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DOI | 10.1007/s11538-016-0225-6 |
Optimization and Control of Agent-Based Models in Biology: A Perspective | |
An, G.1; Fitzpatrick, B. G.2,3; Christley, S.4; Federico, P.5; Kanarek, A.6; Neilan, R. Miller7; Oremland, M.8; Salinas, R.9; Laubenbacher, R.10,11; Lenhart, S.12,13 | |
发表日期 | 2017 |
ISSN | 0092-8240 |
卷号 | 79期号:1页码:63-87 |
英文摘要 | Agent-based models (ABMs) have become an increasingly important mode of inquiry for the life sciences. They are particularly valuable for systems that are not understood well enough to build an equation-based model. These advantages, however, are counterbalanced by the difficulty of analyzing and using ABMs, due to the lack of the type of mathematical tools available for more traditional models, which leaves simulation as the primary approach. As models become large, simulation becomes challenging. This paper proposes a novel approach to two mathematical aspects of ABMs, optimization and control, and it presents a few first steps outlining how one might carry out this approach. Rather than viewing the ABM as a model, it is to be viewed as a surrogate for the actual system. For a given optimization or control problem (which may change over time), the surrogate system is modeled instead, using data from the ABM and a modeling framework for which ready-made mathematical tools exist, such as differential equations, or for which control strategies can explored more easily. Once the optimization problem is solved for the model of the surrogate, it is then lifted to the surrogate and tested. The final step is to lift the optimization solution from the surrogate system to the actual system. This program is illustrated with published work, using two relatively simple ABMs as a demonstration, Sugarscape and a consumer-resource ABM. Specific techniques discussed include dimension reduction and approximation of an ABM by difference equations as well systems of PDEs, related to certain specific control objectives. This demonstration illustrates the very challenging mathematical problems that need to be solved before this approach can be realistically applied to complex and large ABMs, current and future. The paper outlines a research program to address them. |
英文关键词 | Agent-based modeling;Systems theory;Optimization;Optimal control |
语种 | 英语 |
WOS记录号 | WOS:000392195500004 |
来源期刊 | BULLETIN OF MATHEMATICAL BIOLOGY
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来源机构 | 美国环保署 |
文献类型 | 期刊论文 |
条目标识符 | http://gcip.llas.ac.cn/handle/2XKMVOVA/61867 |
作者单位 | 1.Univ Chicago, Dept Surg, 5841 S Maryland Ave, Chicago, IL 60637 USA; 2.Loyola Marymount Univ, Dept Math, Los Angeles, CA 90045 USA; 3.Tempest Technol, Los Angeles, CA 90045 USA; 4.Univ Texas Southwestern Med Ctr Dallas, Dept Clin Sci, Dallas, TX 75390 USA; 5.Capital Univ, Dept Math Comp Sci & Phys, Columbus, OH USA; 6.US EPA, Washington, DC 20460 USA; 7.Duquesne Univ, Dept Math & Comp Sci, Pittsburgh, PA 15219 USA; 8.Ohio State Univ, Math Biosci Inst, Columbus, OH 43210 USA; 9.Appalachian State Univ, Dept Math Sci, Boone, NC 28608 USA; 10.UConn Hlth, Ctr Quantitat Med, Farmington, CT USA; 11.Jackson Lab Genom Med, Farmington, CT USA; 12.Univ Tennessee, Dept Math, Knoxville, TN 37996 USA; 13.Univ Tennessee, NIMBioS, Knoxville, TN 37996 USA |
推荐引用方式 GB/T 7714 | An, G.,Fitzpatrick, B. G.,Christley, S.,et al. Optimization and Control of Agent-Based Models in Biology: A Perspective[J]. 美国环保署,2017,79(1):63-87. |
APA | An, G..,Fitzpatrick, B. G..,Christley, S..,Federico, P..,Kanarek, A..,...&Lenhart, S..(2017).Optimization and Control of Agent-Based Models in Biology: A Perspective.BULLETIN OF MATHEMATICAL BIOLOGY,79(1),63-87. |
MLA | An, G.,et al."Optimization and Control of Agent-Based Models in Biology: A Perspective".BULLETIN OF MATHEMATICAL BIOLOGY 79.1(2017):63-87. |
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