RAMIREZ, Wulfrano Arturo Luna (2017). Agent-based modelling: a tool for supporting disaster-rescue tasks. In: Computational Intelligence for Societal Development in Developing Countries (CISDIDC), Sheffield Hallam University, 17 February 2017. (Unpublished) [Conference or Workshop Item]
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Ramirez CISDIDC 2017.pdf - Accepted Version
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Ramirez CISDIDC 2017.pdf - Accepted Version
Available under License All rights reserved.
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Abstract
  Agent-Based Modeling (ABM) is a technique oriented to representing, modelling and explaining complex systems. Through ABM, the elements of the system can be directly represented including their relationships and timing. These features make this technique ideal for representing social systems. On the other hand, cognitive agents comprise a computational tool capable of modelling aspects of human behaviour from individual to crowds. Consequently, integrating cognitive agents in an ABM is a promising field to provide for realistic simulations such as those required to simulate disaster-rescue circumstances. Disaster-rescue (DR) simulations have been deployed in the academic, government and private sectors supporting contingency anticipation, planning and policy making. DR is particularly relevant in developing countries as an instrument to support contingency response and management tasks since it does not require very specialized infrastructure or large budgets for its development and it can be adapted to a particular case including as much detail as required.
        
      
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