Agent-Based And Population-Based Simulation: A Comparative Case Study For Epidemics

This paper reports a comparative evaluation of population-based simulation in comparison to agentbased simulation for different numbers of agents. Population-based simulation, such as for example in the classical approaches to predator-prey modelling and modelling of epidemics, has computational advantages over agent-based modelling with large numbers of agents. Therefore the latter approaches can be considered useful only when the results are expected to deviate from the results of population-based simulation, and are considered more realistic. However, there is sometimes also a silent assumption that for larger numbers of agents, agent-based simulations approximate population-based simulations, which would indicate that agent-based simulation just can be replaced by population-based simulation. The paper evaluates this assumption by a detailed comparative case study in epidemics.

[1]  Luis Antunes,et al.  Multi-Agent-Based Simulation VII, International Workshop, MABS 2006, Hakodate, Japan, May 8, 2006, Revised and Invited Papers , 2007, MABS.

[2]  Andrzej Bargiela,et al.  Granular prototyping in fuzzy clustering , 2004, IEEE Transactions on Fuzzy Systems.

[3]  Jaime Simão Sichman,et al.  Multi-Agent-Based Simulation VI , 2005, Lecture Notes in Computer Science.

[4]  Andrzej Bargiela,et al.  A model of granular data: a design problem with the Tchebyschev FCM , 2005, Soft Comput..

[5]  Patrick Brézillon,et al.  Lecture Notes in Artificial Intelligence , 1999 .

[6]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[7]  V. Volterra.  Fluctuations in the Abundance of a Species considered Mathematically , 1926, Nature.

[8]  R. May,et al.  Infectious Diseases of Humans: Dynamics and Control , 1991, Annals of Internal Medicine.

[9]  M. R. Irving,et al.  Observability Determination in Power System State Estimation Using a Network Flow Technique , 1986, IEEE Transactions on Power Systems.

[10]  Paul Davidsson,et al.  Multi-Agent and Multi-Agent-Based Simulation , 2008 .

[11]  S. Jørgensen.  Models in Ecology , 1975 .

[12]  Roberto Berchi,et al.  A comparison of simulation models applied to epidemics , 2002, J. Artif. Soc. Soc. Simul..

[13]  Shigui Ruan,et al.  Global analysis of an epidemic model with nonmonotone incidence rate , 2006, Mathematical Biosciences.

[14]  A. J. Lotka,et al.  Elements of Physical Biology. , 1925, Nature.

[15]  David N. Burghes,et al.  Modelling with differential equations , 1981 .

[16]  V. Volterra.  Variations and Fluctuations of the Number of Individuals in Animal Species living together , 1928 .

[17]  Russian Federation.,et al.  FULLY AGENT BASED MODELLINGS OF EPIDEMIC SPREAD USING ANYLOGIC , 2007 .

[18]  Jaime Simão Sichman,et al.  Multi-Agent-Based Simulation , 2002, Lecture Notes in Computer Science.

[19]  Andrzej Bargiela,et al.  Fuzzy fractal dimensions and fuzzy modeling , 2003, Inf. Sci..

[20]  S. Ellner,et al.  Dynamic Models in Biology , 2006 .

[21]  H. P. Hudson,et al.  An application of the theory of probabilities to the study of a priori pathometry.—Part I , 1917 .

[22]  Xianning Liu,et al.  Avian-human influenza epidemic model. , 2007, Mathematical biosciences.