Agent-based modeling for a complex world. Part 1

被引:3
作者
Makarov, V. L. [1 ,2 ,3 ,4 ]
Bakhtizin, A. R. [2 ,5 ]
Epstein, J. M. [6 ,7 ,8 ,9 ]
机构
[1] Russian Acad Sci, Moscow, Russia
[2] Russian Acad Sci, Cent Econ & Math Inst, Moscow, Russia
[3] Moscow MV Lomonosov State Univ, Russian Sch Econ, New Econ Sch, Moscow, Russia
[4] Moscow MV Lomonosov State Univ, Higher Sch Publ Adm, Moscow, Russia
[5] Moscow MV Lomonosov State Univ, Moscow, Russia
[6] NYU, Agent Based Modeling Lab, New York, NY USA
[7] Courant Inst Math Sci, New York, NY USA
[8] Courant Inst Math Sci, New York, NY USA
[9] Dept Polit, New York, NY USA
来源
EKONOMIKA I MATEMATICESKIE METODY-ECONOMICS AND MATHEMATICAL METHODS | 2022年 / 58卷 / 01期
关键词
agent; based models; epidemiology; pedestrian traffic; demographic processes; transport systems; ecological forecasting; land use; urban dynamics; historical episodes; conflict simulation; social networks; economic systems; SIMULATION; ENVIRONMENT; FRAMEWORK;
D O I
10.31857/S042473880018970-6
中图分类号
F [经济];
学科分类号
02 ;
摘要
The main goal of this paper is to summarize selected developments in the field of artificial societies and agent-based modeling and to suggest, how this fundamentally new toolkit can contribute to solving some of the most complex scientific and practical problems of our time. The entire field of agent-based modeling has expanded dramatically over the last quarter century, with applications across a remarkable array of fields, at scales ranging from molecular to global. The models described in this paper are a small part of worldwide scientific and practical developments in the field of agent-based modelling and related areas. We have attempted to give an impression of the vast range of application areas (epidemiology, economics, demography, environment, urban dynamics, history, conflict, disaster preparedness), scales (from cellular to local to urban to planetary), and goals (simple exploratory models, optimization, generative explanation, forecasting, policy) of agent-based modeling. Agent-based models offer a new and powerful alternative, or complement, to traditional mathematical methods for addressing complex challenges.
引用
收藏
页码:5 / 26
页数:22
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