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A multi-agent architecture for geosimulation of moving agents

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  • Mohammad Vahidnia
  • Ali Alesheikh
  • Seyed Alavipanah

Abstract

In this paper, a novel architecture is proposed in which an axiomatic derivation system in the form of first-order logic facilitates declarative explanation and spatial reasoning. Simulation of environmental perception and interaction between autonomous agents is designed with a geographic belief–desire–intention and a request–inform–query model. The architecture has a complementary quantitative component that supports collaborative planning based on the concept of equilibrium and game theory. This new architecture presents a departure from current best practices geographic agent-based modelling. Implementation tasks are discussed in some detail, as well as scenarios for fleet management and disaster management. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Mohammad Vahidnia & Ali Alesheikh & Seyed Alavipanah, 2015. "A multi-agent architecture for geosimulation of moving agents," Journal of Geographical Systems, Springer, vol. 17(4), pages 353-390, October.
    • Handle: RePEc:kap:jgeosy:v:17:y:2015:i:4:p:353-390
    DOI: 10.1007/s10109-015-0218-2
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    References listed on IDEAS

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    1. Daniel G. Brown & Rick Riolo & Derek T. Robinson & Michael North & William Rand, 2005. "Spatial process and data models: Toward integration of agent-based models and GIS," Journal of Geographical Systems, Springer, vol. 7(1), pages 25-47, October.
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    5. Muaz Niazi & Amir Hussain, 2011. "Agent-based computing from multi-agent systems to agent-based models: a visual survey," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(2), pages 479-499, November.
    6. Joshua M. Epstein & Robert L. Axtell, 1996. "Growing Artificial Societies: Social Science from the Bottom Up," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262550253, April.
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    1. Daniel Seaberg & Laura Devine & Jun Zhuang, 2017. "A review of game theory applications in natural disaster management research," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 89(3), pages 1461-1483, December.
    2. Amanda Melendez & David Caballero-Russi & Mariantonieta Gutierrez Soto & Luis Felipe Giraldo, 2022. "Computational models of community resilience," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1121-1152, March.

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