Multiagent Systems, Artificial Societies, and Simulated Organizations, chapter 6, pages 149–174. Springer, Cham.
Rao, A. S. and Georgeff, M. P. (1995). BDI agents: from theory to practice. In Lesser, V., editor, Proceedings of the First International Conference on MultiAgent Systems (ICMAS’95), pages 312–319, San Francisco, USA. AAAI Pess.
Russell, S. J. and Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Prentice Hall, New Jersey, 3 edition.
Sardina, S. and Padgham, L. (2011). A BDI agent programming language with failure handling, declarative goals, and planning. Autonomous Agents and Multi-Agent Systems, 23(1):18–70.
Silva, L. d., Meneguzzi, F., and Logan, B. (2020). BDI agent architectures: A survey. In Bessiere, C., editor, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, pages 4914–4921.
Silver, D. (2021). Cooperative pathfinding. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 1(1):117–122.
Singh, D., Sardina, S., and Padgham, L. (2010). Extending BDI plan selection to incorporate learning from experience. Robotics and Autonomous Systems, 58(9):1067–1075. Hybrid Control for Autonomous Systems.
Söderström, T. and Stoica, P. (1989). System identification. Prentice Hall, Saddle River, New Jersey.
Stern, R., Sturtevant, N., Felner, A., Koenig, S., Ma, H., Walker, T., Li, J., Atzmon, D., Cohen, L., Kumar, T., and Boyarski, E. (2021). Multi-agent pathfinding: Definitions, variants, and benchmarks. Proceedings of the International Symposium on Combinatorial Search, 10:151–158.
Surynek, P. (2022). Problem compilation for multi-agent path finding: a survey. In Raedt, L. D., editor, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pages 5615–5622. International Joint Conferences on Artificial Intelligence Organization. Survey Track.
Sutton, R. S. and Barto, A. G. (1998). Reinforcement Learning: An Introduction. Bradford, Cambridge.
Szpunar, K. K., Spreng, R. N., and Schacter, D. L. (2014). A taxonomy of prospection: Introducing an organizational framework for future-oriented cognition. Proceedings of the National Academy of Sciences, 111(52):18414–18421.
Thangarajah, J., Padgham, L., and Winikoff, M. (2003). Detecting & Avoiding Interference Between Goals in Intelligent Agents. In IJCAI’03: Proceedings of the 18th international joint conference on Artificial intelligence, pages 721–726.
Uez, D. M. and Hübner, J. F. (2017). Modeling for openness in MAS. In Fallah-Seghrouchi, A. E., Son, T. C., and Ricci, A., editors, Pre Proc. of 5th International Workshop on Engineering Multi-Agent Systems (EMAS@AAMAS 2017), pages 174–189.
Wang, S., Xu, H., Zhang, Y., Lin, J., Lu, C., Wang, X., and Li, W. (2025). Where paths collide: A comprehensive survey of classic and learning-based multi-agent pathfinding. [link].
Yao, Y., Logan, B., and Thangarajah, J. (2014). Sp-mcts-based intention scheduling for bdi agents. In Proceedings of the Twenty-First European Conference on Artificial Intelligence, ECAI’14, pages 1133–1134, NLD. IOS Press.
Amos-Binks, A., Dannenhauer, D., and Gilpin, L. H. (2023). The anticipatory paradigm. AI Magazine, 44(2):133–143.
Baitiche, H., Bouzenada, M., and Saïdouni, D. E. (2017). Towards a generic predictive-based plan selection approach for bdi agents. Procedia Computer Science, 113:41–48. The 8th International Conference on Emerging Ubiquitous Systems and Pervasive Networks (EUSPN 2017) / The 7th International Conference on Current and Future Trends of Information and Communication Technologies in Healthcare (ICTH-2017) / Affiliated Workshops.
Boissier, O., Bordini, R., Hübner, J. F., Ricci, A., and Santi, A. (2013). Multi-agent oriented programming with JaCaMo. Science of Computer Programming, 78(6):747–761.
Bordini, R. H., Hübner, J. F., and Wooldrige, M. (2007). Programming Multi-Agent Systems in AgentSpeak using Jason. Wiley Series in Agent Technology. John Wiley & Sons, England.
Bordini, R. H., Visser, W., Fisher, M., Pardavila, C., and Wooldridge, M. (2003). Model checking multi-agent programs with CASP. In Pre-proceedings of Third Workshop on Automated Verification of Critical Systems (AVoCS 2003), 2–3 April, Southampton, U.K.
Bratman, M. E. (1987). Intention, Plans, and Practical Reason. Harvard University Press, Cambridge.
Cohen, P. R. and Levesque, H. J. (1987). Intention = choice + commitment. In Proceedings of the 6th National Conference on Artificial Intelligence, pages 410–415, Cambridge. Morgan Kaufmann.
da Rocha Costa, A. C., Hübner, J. F., and Bordini, R. H. (1994). On entering an open society. In Anais do XI Simpósio Brasileiro de Inteligência Artificial, pages 535–546, Fortaleza.
Dann, M., Thangarajah, J., and Li, M. (2023). Feedback-guided intention scheduling for bdi agents. In Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems, AAMAS’23, pages 1173–1181.
Dastani, M. (2008). 2APL: a practical agent programming language. Autonomous Agent and Multi-Agent Systems, 16:241–248.
Ferrando, A. and Cardoso, R. C. (2023). Failure handling in BDI plans via runtime enforcement. In Gal, K., Nowé, A., Nalepa, G. J., Fairstein, R., and Radulescu, R., editors, ECAI 2023 - 26th European Conference on Artificial Intelligence, September 30 - October 4, 2023, Kraków, Poland - Including 12th Conference on Prestigious Applications of Intelligent Systems (PAIS 2023), volume 372 of Frontiers in Artificial Intelligence and Applications, pages 716–723. IOS Press.
Georgeff, M. P. and Lansky, A. L. (1987). Reactive reasoning and planning. In Proc. of the Sixth National Conference on Artificial Intelligence (AAAI 87), pages 677–682.
Ghallab, M., Nau, D., and Traverso, P. (2016). Automated Planning and Acting. Cambridge University Press, Cambridge.
Hindriks, K. V. (2009). Programming rational agents in GOAL. In Bordini, R. H., Dastani, M., Dix, J., and Seghrouchni, A. E. F., editors, Multi-Agent Programming, pages 119–157. Springer, Cham.
Hübner, J. F., Burattini, S., Ricci, A., and Mayer, S. (2025). Reflexive anticipatory reasoning by BDI agents. Auton. Agents Multi Agent Syst., 39(1):7.
Jones, S. J. and Laird, J. E. (2023). A cognitive architecture theory of anticipatory thinking. AI Magazine, 44(2):155–164.
Kamali, M., Dennis, L. A., McAree, O., Fisher, M., and Veres, S. M. (2017). Formal verification of autonomous vehicle platooning. Science of Computer Programming, 148:88 – 106. Special issue on Automated Verification of Critical Systems (AVoCS 2015).
Laird, J. E. (2019). The SOAR Cognitive Architecture. The MIT Press, Cambridge.
Logan, B., Thangarajah, J., and Yorke-Smith, N. (2017). Progressing intention progression: A call for a goal-plan tree contest. In Proceedings of the 16th Conference on Autonomous Agents and MultiAgent Systems, AAMAS’17, pages 768–772.
Meneguzzi, F. and De Silva, L. (2015). Planning in BDI agents: a survey of the integration of planning algorithms and agent reasoning. The Knowledge Engineering Review, 30(1):1–44.
Moan, R. A., McBeth, C., Morales, M., Amato, N. M., and Hauser, K. (2024). Experience-based multi-agent path finding with narrow corridors. In Robotics: Science and Systems.
Pokahr, A., Braubach, L., and Lamersdorf, W. (2005). Jadex: A BDI reasoning engine. In Bordini, R. H., Dastani, M., Dix, J., and El Fallah Seghrouchni, A., editors, Multi-Agent Programming: Languages, Platforms, and Applications, number 15 in Multiagent Systems, Artificial Societies, and Simulated Organizations, chapter 6, pages 149–174. Springer, Cham.
Rao, A. S. and Georgeff, M. P. (1995). BDI agents: from theory to practice. In Lesser, V., editor, Proceedings of the First International Conference on MultiAgent Systems (ICMAS’95), pages 312–319, San Francisco, USA. AAAI Pess.
Russell, S. J. and Norvig, P. (2010). Artificial Intelligence: A Modern Approach. Prentice Hall, New Jersey, 3 edition.
Sardina, S. and Padgham, L. (2011). A BDI agent programming language with failure handling, declarative goals, and planning. Autonomous Agents and Multi-Agent Systems, 23(1):18–70.
Silva, L. d., Meneguzzi, F., and Logan, B. (2020). BDI agent architectures: A survey. In Bessiere, C., editor, Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, IJCAI-20, pages 4914–4921.
Silver, D. (2021). Cooperative pathfinding. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, 1(1):117–122.
Singh, D., Sardina, S., and Padgham, L. (2010). Extending BDI plan selection to incorporate learning from experience. Robotics and Autonomous Systems, 58(9):1067–1075. Hybrid Control for Autonomous Systems.
Söderström, T. and Stoica, P. (1989). System identification. Prentice Hall, Saddle River, New Jersey.
Stern, R., Sturtevant, N., Felner, A., Koenig, S., Ma, H., Walker, T., Li, J., Atzmon, D., Cohen, L., Kumar, T., and Boyarski, E. (2021). Multi-agent pathfinding: Definitions, variants, and benchmarks. Proceedings of the International Symposium on Combinatorial Search, 10:151–158.
Surynek, P. (2022). Problem compilation for multi-agent path finding: a survey. In Raedt, L. D., editor, Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, IJCAI-22, pages 5615–5622. International Joint Conferences on Artificial Intelligence Organization. Survey Track.
Sutton, R. S. and Barto, A. G. (1998). Reinforcement Learning: An Introduction. Bradford, Cambridge.
Szpunar, K. K., Spreng, R. N., and Schacter, D. L. (2014). A taxonomy of prospection: Introducing an organizational framework for future-oriented cognition. Proceedings of the National Academy of Sciences, 111(52):18414–18421.
Thangarajah, J., Padgham, L., and Winikoff, M. (2003). Detecting & Avoiding Interference Between Goals in Intelligent Agents. In IJCAI’03: Proceedings of the 18th international joint conference on Artificial intelligence, pages 721–726.
Uez, D. M. and Hübner, J. F. (2017). Modeling for openness in MAS. In Fallah-Seghrouchi, A. E., Son, T. C., and Ricci, A., editors, Pre Proc. of 5th International Workshop on Engineering Multi-Agent Systems (EMAS@AAMAS 2017), pages 174–189.
Wang, S., Xu, H., Zhang, Y., Lin, J., Lu, C., Wang, X., and Li, W. (2025). Where paths collide: A comprehensive survey of classic and learning-based multi-agent pathfinding. [link].
Yao, Y., Logan, B., and Thangarajah, J. (2014). Sp-mcts-based intention scheduling for bdi agents. In Proceedings of the Twenty-First European Conference on Artificial Intelligence, ECAI’14, pages 1133–1134, NLD. IOS Press.
Publicado
29/09/2025
Como Citar
HÜBNER, Jomi F.; BURATTINI, Samuele; RICCI, Alessandro; MAYER, Simon.
Anticipatory Thinking in Multi-Agent Contexts. 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. 1-12.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2025.37525.
