Editing Agent-based model (section)

==Applications==

===In biology===
{{main|Agent-based model in biology}}

Agent-based modeling has been used extensively in biology, including the analysis of the spread of [[epidemics]],<ref>{{cite arXiv |eprint=nlin/0403035 |last1=Situngkir |first1=Hokky |title=Epidemiology Through Cellular Automata: Case of Study Avian Influenza in Indonesia |year=2004}}</ref> and the threat of [[biowarfare]], [[Agent-based model in biology|biological applications]] including [[population dynamics]],<ref>{{cite journal |last=Caplat |first=Paul |author2=Anand, Madhur |author3=Bauch, Chris |title=Symmetric competition causes population oscillations in an individual-based model of forest dynamics |journal=Ecological Modelling |date=March 10, 2008 |volume=211 |issue=3–4 |pages=491–500 |doi=10.1016/j.ecolmodel.2007.10.002|bibcode=2008EcMod.211..491C }}</ref> stochastic gene expression,<ref>{{Cite journal|last=Thomas|first=Philipp|date=December 2019|title=Intrinsic and extrinsic noise of gene expression in lineage trees|journal=Scientific Reports|volume=9|issue=1|pages=474|doi=10.1038/s41598-018-35927-x|issn=2045-2322|pmc=6345792|pmid=30679440|bibcode=2019NatSR...9..474T}}</ref> plant-animal interactions,<ref>Fedriani JM, T Wiegand, D Ayllón, F Palomares, A Suárez-Esteban and V. Grimm.  2018. Assisting seed dispersers to restore old-fields: an individual-based model of the interactions among badgers, foxes, and Iberian pear trees. Journal of Applied Ecology 55: 600–611.</ref>  vegetation ecology,<ref name="Ch'ng, E. (2009)">Ch'ng, E. (2009) An Artificial Life-Based Vegetation Modelling Approach for Biodiversity Research, in Nature-Inspired informatics for Intelligent Applications and Knowledge Discovery: Implications in Business, Science and Engineering, R. Chiong, Editor. 2009, IGI Global: Hershey, PA. http://complexity.io/Publications/NII-alifeVeg-eCHNG.pdf {{Webarchive|url=https://web.archive.org/web/20131113173223/http://complexity.io/Publications/NII-alifeVeg-eCHNG.pdf |date=November 13, 2013 }}</ref> migratory ecology,<ref>{{cite report|first1=F.G.|last1=Weller|first2=E.B.|last2=Webb|first3=W.S.|last3=Beatty|first4=S.|last4=Fogenburg|first5=D.|last5=Kesler|first6=R.H.|last6=Blenk|first7=J.M.|last7=Eadie|first8=K.|last8=Ringelman |first9=M. L.|last9=Miller|year= 2022|title=Agent-based modeling of movements and habitat selection by mid-continent mallards|publisher=U.S. Department of Interior, Fish and Wildlife Service|series=Cooperator Science Series|id=FWS/CSS-143-2022|location=Washington, D. C|doi=10.3996/css47216360}}</ref> landscape diversity,<ref>{{Cite journal |last1=Wirth |first1=E. |last2=Szabó |first2=Gy. |last3=Czinkóczky |first3=A. |date=2016-06-07 |journal=ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences |volume=III-8 |pages=145–151 |doi=10.5194/isprs-annals-iii-8-145-2016 |bibcode=2016ISPAnIII8..145W|title=Measure of Landscape Heterogeneity by Agent-Based Methodology |doi-access=free }}</ref> [[sociobiology]],<ref name=Lima2009>{{cite journal
 |first1=Francisco W.S. |last1=Lima
 |first2=Tarik |last2=Hadzibeganovic |first3=Dietrich |last3=Stauffer.
 |year=2009
 |title=Evolution of ethnocentrism on undirected and directed Barabási-Albert networks
 |journal=Physica A
 |volume=388
 |pages=4999–5004
 |doi=10.1016/j.physa.2009.08.029
 |issue=24
|arxiv=0905.2672|bibcode=2009PhyA..388.4999L|s2cid=18233740
 }}</ref> the growth and decline of ancient civilizations, evolution of ethnocentric behavior,<ref>{{cite journal |last1=Lima |first1=Francisco W. S. |last2=Hadzibeganovic |first2=Tarik |last3=Stauffer |first3=Dietrich |year=2009 |title=Evolution of ethnocentrism on undirected and directed Barabási–Albert networks |journal=Physica A |volume=388 |issue=24 |pages=4999–5004 |doi=10.1016/j.physa.2009.08.029 |bibcode=2009PhyA..388.4999L |arxiv=0905.2672 |s2cid=18233740 }}</ref> forced displacement/migration,<ref>{{cite book |title=The Chaos of Forced Migration: A Modeling Means to an Humanitarian End |first=Scott |last=Edwards |date=June 9, 2009 |publisher=[[VDM Verlag]] |pages=168 |isbn=978-3-639-16516-6}}</ref> language choice dynamics,<ref>{{cite journal |last1=Hadzibeganovic |first1=Tarik |last2=Stauffer |first2=Dietrich |last3=Schulze |first3=Christian |year=2009 |title=Agent-based computer simulations of language choice dynamics |journal=Annals of the New York Academy of Sciences |volume=1167 |issue=1|pages=221–229 |doi=10.1111/j.1749-6632.2009.04507.x |pmid=19580569 |bibcode=2009NYASA1167..221H |s2cid=32790067 }}</ref> [[Cognitive model#Dynamical systems|cognitive modeling]], and biomedical applications including modeling 3D breast tissue formation/morphogenesis,<ref>{{cite journal |last1=Tang |first1=Jonathan|author2-link=Heiko Enderling |last2=Enderling |first2=Heiko |last3=Becker-Weimann |first3=Sabine |last4=Pham |first4=Christopher |last5=Polyzos |first5=Aris |last6=Chen |first6=Charlie |last7=Costes |first7=Sylvain |year=2011 |title=Phenotypic transition maps of 3D breast acini obtained by imaging-guided agent-based modeling |journal=Integrative Biology |volume=3 |issue=4 |pages=408–21 |doi=10.1039/c0ib00092b |pmid=21373705 |pmc=4009383 }}</ref> the effects of ionizing radiation on mammary stem cell subpopulation dynamics,<ref>{{cite journal |last1=Tang |first1=Jonathan |last2=Fernando-Garcia |first2=Ignacio |last3=Vijayakumar |first3=Sangeetha |last4=Martinez-Ruis |first4=Haydeliz |last5=Illa-Bochaca |first5=Irineu |last6=Nguyen |first6=David |last7=Mao |first7=Jian-Hua |last8=Costes |first8=Sylvain |last9=Barcellos-Hoff |first9=Mary Helen |year=2014 |title=Irradiation of juvenile, but not adult, mammary gland increases stem cell self-renewal and estrogen receptor negative tumors |journal=Stem Cells |volume=32 |issue=3 |pages=649–61 |doi=10.1002/stem.1533 |pmid=24038768   |s2cid=32979016 |doi-access=free }}</ref> inflammation,<ref>{{cite journal |last1=Tang |first1=Jonathan |last2=Ley |first2=Klaus |last3=Hunt |first3=C. Anthony |year=2007 |title=Dynamics of in silico leukocyte rolling, activation, and adhesion |journal=BMC Systems Biology |volume=1 |issue=14 |pages=14 |doi=10.1186/1752-0509-1-14 |pmid=17408504 |pmc=1839892 |doi-access=free }}</ref>
<ref>{{cite journal |last1=Tang |first1=Jonathan |last2=Hunt |first2=C. Anthony |year=2010 |title=Identifying the rules of engagement enabling leukocyte rolling, activation, and adhesion |journal=PLOS Computational Biology |volume=6 |issue=2 |pages=e1000681 |doi=10.1371/journal.pcbi.1000681 |pmid=20174606 |pmc=2824748 |bibcode=2010PLSCB...6E0681T |doi-access=free }}</ref> 
and the human [[immune system]],<ref>{{cite book |last1=Castiglione |first1=Filippo |first2=Franco |last2=Celada |url=http://www.crcpress.com/product/isbn/9781466597488 |title=Immune System Modeling and Simulation |publisher=CRC Press, Boca Raton |year=2015 |pages=274 |isbn=978-1-4665-9748-8 |access-date=December 17, 2017 |archive-date=February 4, 2023 |archive-url=https://web.archive.org/web/20230204160700/https://www.routledge.com/Immune-System-Modelling-and-Simulation/Castiglione-Celada/p/book/9781466597488 |url-status=live }}</ref> and the evolution of foraging behaviors.<ref>{{cite journal |last1=Liang |first1=Tong |last2=Brinkman |first2=Braden A. W. |title=Evolution of innate behavioral strategies through competitive population dynamics |journal=PLOS Computational Biology |date=14 March 2022 |volume=18 |issue=3 |pages=e1009934 |doi=10.1371/journal.pcbi.1009934 |doi-access=free |pmid=35286315 |bibcode=2022PLSCB..18E9934L |language=en |issn=1553-7358|pmc=8947601 }}</ref> Agent-based models have also been used for developing decision support systems such as for breast cancer.<ref>{{Cite book |doi=10.1109/ICICT.2009.5267202 |chapter-url=http://www.cs.stir.ac.uk/~man/papers/ICICT_Cameraready_June20_09.pdf |url-status=dead |archive-url=https://web.archive.org/web/20110614051810/http://www.cs.stir.ac.uk/~man/papers/ICICT_Cameraready_June20_09.pdf |archive-date=June 14, 2011 |df=mdy-all |chapter=A new hybrid agent-based modeling & simulation decision support system for breast cancer data analysis |title=2009 International Conference on Information and Communication Technologies |pages=134–139 |year=2009 |last1=Siddiqa |first1=Amnah |last2=Niazi |first2=Muaz |last3=Mustafa |first3=Farah |last4=Bokhari |first4=Habib |last5=Hussain |first5=Amir |last6=Akram |first6=Noreen |last7=Shaheen |first7=Shabnum |last8=Ahmed |first8=Fouzia |last9=Iqbal |first9=Sarah |isbn=978-1-4244-4608-7 |s2cid=14433449 }} (Breast Cancer DSS)</ref> Agent-based models are increasingly being used to model pharmacological systems in early stage and pre-clinical research to aid in drug development and gain insights into biological systems that would not be possible ''a priori''.<ref name=CPT>{{cite journal |last1=Butler |first1=James |last2=Cosgrove |first2=Jason |last3=Alden |first3=Kieran |last4=Read |first4=Mark |last5=Kumar |first5=Vipin |last6=Cucurull-Sanchez |first6=Lourdes |last7=Timmis |first7=Jon |last8=Coles |first8=Mark |title=Agent-Based Modeling in Systems Pharmacology |journal=CPT: Pharmacometrics & Systems Pharmacology |date=2015 |volume=4 |issue=11 |pages=615–629 |doi=10.1002/psp4.12018 |pmid = 26783498|pmc=4716580 }}</ref> Military applications have also been evaluated.<ref>{{cite book |title=Engineering Principles of Combat Modeling and Distributed Simulation |first1=Gnana |last1=Barathy |first2=Levent |last2=Yilmaz |first3=Andreas |last3=Tolk |location=Hoboken, NJ |publisher=[[John Wiley & Sons|Wiley]] |pages=669–714 |date=March 2012 |doi=10.1002/9781118180310.ch27 |chapter=Agent Directed Simulation for Combat Modeling and Distributed Simulation |isbn=9781118180310}}</ref> Moreover, agent-based models have been recently employed to study molecular-level biological systems.<ref>{{Cite journal |last1=Azimi |first1=Mohammad |last2=Jamali |first2=Yousef |last3=Mofrad |first3=Mohammad R. K. |title=Accounting for Diffusion in Agent Based Models of Reaction-Diffusion Systems with Application to Cytoskeletal Diffusion |journal=PLOS ONE |volume=6 |issue=9 |pages=e25306 |doi=10.1371/journal.pone.0025306 |pmc=3179499 |pmid=21966493 |year=2011 |bibcode=2011PLoSO...625306A|doi-access=free }}</ref><ref>{{Cite journal |last1=Azimi |first1=Mohammad |last2=Mofrad |first2=Mohammad R. K. |title=Higher Nucleoporin-Importinβ Affinity at the Nuclear Basket Increases Nucleocytoplasmic Import |journal=PLOS ONE |volume=8 |issue=11 |pages=e81741 |doi=10.1371/journal.pone.0081741 |pmc=3840022 |pmid=24282617 |year=2013 |bibcode=2013PLoSO...881741A|doi-access=free }}</ref><ref>{{Cite journal |last1=Azimi |first1=Mohammad |last2=Bulat |first2=Evgeny |last3=Weis |first3=Karsten |last4=Mofrad |first4=Mohammad R. K. |date=2014-11-05 |title=An agent-based model for mRNA export through the nuclear pore complex |journal=Molecular Biology of the Cell |volume=25 |issue=22 |pages=3643–3653 |doi=10.1091/mbc.E14-06-1065 |pmc=4230623 |pmid=25253717}}</ref> Agent-based models have also been written to describe ecological processes at work in ancient systems, such as those in dinosaur environments and more recent ancient systems as well.<ref>{{Cite journal |last1=Pahl |first1=Cameron C. |last2=Ruedas |first2=Luis |title=Carnosaurs as Apex Scavengers: Agent-based simulations reveal possible vulture analogues in late Jurassic Dinosaurs |journal=Ecological Modelling |volume=458 |doi=10.1016/j.ecolmodel.2021.109706|year=2021|page=109706 |bibcode=2021EcMod.45809706P }}</ref><ref>{{Cite journal |last1=Volmer |display-authors=etal |date=2017 |title=Did Panthera pardus (Linnaeus, 1758) become extinct in Sumatra because of competition for prey? Modeling interspecific competition within the Late Pleistocene carnivore guild of the Padang Highlands, Sumatra |journal=Palaeogeography, Palaeoclimatology, Palaeoecology |volume=487 |pages=175–186 |doi=10.1016/j.palaeo.2017.08.032|bibcode=2017PPP...487..175V }}</ref><ref>{{Cite journal |last1=Hagen |first1=Oskar |last2=Flück |first2=Benjamin |last3=Fopp|first3=Fabian |last4=Cabral |first4=Juliano C. |last5=Hartig |first5=Florian |last6=Pontarp |first6=Mikael |last7=Rangel |first7=Thiago F. |last8=Pellissier |first8=Loïc |title=gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth's biodiversity |journal=PLOS Biology |volume=19|doi=10.1371/journal.pbio.3001340|year=2021|issue=7 |page=e3001340 |pmid=34252071 |pmc=8384074 |s2cid=235807562 |doi-access=free }}</ref>

=== In epidemiology ===
Agent-based models now complement traditional [[Compartmental models in epidemiology|compartmental]] models, the usual type of epidemiological models. ABMs have been shown to be superior to compartmental models in regard to the accuracy of predictions.<ref>{{Cite journal|last1=Eisinger|first1=Dirk|last2=Thulke|first2=Hans-Hermann|date=2008-04-01|title=Spatial pattern formation facilitates eradication of infectious diseases|journal=The Journal of Applied Ecology|volume=45|issue=2|pages=415–423|doi=10.1111/j.1365-2664.2007.01439.x|issn=0021-8901|pmc=2326892|pmid=18784795|bibcode=2008JApEc..45..415E }}</ref><ref>{{Cite book|url=https://press.princeton.edu/books/hardcover/9780691190822/agent-based-and-individual-based-modeling|title=Agent-Based and Individual-Based Modeling|date=2019-03-26|isbn=978-0-691-19082-2|language=en|last1=Railsback|first1=Steven F.|last2=Grimm|first2=Volker|publisher=Princeton University Press |access-date=October 19, 2020|archive-date=October 24, 2020|archive-url=https://web.archive.org/web/20201024163738/https://press.princeton.edu/books/hardcover/9780691190822/agent-based-and-individual-based-modeling|url-status=live}}</ref> Recently, ABMs such as [[CovidSim]] by epidemiologist [[Neil Ferguson (epidemiologist)|Neil Ferguson]], have been used to inform public health (nonpharmaceutical) interventions against the spread of [[Severe acute respiratory syndrome coronavirus 2|SARS-CoV-2]].<ref>{{Cite journal|last=Adam|first=David|date=2020-04-02|title=Special report: The simulations driving the world's response to COVID-19|journal=Nature|language=en|volume=580|issue=7803|pages=316–318|doi=10.1038/d41586-020-01003-6|pmid=32242115|bibcode=2020Natur.580..316A|s2cid=214771531|doi-access=}}</ref> Epidemiological ABMs have been criticized for simplifying and unrealistic assumptions.<ref>{{Cite journal|last1=Sridhar|first1=Devi|last2=Majumder|first2=Maimuna S.|date=2020-04-21|title=Modelling the pandemic|url=https://www.bmj.com/content/369/bmj.m1567|journal=BMJ|language=en|volume=369|pages=m1567|doi=10.1136/bmj.m1567|issn=1756-1833|pmid=32317328|s2cid=216074714|doi-access=free|access-date=October 19, 2020|archive-date=May 16, 2021|archive-url=https://web.archive.org/web/20210516061544/https://www.bmj.com/content/369/bmj.m1567|url-status=live|url-access=subscription}}</ref><ref>{{Cite journal|last1=Squazzoni|first1=Flaminio|last2=Polhill|first2=J. Gareth|last3=Edmonds|first3=Bruce|last4=Ahrweiler|first4=Petra|last5=Antosz|first5=Patrycja|last6=Scholz|first6=Geeske|last7=Chappin|first7=Émile|last8=Borit|first8=Melania|last9=Verhagen|first9=Harko|last10=Giardini|first10=Francesca|last11=Gilbert|first11=Nigel|date=2020|title=Computational Models That Matter During a Global Pandemic Outbreak: A Call to Action|url=http://jasss.soc.surrey.ac.uk/23/2/10.html|journal=Journal of Artificial Societies and Social Simulation|volume=23|issue=2|pages=10|doi=10.18564/jasss.4298|s2cid=216426533|issn=1460-7425|doi-access=free|access-date=October 19, 2020|archive-date=February 24, 2021|archive-url=https://web.archive.org/web/20210224024334/http://jasss.soc.surrey.ac.uk/23/2/10.html|url-status=live|hdl=10037/19057|hdl-access=free}}</ref> Still, they can be useful in informing decisions regarding mitigation and suppression measures in cases when ABMs are accurately calibrated.<ref>{{Cite journal|last1=Maziarz|first1=Mariusz|last2=Zach|first2=Martin|date=2020|title=Agent-based modelling for SARS-CoV-2 epidemic prediction and intervention assessment: A methodological appraisal|url= |journal=Journal of Evaluation in Clinical Practice|language=en|volume=26|issue=5|pages=1352–1360|doi=10.1111/jep.13459|issn=1365-2753|pmc=7461315|pmid=32820573}}</ref> The ABMs for such simulations are mostly based on [[synthetic population]]s, since the data of the actual population is not always available.<ref>{{cite journal |last1=Manout |first1=O. |last2=Ciari |first2=F. |title=Assessing the Role of Daily Activities and Mobility in the Spread of COVID-19 in Montreal With an Agent-Based Approach |journal=Frontiers in Built Environment |date=2021 |volume=7 |doi=10.3389/fbuil.2021.654279 |url=https://pesquisa.bvsalud.org/global-literature-on-novel-coronavirus-2019-ncov/resource/pt/covidwho-1346397 |language=en|doi-access=free }}</ref>

{| class="wikitable"
|+ Examples of ABM use in epidemiology
|-
! Program !! Year !! Citation !! Description
|-
| Covasim || 2021 ||<ref>{{Citation |last1=Kerr |first1=Cliff |last2=Stuart |first2=Robyn |display-authors=1 |year=2021 |title=Covasim: an agent-based model of COVID-19 dynamics and interventions |work=medRxiv |volume=17 |issue=7 |pages=e1009149 |doi=10.1371/journal.pcbi.1009149 |doi-access=free |pmid=34310589 |pmc=8341708 |bibcode=2021PLSCB..17E9149K }}</ref> || SEIR model implemented in Python with an emphasis on features for studying the effects of interventions.
|-
| OpenABM-Covid19 || 2021 ||<ref>{{Citation |last1=Hinch |first1=Robert |last2=Probert |first2=William |display-authors=1 |year=2021 |title=OpenABM-Covid19—An agent-based model for non-pharmaceutical interventions against COVID-19 including contact tracing |journal=PLOS Computational Biology |volume=17 |issue=7 |pages=e1009146 |doi=10.1371/journal.pcbi.1009146 |pmid=34252083 |pmc=8328312 |bibcode=2021PLSCB..17E9146H |doi-access=free }}</ref> || Epidemic model of the spread of COVID-19, simulating every individual in a population with both R and Python interfaces but using C for heavy computation.
|-
| OpenCOVID || 2021 ||<ref>{{Citation |last1=Shattock |first1=Andrew |last2=Le Rutte |first2=Epke |last3=Duenner |first3=Robert |display-authors=2 |year=2021 |title=Impact of vaccination and non-pharmaceutical interventions on SARS-CoV-2 dynamics in Switzerland |journal=Epidemics |volume=38 |issue=7 |pages=100535 |doi=10.1016/j.epidem.2021.100535 |pmid=34923396 |pmc=8669952 |bibcode=2021PLSCB..17E9146H }}</ref><ref>{{cite web |url=https://github.com/SwissTPH/OpenCOVID |title=Git-repository with open access source-code for OpenCOVID. |author=<!--Not stated--> |date=2022-01-31 |website=GitHub |publisher=Swiss TPH |access-date=2022-02-15 |archive-date=February 15, 2022 |archive-url=https://web.archive.org/web/20220215120617/https://github.com/SwissTPH/OpenCOVID |url-status=live }}</ref> || An individual-based transmission model of SARS-CoV-2 infection and COVID-19 disease dynamics, developed at the [[Swiss Tropical and Public Health Institute]].
|}

===In business, technology and network theory===

Agent-based models have been used since the mid-1990s to solve a variety of business and technology problems. Examples of applications include [[marketing]],<ref name="Rand and Rust (2011) IJRM">{{cite journal |last1=Rand |first1=William |last2=Rust |first2=Roland T. |year=2011 |title=Agent-based modeling in marketing: Guidelines for rigor |journal=International Journal of Research in Marketing |volume=28 |issue=3 |pages=181–193 |doi=10.1016/j.ijresmar.2011.04.002}}</ref> [[organizational behaviour]] and [[cognition]],<ref name="Hughes et al (2012) JOOP">{{cite journal |last1=Hughes |first1=H. P. N. |last2=Clegg |first2=C. W. |last3=Robinson |first3=M. A. |last4=Crowder |first4=R. M. |year=2012 |title=Agent-based modelling and simulation: The potential contribution to organizational psychology |journal=Journal of Occupational and Organizational Psychology |volume=85 |issue=3 |pages=487–502 |doi=10.1111/j.2044-8325.2012.02053.x }}</ref> [[teamwork|team working]],<ref>{{cite journal |last1=Boroomand |first1=Amin |title=Hard work, risk-taking, and diversity in a model of collective problem solving. |journal=Journal of Artificial Societies and Social Simulation |date=2021 |volume=24 |issue=4 |doi=10.18564/jasss.4704 |url=https://www.jasss.org/24/4/10.html#:~:text=When%20problems%20are%20simpler%2C%20risk,to%20the%20increase%20in%20diversity|doi-access=free }}</ref><ref name="Crowder et al (2012) IEEE TSMCA">{{cite journal |last1=Crowder |first1=R. M. |last2=Robinson |first2=M. A. |last3=Hughes |first3=H. P. N. |last4=Sim |first4=Y. W. |year=2012 |title=The development of an agent-based modeling framework for simulating engineering team work |journal=IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans |volume=42 |issue=6 |pages=1425–1439 |doi=10.1109/TSMCA.2012.2199304 |s2cid=7985332 }}</ref> [[supply chain optimization]] and logistics, modeling of [[consumer behavior]], including [[word of mouth]], [[social network]] effects, [[distributed computing]], [[workforce management]], and [[Investment management|portfolio management]]. They have also been used to analyze [[traffic congestion]].<ref>{{cite web |url=http://www.tfhrc.gov/advanc/agent.htm |title=Application of Agent Technology to Traffic Simulation |publisher=[[United States Department of Transportation]] |date=May 15, 2007 |access-date=October 31, 2007 |archive-url=https://web.archive.org/web/20110101034847/http://www.tfhrc.gov/advanc/agent.htm |archive-date=January 1, 2011 |url-status=dead |df=mdy-all }}</ref>

Recently, agent based modelling and simulation has been applied to various domains such as studying the impact of publication venues by researchers in the computer science domain (journals versus conferences).<ref>{{cite book |last1=Niazi |first1=M. |last2=Baig |first2=A. R. |last3=Hussain |first3=A. |last4=Bhatti |first4=S. |title=2008 Winter Simulation Conference |chapter=Simulation of the research process |year=2008 |editor1-first=S. |editor1-last=Mason |editor2-first=R. |editor2-last=Hill |editor3-first=L. |editor3-last=Mönch |editor4-first=O. |editor4-last=Rose |editor5-first=T. |editor5-last=Jefferson |editor6-first=J. W. |editor6-last=Fowler |pages=1326–1334 |chapter-url=http://www.informs-sim.org/wsc08papers/159.pdf |doi=10.1109/WSC.2008.4736206 |isbn=978-1-4244-2707-9 |hdl=1893/3203 |s2cid=6597668 |access-date=June 7, 2009 |archive-date=June 1, 2011 |archive-url=https://web.archive.org/web/20110601150006/http://www.informs-sim.org/wsc08papers/159.pdf |url-status=live }}</ref> In addition, ABMs have been used to simulate information delivery in ambient assisted environments.<ref>{{cite book |last=Niazi |first=Muaz A. |title=Proceedings of the third international workshop on Use of P2P, grid and agents for the development of content networks |chapter=Self-organized customized content delivery architecture for ambient assisted environments |year=2008 |pages=45–54 |chapter-url=http://www.cs.stir.ac.uk/~man/papers/upg106-niazi.pdf |url-status=dead |archive-url=https://web.archive.org/web/20110614051629/http://www.cs.stir.ac.uk/~man/papers/upg106-niazi.pdf |archive-date=June 14, 2011 |df=mdy-all |doi=10.1145/1384209.1384218 |isbn=9781605581552 |s2cid=16916130 }}</ref> A November 2016 article in [[arXiv]] analyzed an agent based simulation of posts spread in [[Facebook]].<ref>{{Cite arXiv |last1=Nasrinpour |first1=Hamid Reza |last2=Friesen |first2=Marcia R. |last3=McLeod |first3=Robert D. |date=2016-11-22 |title=An Agent-Based Model of Message Propagation in the Facebook Electronic Social Network |eprint=1611.07454 |class=cs.SI}}</ref> In the domain of peer-to-peer, ad hoc and other self-organizing and complex networks, the usefulness of agent based modeling and simulation has been shown.<ref>{{cite journal |first1=Muaz |last1=Niazi |first2=Amir |last2=Hussain |title=Agent based Tools for Modeling and Simulation of Self-Organization in Peer-to-Peer, Ad-Hoc and other Complex Networks |journal=IEEE Communications Magazine |volume=47 |issue=3 |date=March 2009 |pages=163–173 |url=http://www.cs.stir.ac.uk/~man/papers/niaziCommmag.pdf |doi=10.1109/MCOM.2009.4804403 |url-status=dead |archive-url=https://web.archive.org/web/20101204212920/http://www.cs.stir.ac.uk/~man/papers/niaziCommmag.pdf |archive-date=December 4, 2010 |df=mdy-all |hdl=1893/2423 |s2cid=23449913 }}</ref> The use of a computer science-based formal specification framework coupled with [[wireless sensor networks]] and an agent-based simulation has recently been demonstrated.<ref>{{cite journal |first1=Muaz |last1=Niazi |first2=Amir |last2=Hussain |year=2011 |title=A Novel Agent-Based Simulation Framework for Sensing in Complex Adaptive Environments |journal=IEEE Sensors Journal |volume=11 |issue=2 |pages=404–412 |url=http://cs.stir.ac.uk/~man/papers/Accepted_IEEESensorsAug2010.pdf |doi=10.1109/JSEN.2010.2068044 |url-status=dead |archive-url=https://web.archive.org/web/20110725023733/http://cs.stir.ac.uk/~man/papers/Accepted_IEEESensorsAug2010.pdf |archive-date=July 25, 2011 |df=mdy-all |bibcode=2011ISenJ..11..404N |arxiv=1708.05875 |hdl=1893/3398 |s2cid=15367419 }}</ref>

Agent based evolutionary search or algorithm is a new research topic for solving complex optimization problems.<ref>{{Cite book |last1=Sarker |first1=R. A. |last2=Ray |first2=T. |chapter=Agent Based Evolutionary Approach: An Introduction |doi=10.1007/978-3-642-13425-8_1 |title=Agent-Based Evolutionary Search |series=Adaptation, Learning, and Optimization |volume=5 |pages=1–11 |year=2010 |isbn=978-3-642-13424-1 }}</ref>

===In team science===
In the realm of team science, agent-based modeling has been utilized to assess the effects of team members' characteristics and biases on team performance across various settings.<ref>{{cite journal |last1=Boroomand |first1=Amin |last2=Smaldino |first2=Paul E. |title=Superiority bias and communication noise can enhance collective problem solving. |journal=Journal of Artificial Societies and Social Simulation |date=2023 |volume=26 |issue=3 |doi=10.18564/jasss.5154|doi-access=free }}</ref> By simulating interactions between agents—each representing individual team members with distinct traits and biases—this modeling approach enables researchers to explore how these factors collectively influence the dynamics and outcomes of team performance. Consequently, agent-based modeling provides a nuanced understanding of team science, facilitating a deeper exploration of the subtleties and variabilities inherent in team-based collaborations.

===In economics and social sciences===
{{main|Agent-based computational economics|Agent-based social simulation}}
{{see also|Artificial financial market}}
Prior to, and in the wake of the [[Financial crisis of 2007–2008|2008 financial crisis]], interest has grown in ABMs as possible tools for economic analysis.<ref>{{cite book |first=Scott E. |last=Page |year=2008 |title=Agent-Based Models |work=[[The New Palgrave Dictionary of Economics]] |edition=2 |url=http://www.dictionaryofeconomics.com/article?id=pde2008_A000218&edition=current&q=agent-based%20computational%20modeling&topicid=&result_number=1 |access-date=October 3, 2011 |archive-date=February 10, 2018 |archive-url=https://web.archive.org/web/20180210023520/https://www.springernature.com/gp/ |url-status=live }}</ref><ref>{{cite book |editor1-first=Leigh |editor1-last=Testfatsion |editor1-link=Leigh Tesfatsion |editor2-first=Kenneth |editor2-last=Judd |editor2-link=Kenneth Judd |date=May 2006 |title=Handbook of Computational Economics |volume=2 |publisher=[[Elsevier]] |pages=904 |url=http://www.elsevier.com/wps/find/bookdescription.cws_home/660847/description#description |isbn=978-0-444-51253-6 |access-date=January 29, 2012 |archive-url=https://web.archive.org/web/20120306100156/http://www.elsevier.com/wps/find/bookdescription.cws_home/660847/description#description |archive-date=March 6, 2012 |url-status=dead |df=mdy-all }} ([https://www.sciencedirect.com/science/journal/15740021/2 Chapter preview)]</ref> ABMs do not assume the economy can [[Economic equilibrium|achieve equilibrium]] and "[[representative agent]]s" are replaced by agents with [[Heterogeneity in economics#Economic models with heterogeneous agents|diverse, dynamic, and interdependent behavior]] including [[herding]]. ABMs take a [[Microfoundations|"bottom-up" approach]] and can generate extremely complex and volatile simulated economies. ABMs can represent unstable systems with crashes and booms that develop out of non-[[linear]] (disproportionate) responses to proportionally small changes.<ref name="agents">{{cite news |url=http://www.economist.com/node/16636121 |title=Agents of change |date=July 22, 2010 |newspaper=The Economist |access-date=February 16, 2011 |archive-date=January 23, 2011 |archive-url=https://web.archive.org/web/20110123110948/http://www.economist.com/node/16636121 |url-status=live }}</ref> A July 2010 article in ''[[The Economist]]'' looked at ABMs as alternatives to [[Dynamic stochastic general equilibrium|DSGE]] models.<ref name="agents"/> The journal ''[[Nature (journal)|Nature]]'' also encouraged agent-based modeling with an editorial that suggested ABMs can do a better job of representing financial markets and other economic complexities than standard models<ref>{{cite journal |title=A model approach |journal=[[Nature (journal)|Nature]] |volume=460 |issue=7256 |page=667 |date=August 6, 2009 |doi=10.1038/460667a |pmid=19661863 |bibcode=2009Natur.460Q.667.|doi-access=free }}</ref> along with an essay by [[J. Doyne Farmer]] and Duncan Foley that argued ABMs could fulfill both the desires of Keynes to represent a complex economy and of Robert Lucas to construct models based on microfoundations.{{sfn|Farmer|Foley|2009|p=685}} Farmer and Foley pointed to progress that has been made using ABMs to model parts of an economy, but argued for the creation of a very large model that incorporates low level models.{{sfn|Farmer|Foley|2009|p=686}} By modeling a complex system of [[financial analyst|analysts]] based on three distinct behavioral profiles – imitating, anti-imitating, and indifferent – [[financial market]]s were simulated to high accuracy. Results showed a correlation between network morphology and the stock market index.<ref>Stefan, F., & Atman, A. (2015). Is there any connection between the network morphology and the fluctuations of the stock market index? Physica A: Statistical Mechanics and Its Applications, (419), 630-641.</ref> However, the ABM approach has been criticized for its lack of robustness between models, where similar models can yield very different results.<ref>{{cite journal |last1=Dawid |first1=Herbert |last2=Gatti |first2=Delli |date=January 2018 |title=Agent-based macroeconomics |journal=Handbook of Computational Economics |volume=4 |pages=63–156|doi=10.1016/bs.hescom.2018.02.006 }}</ref><ref>{{cite journal |last1=Rand |first1=William |last2=Rust |first2=Roland T. |date=July 2011 |title=Agent-based modeling in marketing: Guidelines for rigor |journal=International Journal of Research in Marketing |volume=28 |issue=3 |pages=181–193 |doi=10.1016/j.ijresmar.2011.04.002 }}</ref>

ABMs have been deployed in architecture and urban planning to evaluate design and to simulate pedestrian flow in the urban environment<ref>{{cite journal |first1=G.D.P.A |last2=Wullschleger |first2=Tobias |last3=Müller |first3=Hanspeter |last4=Schmitt |first4=Gerhard |last1=Aschwanden |year=2009 |title=Evaluation of 3D city models using automatic placed urban agents |journal=Automation in Construction |volume=22 |pages=81–89 |doi=10.1016/j.autcon.2011.07.001}}</ref> and the examination of public policy applications to land-use.<ref>{{cite journal |first1=Daniel G. |last1=Brown |last2=Page |first2=Scott E. |last3=Zellner |first3=Moira |last4=Rand |first4=William |year=2005 |title=Path dependence and the validation of agent-based spatial models of land use |journal=International Journal of Geographical Information Science |volume=19 |issue=2 |pages=153–174 |doi=10.1080/13658810410001713399|doi-access=free |bibcode=2005IJGIS..19..153B }}</ref> There is also a growing field of socio-economic analysis of infrastructure investment impact using ABM's ability to discern systemic impacts upon a socio-economic network.<ref>{{cite report |first1=Paul |last2=Stiff |first2=David |last1=Smetanin |year=2015 |title=Investing in Ontario's Public Infrastructure: A Prosperity at Risk Perspective, with an analysis of the Greater Toronto and Hamilton Area |publisher=The Canadian Centre for Economic Analysis |url=http://www.cancea.ca/sites/economic-analysis.ca/files/reports/CANCEA%20Report%20-%20Investing%20in%20Ontario%27s%20Infrastructure%20FINAL%20Oct%202015%20Web.pdf |access-date=November 17, 2016 |archive-date=November 18, 2016 |archive-url=https://web.archive.org/web/20161118042407/http://www.cancea.ca/sites/economic-analysis.ca/files/reports/CANCEA%20Report%20-%20Investing%20in%20Ontario%27s%20Infrastructure%20FINAL%20Oct%202015%20Web.pdf |url-status=live }}</ref> Heterogeneity and dynamics can be easily built in ABM models to address wealth inequality and social mobility.<ref>{{Cite journal |last1=Yang |first1=Xiaoliang |last2=Zhou |first2=Peng |date=April 2022 |title=Wealth inequality and social mobility: A simulation-based modelling approach |journal=Journal of Economic Behavior & Organization |language=en |volume=196 |pages=307–329 |doi=10.1016/j.jebo.2022.02.012 |s2cid=247143315 |doi-access=free |hdl=10419/261231 |hdl-access=free }}</ref>

ABMs have also been proposed as applied educational tools for diplomats in the field of [[international relations]]<ref>{{Cite journal |last1=Butcher |first1=Charity |last2=Njonguo |first2=Edwin |date=2021-12-22 |title=Simulating Diplomacy: Learning Aid or Business as Usual? |url=|journal=Journal of Political Science Education |language=en |volume=17 |issue=sup1 |pages=185–203 |doi=10.1080/15512169.2020.1803080 |issn=1551-2169}}</ref> and for domestic and international policymakers to enhance their evaluation of [[public policy]].<ref>{{Cite journal |last1=Gilbert |first1=Nigel |last2=Ahrweiler |first2=Petra |last3=Barbrook-Johnson |first3=Pete |last4=Narasimhan |first4=Kavin Preethi |last5=Wilkinson |first5=Helen |date=2018 |title=Computational Modelling of Public Policy: Reflections on Practice |url=http://jasss.soc.surrey.ac.uk/21/1/14.html |journal=Journal of Artificial Societies and Social Simulation |language=en |volume=21 |issue=1 |doi=10.18564/jasss.3669 |issn=1460-7425|hdl=10044/1/102075 |hdl-access=free }}</ref>

=== In water management ===
ABMs have also been applied in water resources planning and management, particularly for exploring, simulating, and predicting the performance of infrastructure design and policy decisions,<ref>{{Cite journal|last=Berglund|first=Emily Zechman|date=November 2015|title=Using Agent-Based Modeling for Water Resources Planning and Management|url=http://ascelibrary.org/doi/10.1061/%28ASCE%29WR.1943-5452.0000544|journal=Journal of Water Resources Planning and Management|language=en|volume=141|issue=11|pages=04015025|doi=10.1061/(ASCE)WR.1943-5452.0000544|issn=0733-9496|access-date=September 18, 2021|archive-date=January 19, 2022|archive-url=https://web.archive.org/web/20220119081321/http://ascelibrary.org/doi/10.1061/(ASCE)WR.1943-5452.0000544|url-status=live|url-access=subscription}}</ref> and in assessing the value of cooperation and information exchange in large water resources systems.<ref>{{Cite journal|last1=Giuliani|first1=M.|last2=Castelletti|first2=A.|date=July 2013|title=Assessing the value of cooperation and information exchange in large water resources systems by agent-based optimization: MAS Framework for Large Water Resources Systems|journal=Water Resources Research|language=en|volume=49|issue=7|pages=3912–3926|doi=10.1002/wrcr.20287|s2cid=128659104 |doi-access=free}}</ref>

===Organizational ABM: agent-directed simulation===

The agent-directed simulation (ADS) metaphor distinguishes between two categories, namely "Systems for Agents" and "Agents for Systems."<ref>{{cite web |url=http://www.eng.auburn.edu/~yilmaz/ADS.html |title=Agent-Directed Simulation |access-date=August 9, 2011 |archive-date=September 27, 2011 |archive-url=https://web.archive.org/web/20110927165246/http://www.eng.auburn.edu/~yilmaz/ADS.html |url-status=live }}</ref> Systems for Agents (sometimes referred to as agents systems) are systems implementing agents for the use in engineering, human and [[social dynamics]], military applications, and others. Agents for Systems are divided in two subcategories. Agent-supported systems deal with the use of agents as a support facility to enable computer assistance in problem solving or enhancing cognitive capabilities. Agent-based systems focus on the use of agents for the generation of model behavior in a system evaluation (system studies and analyses).

===Self-driving cars===
Hallerbach et al. discussed the application of agent-based approaches for the development and validation of automated driving systems via a digital twin of the vehicle-under-test and microscopic traffic simulation based on independent agents.<ref>{{cite journal |last1=Hallerbach |first1=S. |last2=Xia |first2=Y. |last3=Eberle |first3=U. |last4=Koester |first4=F. |title=Simulation-Based Identification of Critical Scenarios for Cooperative and Automated Vehicles |journal=SAE International Journal of Connected and Automated Vehicles |date=2018 |volume=1 |issue=2 |pages=93–106 |publisher=SAE International |doi=10.4271/2018-01-1066 |url=https://www.researchgate.net/publication/324194968}}</ref> [[Waymo]] has created a multi-agent simulation environment Carcraft to test algorithms for [[self-driving car]]s.<ref>{{cite news |last1=Madrigal |first1=Story by Alexis C. |title=Inside Waymo's Secret World for Training Self-Driving Cars |url=https://www.theatlantic.com/technology/archive/2017/08/inside-waymos-secret-testing-and-simulation-facilities/537648/ |access-date=14 August 2020 |work=The Atlantic |archive-date=August 14, 2020 |archive-url=https://web.archive.org/web/20200814195438/https://www.theatlantic.com/technology/archive/2017/08/inside-waymos-secret-testing-and-simulation-facilities/537648/ |url-status=live }}</ref><ref>{{cite journal |last1=Connors |first1=J. |last2=Graham |first2=S. |last3=Mailloux |first3=L. |title=Cyber Synthetic Modeling for Vehicle-to-Vehicle Applications |journal=International Conference on Cyber Warfare and Security |date=2018 |page=594-XI |publisher=Academic Conferences International Limited}}</ref> It simulates traffic interactions between human drivers, pedestrians and automated vehicles. People's behavior is imitated by artificial agents based on data of real human behavior. The basic idea of using agent-based modeling to understand self-driving cars was discussed as early as 2003.<ref>{{Cite book|last1=Yang|first1=Guoqing|last2=Wu|first2=Zhaohui|last3=Li|first3=Xiumei|last4=Chen|first4=Wei|title=Proceedings of the 2003 IEEE International Conference on Intelligent Transportation Systems |chapter=SVE: Embedded agent based smart vehicle environment |date=2003|chapter-url=https://ieeexplore.ieee.org/document/1252782|volume=2|pages=1745–1749 vol.2|doi=10.1109/ITSC.2003.1252782|isbn=0-7803-8125-4|s2cid=110177067|access-date=August 19, 2021|archive-date=January 31, 2022|archive-url=https://web.archive.org/web/20220131211240/https://ieeexplore.ieee.org/document/1252782|url-status=live}}</ref>