Descoberta de tamanho de mapas ilimitados através da cooperação entre agentes BDI
Resumo
Agentes podem cooperar na exploração e mapeamento de ambientes desconhecidos. Os mapas produzidos podem ser ilimitados, de forma que, ao andar em uma mesma direção, o agente eventualmente retornará ao ponto de origem. O tamanho do ambiente, que é a distância de uma volta completa até retornar ao ponto de origem, é uma informação relevante na exploração de ambientes desconhecidos. Sem ela, um mesmo ponto pode ser mapeado múltiplas vezes como se todos os mapeamentos fossem pontos distintos. No entanto, alguns sistemas não fornecem essa informação e não fornecem sequer um referencial global de posicionamento. Este artigo descreve um algoritmo baseado na colaboração entre agentes para a descoberta do tamanho de mapas ilimitados. Os resultados são avaliados experimentalmente usando o cenário do Multi-Agent Programming Contest.Referências
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Bhandari, N. (2008). Planetary exploration: scientific importance and future prospects. Current Science, 94(2):185–200.
Bratman, M. (1987). Intention, plans, and practical reason. Harvard University Press, Cambridge, MA.
Cao, Z. L., Huang, Y., and Hall, E. L. (1988). Region filling operations with random obstacle avoidance for mobile robots. J. Field Robotics, 5(2):87–102.
Cardoso, R. C., Ferrando, A., and Papacchini, F. (2019). LFC: combining autonomous agents and automated planning in the multi-agent programming contest. In The Multi-Agent Programming Contest, pages 31–58.
Hand, K. P. and German, C. R. (2018). Exploring ocean worlds on earth and beyond. Nature Geoscience, 11(1):2–4.
Hert, S., Tiwari, S., and Lumelsky, V. J. (1996). A terrain-covering algorithm for an AUV. Auton. Robots, 3(2-3):91–119.
Jensen, A. B. and Villadsen, J. (2019). GOAL-DTU: development of distributed intelligence for the multi-agent programming contest. In The Multi-Agent Programming Contest, pages 79–105.
Labrou, Y. and Finin, T. W. (1994). A semantics approach for KQML - A general purpose communication language for software agents. In Proceedings of the Third International Conference on Information and Knowledge Management (CIKM’94), Gaithersburg, Maryland, USA, November 29 - December 2, 1994, pages 447–455. ACM.
Moorehead, S. J. (2001). Autonomous Surface Exploration for Mobile Robots. PhD thesis, USA. AAI3043383.
Nieuwenhuisen, M., Schulz, D., and Behnke, S. (2011). Exploration strategies for building compact maps in unbounded environments. In Jeschke, S., Liu, H., and Schilberg, D., editors, Intelligent Robotics and Applications - 4th International Conference, ICIRA 2011, Aachen, Germany, December 6-8, 2011, Proceedings, Part I, volume 7101 of Lecture Notes in Computer Science, pages 33–43. Springer.
PLC, S. F. (2018). How big is earth. [link]. Acesso: 30-04-2020.
Plotkin, G. D. (2004). A structural approach to operational semantics. J. Log. Algebraic Methods Program., 60-61:17–139.
Uhlir, V., Zboril, F., and Vidensky, F. (2019). Multi-agent programming contest 2019 FIT BUT team solution. In The Multi-Agent Programming Contest, pages 59–78.
Publicado
10/08/2021
Como Citar
FURIO, Vitor Luis Babireski; BRITO, Maiquel de; SCHMITZ, Tiago L.; AMARAL, Cleber J.; ZAGRE JUNIOR, Robson; ZATELLI, Maicon R.; FERRANDIN, Mauri; KAMPIK, Timotheus.
Descoberta de tamanho de mapas ilimitados através da cooperação entre agentes BDI. In: WORKSHOP-ESCOLA DE SISTEMAS DE AGENTES, SEUS AMBIENTES E APLICAÇÕES (WESAAC), 15. , 2021, Evento Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2021
.
p. 178-188.
ISSN 2326-5434.
