Computer Science ›› 2015, Vol. 42 ›› Issue (Z11): 467-472.

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Improvement of General ABMS Model Representation Based on FLAME

YAN Yi-shi and LI Bo   

  • Online:2018-11-14 Published:2018-11-14

Abstract: Model representation is one of the most important issues during Agent-based modeling.Research on general ABMS model representation can reduce the threshold of using ABMS tools,which plays a significant role in the interdisciplinary research.As the leader of existing ABMS platforms,FLAME is not only with a high completeness,but also outstanding advantages in representation,code generation,visualization,etc.In this context,FLAME and XML were selected as the basis of general model representation.With inheriting their advantages of conciseness,completeness and parallelization,a deep research was achieved to find out the potential weakness and improvement possibilities,with targeted solutions as well.Finally,an Agent model example was tested and verified for the feasibility of solutions.

Key words: Model representation,ABMS,FLAME,XML

[1] Wikipedia.Agent-based model[EB/OL].
[2] FLAME.XMML Schema[DB/OL].
[3] FLAME.User Manual[EB/OL].
[4] FLAME.Projects[EB/OL].
[5] Coakley S,Gheorghe M,Holcombe M,et al.Exploitation ofHigh Performance Computing in the FLAME Agent-Based Simulation Framework[C]∥IEEE Computer Society.2012,2012:538-545
[6] Chin L S,Worth D J,Greenough C,et al.FLAME:an approach to the parallelisation of agent-based applications.RAL-TR-2012-013.[R].Science and Technology Facilities Council,2012
[7] Chin L S,Worth D J,Greenough C,et al.FLAME-II:a redesign of the Flexible Large-scale Agent-based Modelling Environment.RAL-TR-2012-019.[R].Science and Technology Facilities Council,2012
[8] Park S,Zeigler B P.Distributing Simulation Work Based onComponent Activity:A New Approach to Partitioning Hierarchical DEVS Models [C]∥IEEE Computer Society CLADE.2003:124-131
[9] 伍选,文中华,汪泉,等.多agent规划领域中的观察信息约简[J].计算机科学,2014,1(6):176-179,2

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