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This study introduces a new agent-based library for active shooting incident (ASI) research in AnyLogic®. This reusable tool significantly reduces model development time for researchers.

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Area of Science:

  • Computational Social Science
  • Simulation Modeling
  • Public Safety Research

Background:

  • Software libraries enhance code reusability and application development efficiency.
  • Existing tools for active shooting incident (ASI) research lack model and code reusability, hindering research advancement.
  • Repetitive tasks limit researchers' ability to improve model fidelity and address the core problem.

Purpose of the Study:

  • To propose and develop a novel agent-based library for active shooting incident (ASI) research within the AnyLogic® simulation environment.
  • To enhance the efficiency and reusability of ASI models through a well-defined application programming interface (API).
  • To abstract complex implementation details, facilitating quicker model development for researchers.

Main Methods:

  • Development of a new agent-based library tailored for AnyLogic®.
  • Creation of a well-defined API to streamline model construction.
  • Abstraction of implementation details to simplify user experience.
  • Replication of components from an existing AnyLogic® ASI model to evaluate the library's utility.

Main Results:

  • The new library allows for rapid creation of ASI models.
  • Significant time savings were observed in building new models using the library.
  • The library's initial version demonstrated its potential for improving research efficiency.

Conclusions:

  • The proposed agent-based ASI library offers a substantial improvement in model development time.
  • Increased code and model reusability can accelerate progress in active shooting incident research.
  • This library facilitates faster iteration and potentially higher fidelity models in ASI research.