Joshua Epstein

Joshua Epstein
Professor of Epidemiology
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Professional overview
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Joshua Epstein is Professor of Epidemiology in the NYU School of Global Public Health, and founding Director of the NYU Agent-Based Modeling Laboratory, with affiliated appointments at The Courant Institute of Mathematical Sciences, and the College of Arts & Sciences. Prior to joining NYU, he was Professor of Emergency Medicine at Johns Hopkins, and Director of the Center for Advanced Modeling in the Social, Behavior, and Health Sciences, with Joint appointments in Economics, Applied Mathematics, International Health, and Biostatistics. Before that, he was Senior Fellow in Economic Studies at the Brookings Institution and Director of the Center on Social and Economic Dynamics. His research interest has been modeling complex social dynamics using mathematical and computational methods, notably the method of Agent-Based Modeling in which he is a recognized pioneer. For this transformative innovation, he was awarded the NIH Director’s Pioneer Award in 2008, an Honorary Doctorate of Science from Amherst College in 2010, and was elected to the Society of Sigma XI in 2018. He has applied this method to the study of infectious diseases (e.g., Ebola, pandemic influenza, and smallpox), vector-borne diseases (e.g., zika), urban disaster preparedness, contagious violence, the evolution of norms, economic dynamics, computational archaeology, and the emergence of social classes, among many other topics. His books include Nonlinear Dynamics, Mathematical Biology, and Social Science (Wiley 1997), Generative Social Science: Studies in Agent-Based Computational Modeling (Princeton, 2006), Agent_Zero: Toward Neurocognitive Foundations for Generative Social Science (Princeton, 2013), and with Robert Axtell, Growing Artificial Societies: Social Science from the Bottom Up (MIT, 1996). Dr. Epstein earned his BA from Amherst College and his Ph.D. from The Massachusetts Institute of Technology.
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Education
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BA, Independent Scholar with Thesis in Political Economy, Amherst College, Amherst, MAPhD, Political Science (Specialization: Security Studies, Communist Studies, and Economics), Massachusetts Institute of Technology, Cambridge, MA
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Honors and awards
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Honorary Doctorate of Science, Amherst College (2010)Director’s Pioneer Award, National Institutes of Health (2008)Rockefeller Foundation International Relations Fellowship (1984)Council on Foreign Relations International Affairs Fellowship (1983)Ford Foundation Dual Expertise Fellowship in Soviet/East European Area Studies and International Security/Arms Control (1981)Institute for the Study of World Politics Fellowship (1981)
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Areas of research and study
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Agent-Based ModelingApplied EconomicsCost AnalysisDisaster HealthEpidemiologyHealth EconomicsInfectious DiseasesMathematical and Computational ModelingModeling Social and Behavioral DynamicsNew York Department of Health and Mental HygienePublic Health SystemsUrban HealthUrban InformaticsUrban Science
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Presentations
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Publications
Publications
Modelli computazionali fondati su agenti e scienza sociale generativa
Epstein, J. M. (n.d.).Publication year
2000Journal title
Sistemi IntelligentiVolume
12Issue
2Page(s)
177-221Understanding Anasazi Culture Change Through Agent-Based Modeling
Epstein, J., Dean, J., Gumerman, G., & Axtell, R. (n.d.). In G. J. Gumerman & T. Kohler (Eds.), Dynamics in Human and Primate Societies: Agent-Based Modeling of Social and Spatial Processes (1–).Publication year
2000Page(s)
179-206Agent-Based Computational Models and Generative Social Science
Epstein, J. (n.d.).Publication year
1999Journal title
ComplexityVolume
4Issue
5Page(s)
41-60Agent-based computational models and generative social science
Epstein, J. M. (n.d.).Publication year
1999Journal title
ComplexityVolume
4Issue
5Page(s)
41-60AbstractThis article argues that the agent-based computational model permits a distinctive approach to social science for which the term “generative” is suitable. In defending this terminology, features distinguishing the approach from both “inductive” and “deductive” science are given. Then, the following specific contributions to social science are discussed: The agent-based computational model is a new tool for empirical research. It offers a natural environment for the study of connectionist phenomena in social science. Agent-based modeling provides a powerful way to address certain enduring—and especially interdisciplinary—questions. It allows one to subject certain core theories—such as neoclassical microeconomics—to important types of stress (e.g., the effect of evolving preferences). It permits one to study how rules of individual behavior give rise—or “map up”—to macroscopic regularities and organizations. In turn, one can employ laboratory behavioral research findings to select among competing agent-based (“bottom up”) models. The agent-based approach may well have the important effect of decoupling individual rationality from macroscopic equilibrium and of separating decision science from social science more generally. Agent-based modeling offers powerful new forms of hybrid theoretical-computational work; these are particularly relevant to the study of non-equilibrium systems. The agent-based approach invites the interpretation of society as a distributed computational device, and in turn the interpretation of social dynamics as a type of computation. This interpretation raises important foundational issues in social science—some related to intractability, and some to undecidability proper. Finally, since “emergence” figures prominently in this literature, I take up the connection between agent-based modeling and classical emergentism, criticizing the latter and arguing that the two are incompatible.Coordination in Transient Social Networks: An Agent-Based Computational Model of the Timing of Retirement
Epstein, J., & Axtell, R. (n.d.). In H. Aaron (Ed.), Behavioral Dimensions of Retirement Economics (1–).Publication year
1999Page(s)
161-186Zones of cooperation in demographic prisoner’s dilemma
Epstein, J. M. (n.d.).Publication year
1998Journal title
ComplexityVolume
4Issue
2Page(s)
36-48AbstractThe emergence of cooperation in prisoner’s dilemma (PD) games is generally assumed to require repeated play (and strategies such as Tit for Tat, involving memory of previous interactions) or features (“tags”) permitting cooperators and defectors to distinguish one another. In the demographic PD, neither assumption is made: Agents with finite vision move to random sites on a lattice and play a fixed culturally-inherited zero-memory strategy of cooperate (C) or defect (D) against neighbors. Agents are indistinguishable to one another—they are “tagless.” Positive payoffs accrue to agents playing C against C, or D against C. Negative payoffs accrue to agents playing C against D, or D against D. Payoffs accumulate. If accumulated payoffs exceed some threshold, agents clone offspring of the same strategy onto neighboring sites and continue play. If accumulated payoffs are negative, agents die and are removed. Spatial zones of cooperation emerge.Aligning Simulation Models: A Case Study and Results
Axtell, R., Axelrod, R., Cohen, M., & Epstein, J. (n.d.).Publication year
1996Journal title
Computational and Mathematical Organization TheoryVolume
1Issue
2Page(s)
123-141Growing Artificial Societies: Social Science from the Bottom Up
Epstein, J., & Axtell, R. L. (n.d.). (1–).Publication year
1996Agent-Based Modeling: Understanding Our Creations
Axtell, R., & Epstein, J. (n.d.).Publication year
1994Journal title
The Bulletin of the Santa Fe InstituteVolume
9Issue
4Page(s)
28-32On the Mathematical Biology of Arms Races, Wars, and Revolutions
Epstein, J. (n.d.). In L. Nadel & D. L. Stein (Eds.), 1992 Lectures in Complex Systems (1–).Publication year
1994The Adaptive Dynamic Model of War
Epstein, J. (n.d.). In L. Nadel & D. L. Stein (Eds.), 1992 Lectures in Complex Systems (1–).Publication year
1994War With Iraq: What Price Victory?
Epstein, J. (n.d.).Publication year
1991Journal title
Brookings Discussion PapersControlling the Greenhouse Effect: Five Global Regimes Compared
Epstein, J., & Gupta, R. (n.d.). (1–).Publication year
1990Conventional Force Reductions: A Dynamic Assessment
Epstein, J. (n.d.). (1–).Publication year
1990The 3:1 Rule, the Adaptive Dynamic Model, and the Future of Security Studies
Epstein, J. (n.d.).Publication year
1989Journal title
International SecurityVolume
13Issue
4Page(s)
90-127Dynamic Analysis and the Conventional Balance in Europe
Epstein, J. (n.d.).Publication year
1988Journal title
International SecurityVolume
12Issue
4Page(s)
154-65Strategy and Force Planning: The Case of the Persian Gulf
Epstein, J. (n.d.). (1–).Publication year
1987Assessing the Military Balance: Defense Analysis and the Defense Debate
Epstein, J. (n.d.).Publication year
1985Journal title
The Brookings ReviewVolume
3Issue
3Page(s)
16-20The 1987 Defense Budget
Epstein, J. (n.d.). (1–).Publication year
1985The 1988 Defense Budget
Epstein, J. (n.d.). (1–).Publication year
1985The Calculus of Conventional War: Dynamic Analysis Without Lanchester Theory
Epstein, J. (n.d.). (1–).Publication year
1985Measuring Military Power
Epstein, J. (n.d.). (1–).Publication year
1984Horizontal Escalation: Sour Notes of a Recurrent Theme
Epstein, J. (n.d.). In R. Art & K. Waltz (Eds.), The Use of Force (1–).Publication year
1983Page(s)
541-552On Conventional Deterrence in Europe: Questions of Soviet Confidence
Epstein, J. (n.d.).Publication year
1982Journal title
OrbisVolume
26Issue
1Page(s)
71-86Soviet Vulnerabilities in Iran and the RDF Deterrent
Epstein, J. (n.d.).Publication year
1981Journal title
International SecurityVolume
6Issue
2Page(s)
126-59