Wumpus Verse: A Web Platform Prototype for Development and Evaluation of Agents in the Wumpus World
Resumo
Este trabalho apresenta o protótipo de uma plataforma web projetada para oferecer um ambiente de testes intuitivo, agradável e prático para agentes inteligentes no ambiente do Mundo do Wumpus. Voltada para a experimentação e à pesquisa em Inteligência Artificial, a ferramenta permite que o usuário customize ambientes livremente e configure diferentes tipos de agentes. O sistema viabiliza a execução de experimentos combinados com geração de métricas de desempenho, além de garantir a persistência e a reprodução de simulações passadas. A plataforma simplifica a experimentação prática, fornecendo um ecossistema visual que aproxima usuários de conceitos de inteligência artificial.Referências
Bryce, D. (2011). Wumpus world in introductory artificial intelligence. Journal of Computing Sciences in Colleges, 27(2):58–65.
Julien, D. L. L. and Machado, A. (2015). The wumpus world: Implementing a multi-agent system. Technical report, Technical Report, Salvador, Brazil.
Lasisi, R. O., Philips, C., and Hartnett, N. (2022). ALP4AI: Agent-based learning platform for introductory artificial intelligence. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), pages 1–9.
Li, H., Li, Z., Huang, W., and Guo, X. (2025). LLM-Cave: A benchmark and light environment for large language models reasoning and decision-making system. arXiv preprint arXiv:2511.22598.
Russell, S. and Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson, 4 edition.
Salehi, S., Saffar, M. T., Taghiyareh, F., and Badie, K. (2012). A multi-context dynamic test bed for simulating real-world constraints in agents’ teamwork. In Proceedings of the 6th International Symposium on Telecommunications (IST 2012), pages 1–6. IEEE.
Yob, G. (1975). Hunt the wumpus. Creative Computing, 1(5):51–54.
Julien, D. L. L. and Machado, A. (2015). The wumpus world: Implementing a multi-agent system. Technical report, Technical Report, Salvador, Brazil.
Lasisi, R. O., Philips, C., and Hartnett, N. (2022). ALP4AI: Agent-based learning platform for introductory artificial intelligence. In Proceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022), pages 1–9.
Li, H., Li, Z., Huang, W., and Guo, X. (2025). LLM-Cave: A benchmark and light environment for large language models reasoning and decision-making system. arXiv preprint arXiv:2511.22598.
Russell, S. and Norvig, P. (2021). Artificial Intelligence: A Modern Approach. Pearson, 4 edition.
Salehi, S., Saffar, M. T., Taghiyareh, F., and Badie, K. (2012). A multi-context dynamic test bed for simulating real-world constraints in agents’ teamwork. In Proceedings of the 6th International Symposium on Telecommunications (IST 2012), pages 1–6. IEEE.
Yob, G. (1975). Hunt the wumpus. Creative Computing, 1(5):51–54.
Publicado
19/10/2026
Como Citar
PEREIRA, José R. M.; DUARTE, Williams D. E.; BARROSO, Pedro P. V.; TEIXEIRA, Otávio N..
Wumpus Verse: A Web Platform Prototype for Development and Evaluation of Agents in the Wumpus World. 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. 146-157.
ISSN 2326-5434.
DOI: https://doi.org/10.5753/wesaac.2026.31605.
