Accession Number : AD1025494


Title :   Computational Biomathematics: Toward Optimal Control of Complex Biological Systems


Descriptive Note : Technical Report,15 Sep 2009,14 Sep 2013


Corporate Author : Virginia Polytechnic Institute and State University Blacksburg United States


Personal Author(s) : Reinhard,Launbenbacher


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/1025494.pdf


Report Date : 26 Sep 2016


Pagination or Media Count : 9


Abstract : In order to get reliable results from agent-based models, simulations typically have to be run many times and results averaged, given that while the rules determining agent behavior in a model may be fixed, they often involve random processes (e.g., movement in a random direction). The first step towards model reduction involves figuring out how many simulations must be run (for fixed parameter settings) in order to obtain reliable results; this value may be model dependent. We are interested in automatic conversion of agent-based models to systems of equations. We are currently working on parameter estimation methods that show some promise. In this approach, we generate data from the simulation and attempt to determine parameters that fit the equations to the data. This work has been successful with the Rabbits and Grass model and is currently underway for a more spatially complicated version of SugarScape.


Descriptors :   mathematical analysis , agentbased simulations , multiagent systems , automation , data reduction , difference equations , evolutionary algorithms , computational biology , computational modeling


Subject Categories : Operations Research
      Cybernetics


Distribution Statement : APPROVED FOR PUBLIC RELEASE