Course and Program Information

Agent-Based Computational Economics (ACE)
and ACE-Related Topics


Last Updated: 19 March 2012

Site maintained by:
Leigh Tesfatsion
Department of Economics
Iowa State University
Ames, Iowa 50011-1070
http://www.econ.iastate.edu/tesfatsi/
tesfatsi at iastate.edu

Agent-Based Computational Economics (ACE) Website

Provided Materials:

ACE Course Outlines

ACE Course (Tesfatsion, Iowa State University):

Leigh Tesfatsion (Economics, Iowa State University, Ames, IA) has developed an undergraduate course (Econ 308) on Agent-Based Computational Economics. The primary objective of the course is to introduce, motivate, and explore through concrete applications the potential usefulness of ACE for the study of economic processes. Course topics include: introduction to ACE (simple market illustrations); design and conduct of experiments using ACE computational laboratories (hands-on experience); learning and the embodied mind; agent learning representation; the Santa Fe Artificial Stock Market Model; economic networks; economic processes with strong learning/network effects (labor market illustrations); and an ACE real-world application (reliability study of a market design proposed for restructured U.S. wholesale power markets). This course has specifically been designed as a self-study eBook to facilitate long-distance learners. Each topic area includes annotated pointers to key readings, individual researchers, research groups, research area resource sites; interactive computer demos, and software tools.

ACE Course (Argonne National Laboratory and the Santa Fe Institute):

Argonne National Laboratory and the Santa Fe Institute offer a regular annual course on agent-based modeling, typically in mid-May. The course is an intensive applications-oriented introduction to agent-based modeling based on Michael North and Charles Macal’s book Managing Business Complexity: Discovering Strategic Solutions with Agent-Based Modeling and Simulation (Oxford 2007). The first half of the course focuses on agent modeling concepts from the perspective of managers and analysts. The second half of the course focuses on agent modeling implementation from the perspective of software developers and includes extensive hands-on exercises with Repast Simphony ReLogo. Participants are invited to attend the first session, the second session, or both depending on their interests. The course is typically held at the Argonne National Laboratory, which is located in the suburbs of Chicago, Illinois, USA. More information on the course and registration forms can be found here.

ACE Course (LeBaron, Brandeis University):

Blake LeBaron (International Business School, Brandeis University, Waltham, MA) has prepared a graduate course (Econ 326f) titled Agent-Based Modelling. This course is a "hands-on" course with computer exercises and problem sets as the basic learning tool. The primary emphasis of the course is on financial applications of agent-based modeling, but other topics are considered depending on the background interests and demands of the students.

ACE Course (Branke and Veit, U of Karlsruhe):

Dr. Jürgen Branke and Dr. Daniel Veit offer a course on (agent-based) computational economics at the University of Karlsruhe, Germany. Computer-based simulation models are used to analyze complex economic systems; artificial worlds are created that capture relevant aspects of the problems under consideration. Given all exogenous and endogenous factors, the modeled economies evolve over time and different scenarios can be analyzed. Thus, the models serve as virtual testbeds for theory generation and exploration. The course covers a wide range of topics, including a number of simulation paradigms (with emphasis on agent-based simulation), artificial intelligence, and models with learning agents. For more information, visit here.

ACE Course (Fagiolo, Sant'Anna School of Advanced Studies):

Giorgio Fagiolo (Sant'Anna School of Advanced Studies, Pisa, Italy) has developed an undergraduate course on Agent-Based Computational Economics.

ACE Approach to Macro Coordination (Tesfatsion, Iowa State University):

Leigh Tesfatsion (Economics, Iowa State University, Ames, IA) has prepared a module titled Macroeconomic Modeling of Endogenous Coordination for a regularly taught masters-level macroeconomics theory course. The following topics are covered: (1) Coordination issues for macroeconomies;(2) Constructive modeling of endogenous coordination: Agent-based macroeconomics; and (3) Illustrative applications.

Agent-Based Computational Methods in the Social Sciences (Axtell, GMU):

Robert Axtell (George Mason University, Arlington, VA) offered an undergraduate course titled Computational Methods in the Social Sciences at Johns Hopkins University in Spring 2000. The course considered a range of agent-based models in economics, including market processes, evolution of norms (e.g., residential segregation), formation of economic classes, the emergence of multi-agent organizations (e.g., firms), and traffic. The issues examined across models included random number generation, path-dependence, self-organized criticality, controlling the production of artifacts, and verification and validation.

Agent-Based Policy Modeling (Pape, Binghamton University):

Andreas Duus Pape (Department of Economics, Binghamton University, UK) has developed a course consisting of three sections: (1) models and agent-based models; (2) an illustrative policy application (e.g., local property taxes); and (3) development and presentation of specific agent-based software projects. For more information, visit here.

Simulation Models for Economics (Terna, University of Torino):

Pietro Terna (Economics Faculty, University of Torino) teaches a course titled Simulation Models for Economics. The course stresses agent-based model development for simulation experiments or computer-assisted human-subject experiments. Students are introduced to Python (with R and Numpy), Maxima, Scliab, and Octave programming, as well as agent-based toolkits (e.g., NetLogo) and tools useful for agent-based modeling such as artificial neural networks.

Agent-Based and Complex Systems Modeling Tools for Business and Biosphere Issues (University of Sydney):

The University of Sydney is planning a regular summer school offering on complex systems and agent-based modeling tools for business and biosphere issues. Designed for advanced graduate students and faculty, the summer school will combine lectures with hands-on experience in lab sessions for building simulations. For further details, visit here.

ACE-Related Course Outlines

Agent-Based and Computer Intensive Modeling (Kollman, Page, and Riolo, University of Michigan):

As part of the ICPSR Summer Program in quantitative methods of Social Research, Ken Kollman, Scott Page, and Rick Riolo (all at the University of Michigan, Ann Arbor) prepared a series of lectures for a 2003 seminar titled "Nonlinear Systems: Agent-Based and Computer-Intensive Modeling." From the course description: "These lectures will give an introduction to recent approaches in computer modeling of complex social systems, comparing them to more traditional mathematical (analytical) approaches and to the previous generation of computer simulations in the social sciences. In addition to describing the methods and techniques of this modeling approach, a number of social science applications will be reviewed and analyzed. Students will also be able to run and carry out experiments with implementations of several of the models discussed in the lectures." For access to the lecture notes, visit here.

Agent-Based Electronic Commerce (Stone, University of Texas):

Peter Stone (Computer Science, University of Texas, Austin) has developed a course (CS395T) titled Agent-Based Electronic Commerce. This course focuses on topics at the intersection of computer science (including multiagent systems and machine learning), economics, and game theory. In particular, it explores economic mechanisms of exchange suitable for use by automated intelligent agents. It begins with the relatively traditional approaches in game theory and mechanism design in which economic mechanisms are evaluated and analyzed with simple, straightforward agent bidding strategies. Extensive attention is then paid to the creation of sophisticated bidding strategies given a fixed economic exchange mechanism. For other courses taught by Stone on related topics, visit here.

Agent-Based Modeling (Abdollahian, Claremont Graduate University):

Dr. Mark Abdollahian (School of Politics and Economics, Claremont Graduate University) has developed a course titled Computational Agent-Based Modeling. The goals of this course are to survey agent-based models (ABMs) and their methodological foundations across several disciplines so students can build their own ABMs. ... The applied pedagogy is grounded in an interactive, participatory and product oriented philosophy. The course is designed to quickly introduce ABM simulation and modeling concepts and then prepare students to design, build and evaluate their own ABM in politics or economics. ... The course is designed for advanced graduate students familiar with quantitative computational social science, including but not limited to game theory, econometrics, formal modeling and computational analytic methods.

Agent-Based Modeling and Simulation (Earnest, Old Dominion University):

David C. Earnest, an associate professor of political science and international studies at Old Dominion University in Norfolk, Virginia USA, has prepared a course titled IS 765/865: Agent-Based Modeling and Simulation for International Studies. This course introduces masters and doctoral students to complex systems theory and to the application of agent-based modeling technologies to a variety of social systems. The course seeks to train graduate students to use basic computer simulations as a tool of inference for their research in international studies. Topics include the principles of chaos and complex systems and their relevance to contemporary issues in world politics; the epistemological foundations of simulation; object-oriented programming for the beginner; basic genetic algorithms, and the inferential challenges of nonlinear systems. Consistent with the University’s commitment to modeling and simulation, the course emphasizes the interdisciplinary nature of agent-based modeling and simulation and welcomes students from a variety of disciplines, including physics, chemistry, geography, biology, engineering, sociology, psychology, economics and international studies.

Behavioral Economics (Crawford, University of Oxford, UK):

Vince Crawford (Economics, University of Oxford) has prepared a comprehensive and fun syllabus for a graduate course (Economics 142) on Behavioral Economics. The course is divided into two parts: (1) behavioral decision theory; and (2) behavioral game theory. In addition, he has prepared a syllabus for an undergraduate course on Behavioral and Experimental Game Theory. From the course description: "(This course) will discuss the leading alternative approaches to analyzing strategic behavior -- noncooperative game theory, cooperative game theory, evolutionary game theory, and adaptive learning models -- focusing on games with symmetric information. There are two main goals: (i) to introduce the leading approaches and the modeling issues they address; and (ii) to examine their performance in the light of empirical evidence on strategic behavior, in the hope of moving closer to the kind of understanding needed to analyze strategic interactions in economics and related fields."

Bounded Rationality and Macroeconomics (Gerhardt, U of Berlin):

Holgar Gerhardt (University of Berlin) has developed a course titled Bounded Rationality and Macroeconomics. The class starts by reviewing the rationality concept commonly employed in economic models ("full rationality") and its implications for the motion of variables of macroeconomic interest: for example, inflation, the smoothness of consumption, and the structure and volume of trading on financial markets. The existence of deviations between the predictions of theoretic models and actual data is investigated. "Full rationality" is then contrasted with approaches viewing humans as being "boundedly rational." Psychological and neurological findings on human decision-making are presented, based on work by Colin Camerer. Models applying these findings to macroeconomic analysis are introduced, with an emphasis on models that assume agents have only limited abilities to gather and process data. Key concepts considered include "rational inattention," the use of heuristics, learning, epidemiological expectations, and robust control. Asset markets are stressed throughout the course as a principal source of illustrations.

Business Complexity (Argonne,SFI,U of Chicago):

Argonne National Laboratory (Argonne, Illinois), the Santa Fe Institute, and the University of Chicago annually host a course titled Capturing Business Complexity with Agent-Based Modeling (ABM) and Simulation. This short course (typically six days) offers an intensive introduction to agent-based modeling and simulation with a focus on business applications. The course is divided into two sessions. The first stresses ABM concepts from the perspective of company managers and analysts and has no prerequisites. The second focuses on ABM implementation from the perspective of company software developers and includes extensive hands-on exercises. Prerequisites for the second session are a good knowledge of general ABM concepts and basic familiarity with a high-level programming language.

Business Research (Moore, University of Michigan)

Scott Moore (Business, University of Michigan) has developed a PhD seminar titled Complexity and Simulations in Business Research. The course explores complex adaptive systems modeling tools, and examines applications of these tools to business problems. An astonishing number of interesting links are provided. The NetLogo modeling environment (a descendant of StarLogo) is used for many illustrative hands-on applications.

Chaos and Complexity (Brock, University of Wisconsin):

William A. Brock (Emeritus Professor of Economics, University of Wisconsin, Madison) has developed a graduate course Econ 606 titled New Trends in Economic Theory (pdf). The unifying topics and tools of the course are: (1) stochastic dynamic systems theory; (ii) self-organization theories of the Santa Fe Institute variety; and (iii) econometric methods that stress heterogeneity. Topics covered include dynamical systems approaches to learning and to the design of experiments, recent work on systems with multiple time scales and multiple "spatial" scales, and a detailed contrast and comparison of different methods of presenting "stylized facts." The purpose of the course is to bring students to the research frontier in chaos and complexity theory as well as to inform them of recent empirical applications and open research problems.

Classroom Games (Holt, University of Virginia)

Charles Holt (Economics, University of Virginia) maintains a site titled Computer Programs for Classroom Games. This site provides about thirty-five interactive web-based programs available for general use, especially for teaching. The programs include markets (e.g., auctions), individual decision problems, asymmetric information games, bargaining, and public goods games. The students log in through any browser and are then connected to the database table for the particular experiment that you have set up in advance for them via the administrative web pages. The administrative menu has links to html files that describe each experiment and how to base a classroom discussion on the experimental findings.

Complexity Theory in the Social Sciences (Axelrod, University of Michigan):

Robert Axelrod (School of Public Policy Studies, University of Michigan, Ann Arbor) has developed a graduate course (PS 793) titled Complexity Theory in the Social Sciences. This course considers a wide variety of applications of agent-based models to the social sciences, including residential segregation, revolution, social influence, urban growth, war, alliances, organizational change, elections, and stock markets.

Computational Economics (van Kooten, Canada):

G. Cornelis van Kooten (University of Victoria, CA) has prepared a course Econ 549 titled Computational Economics to introduce the use of methods from operational research in the solving of economic problems.

Computer Simulation in the Social Sciences (Janssen, Arizona State University):

Marco Janssen (School of Human Evolution and Change, Arizona State University) has prepared a course titled Computer Simulation in the Social Sciences. The objective of the course is to introduce students to the use of computer simulation for the study of social phenomena such as coooperation,diffusion, and foraging. Students learn the basics of systems dynamics, cellular automata, and agent-based models, evolutionary programming, neural networks, and network-growing models. These techniques are used to study social systems from ancient to modern times. Attention is also given to the testing of simulation models and empirical validation issues.

Computation and Market Mechanism (Suri and Wolski, UC-Santa Barbara):

Subhash Suri and Rich Wolski (Computer Science UC-Santa Barbara, CA) have developed a course (CS-595J) titled Computation and Market Mechanisms. This course focuses on market-based methodologies, both for distributed resource allocation and Internet-based commerce. These applications involve self-interested agents, and thus economic and game theoretic issues play an important role. Topics covered (many with linked readings) include various market formulations and their realizations in different settings, and the algorithmic properties of various combinatorial auctions and commodity markets.

Computational Economics (Rust, University of Maryland):

John Rust (Economics, University of Maryland, College Park) has developed a graduate course titled Computational Economics. The course is designed to give students tools for numerical dynamic programming and the computation of related general equilibrium and game-theoretic problems.

Computational Economics (Doraszelski, Harvard U)

Ulrich Doraszelski (Harvard University) has developed a course titled Computational Economics. The objective of the course is to introduce graduate students to computational approaches for solving economic models. Economic problems are formulated in computationally tractable form and techniques from numerical analysis are used to solve them. Particular attention is given to methods for solving dynamic optimization problems and for computing equilibria of games. Applications include problems from industrial organization, game theory, macroeconomics, finance, and econometrics. The default computer language for in-class exercises is Matlab.

Computational Economics (Stachurski, Australian National University)

Lecture materials on computational economics by John Stachurski (Research School of Economics, Australian National University) can be obtained here. Tools used include Python/NumPy.

Computational Mechanism Design (Parkes, Harvard U):

David C. Parkes (Harvard University) has developed a course titled CS286r: Computational Mechanism Design. Computational mechanism design is a topic of study at the interface between computer science and economics. The problem domain considers distributed open systems with self-interested agents that seek to improve outcomes in their favor. Examples are drawn from e-commerce (Internet auctions, electronic markets for supply chains, automated bidding agents), and from computational applications such as resource allocation in computational grids and routing across peer-to-peer wireless networks.

Computational Modeling and Analytics in Social Science (Blikstein, Stanford University):

Paulo Blikstein (Stanford University) has a course titled CS 424M/Educ 390X: Computational Modeling and Analytics in Social Science. The goal of the course is to introduce students to agent-based computational modeling methods to support research in the learning, cognitive, and social sciences.

Computational Modeling of Organizations, Technology, and Society (Carley, Carnegie Mellon):

Kathleen Carley (Carnegie Mellon University, Pittsburgh). has prepared a course titled Computational Modeling of Organizations, Technology, and Society. This course teaches students how to design and analyze computational models and how to evaluate the results of other computational models. Topics covered include representation of groups, organizational structure, communication, information and knowledge, technology, and task; tracing information flow and belief changes; optimization models; canonical tasks; performance measures; data capturing; virtual experiments; model docking; levels and types of validation; and social Turing tests. Illustrative models are drawn from recent publications in the areas of computational organizational theory, computational sociology, and computational economics.

Computational Political Economy (Burns and Keswell, University of Cape Town):

Justine Burns and Malcolm Keswell (School of Economics, University of Cape Town, South Africa) have developed a course titled Computational Political Economy. The focus of the course is on the social and political foundations of economics. The basic premise of the course is that economists need to adopt a more inclusive view of social norms, institutions, and the state in understanding the role and functioning of markets. The aim of the course is to introduce students to recent advances in the fields of behavioral and institutional economics. In particular, students are introduced to agent-based modeling as a useful tool for the simulation of a society under different institutional arrangements. Many of the course materials (lecture notes, readings, lab session materials) are made accessible on-line.

Computer Science, Game Theory, and Economics (Nisan, Hebrew University):

Noam Nisan (Computer Science, Hebrew University, Israel) has prepared a graduate seminar titled Topics on the Border of Computer Science, Game Theory, and Economics. The seminar consists of a series of topics offered by visiting speakers (most with downloadable ppt slides). Sample topics include: auctions and combinatorial auctions; frugal path mechanisms; incentive compatible interdomain routing; statistical learnability and rationality of choice; and graphical models in game theory.

Computer Tools for Economics (Pellizzari, Italy):

Paolo Pillizari (Italy) has developed a course titled Computer Tools for Economics. Covered topics include: network connectivity; tagged typesetting; R (programming environment for statistics and more); Excel; Maple/MuPAD; Web resources for economists; intro to statistical packages (Stata); NEOS, SWeave, and BibTex; and introduction to computational economics.

Computing for the Physical and Social Sciences (Steiglitz, Princeton University):

Ken Steiglitz (Computer Science, Princeton U), has prepared a course (COS 323) title Computing for the Physical and Social Sciences. This course covers basic principles of scientific computation, driven by current applications in biology, physics, economics, engineering, and other fields.

Design of Experiments (Houser, GMU):

Course materials on the design and analysis of experiments prepared by Prof. Dan Houser (George Mason University, Fairfax, VA) can be obtained here.

Economics and Computation (Feigenbaum, Yale):

Joan Feigenbaum (Computer Science, Yale University, New Haven) offers a dual-listed course Econ425/563 (CPSC455/555) titled Economics and Computation. This course is a mathematically rigorous ivestigation of the interplay of economic theory and computer science with an emphasis on the relationship of incentive compatibility and computational efficiency. Particular attention is paid to the formulation and solution of mechanism-design problems that are relevant to data networking and Internet-based commerce. The course is suitable for mathematically inclined advanced undergraduates and first- or second-year graduate students in computer science, economics, or closely related fields.

Electronic Commerce (Shoham, Stanford):

Yoav Shoham (Computer Science, Stanford University, CA) has developed a graduate course (CS 206) titled Technical Foundations of Electronic Commerce. The course focuses on technological issues. Covered topics include algorithms, data structures, complexity, software engineering, and other computer science issues.

Evolutionary Modelling of Technical Change and Economic Dynamics (Anderson et al., Strasbourg):

A Ph.D. course titled Evolutionary Modelling of Technical Change and Economic Dynamics was offered in Strasbourg during October 12-15, 1998, led by Esben Andersen (IKE, Aalborg), Giovanni Dosi (IIasa, Vienna), Patrick Llerena (BETA, Strasbourg), Gerald Silverberg (MERIT, Maastricht), and Murat Yildizoglu (BETA, Strasbourg). The course was arranged by the European Doctoral Training Programme on the Economics of Technological and Institutional Change.

Experimental Economics (Sunder, Yale U):

Shyam Sunder offers a Ph.D. Seminar at Yale University on Experimental Economics (MGMT 703). The seminar is intended to help students develop hands-on experience in designing and conducting economics experiments and analyzing the data. Topics covered include: the experimental method; auctions; industrial organization; corporate finance; game theory; bargaining; asset markets; and expectations and learning in monetary economies. The seminar home page provides pointers to many related resources. For more information, visit here.

Games Economists Play (Delemeester and Brauer, Marietta college):

Gred Delemeester (Marietta College, Ohio) and Jurgen Brauer (Augusta State University, Georgia) maintain a resource site for instructors of economics titled Games Economists Play: Non-Computerized Classroom Games for College Economics. The bulk of this site consists of an extensively annotated and hyperlinked compilation of more than 120 classroom games, most of which can be played within one class period. The purpose of the games is to teach fundamental microeconomic and macroeconomic principles.

Institutional Economics (Bowles, University of Massachusetts at Amherst):

Samuel Bowles (Economics, UMass at Amherst, MA) has prepared a graduate course (Econ 797) titled Seminar in Theoretical Institutional Economics. The seminar is an introduction to recent research - both theoretical and empirical - concerning institutions and their evolution. It is designed for those simply wanting a survey of this literature as well as for those intending to do research in the area.

Integrated Economic Modeling and Sustainable Development (Angus/Parris, Monash U, Australia):

The syllabus for a course on Integrated Economic Modeling and Sustainable Development taught from a complexity point of view by Dr. Simon Angus and Dr. Brett Parris (Monash University, Clayton, Australia) can be obtained here. Related course materials can be obtained from Dr. Parris here.

Internet Agent Economics (Greenwald, Brown University, RI):

Amy Greenwald (Computer Science, Brown University, Providence, RI) has prepared a graduate course titled Topics in Game-Theoretic Artificial Intelligence. This course is concerned with the use of game theory and economics as frameworks in which to model the interactions of Internet agents. It covers both the design of Internet agents and the design of Internet mechanisms in which agents interact. Selected topics include web auctions, comparison shopping, and automated negotiation.

Market Design (Roth and Coles, Harvard University):

Al Roth and Peter Coles (Economics, Harvard University, Cambridge) have prepared a graduate course titled Market Design. This course deals with the theory and practice of market design, with prominent examples drawn from auctions and labor markets.

Microeconomics of Competition, Coordination, Cooperation, and Conflict (Bowles, University of Massachusetts at Amherst):

Samuel Bowles (Economics, UMass at Amherst, MA) has prepared a graduate course (Econ 700) titled The Microeconomics of Competition, Coordination, Cooperation, and Conflict. The course provides an introduction to fundamental microeconomic concepts relevant to the generic problem of coordinating social interactions among autonomous actors, with particular attention to conflict, competition, collective action, and coordination failures in capitalist economies, and the process of innovation and change in individual preferences and social structures.

MultiAgent Systems (Wooldridge, University of Liverpool, UK)

Michael Wooldridge (Computer Science, University of Liverpool) has developed a multiagent systems teaching resource site to accompany his undergraduate textbook Introduction to MultiAgent Systems (John Wiley, March 2002). The site provides detailed book information, lecture slides, useful links, and various other types of teaching supplements.

Network Theory (Newman, University of Michigan):

Mark Newman (Physics and Complex Systems, University of Michigan, Ann Arbor) has prepared a graduate course (Complex Systems 535) titled Network Theory. This course introduces and develops the mathematical theory of networks, particularly social and technological networks. Applications are made to important network-driven phenomena in epidemiology of human infections and computer viruses, the Internet, network resilience, web search engines, and many others.

Numerical Methods in Economics (Possajennikov, U of Nottingham, UK):

Alex Possajennikov (University of Nottingham, UK) has developed a course module (L13614) titled Numerical Methods in Economics. The objective of the module is to introduce students to numerical techniques that can be used to model and solve economic problems. Covered topics include: numerical optimilzation; non-linear programming; and agent-based economic modeling.

Political Science and Agent-Based Modeling (Lustick, University of Pennsylvania):

Ian Lustick (Political Science, University of Pennsylvania) has prepared a course (Political Science 498) titled Politics, Agent-Based Modeling, and Computer Simulations. The basic objective of the course is to explore how recent developments in evolutionary theory, and in studies of complexity and complex adaptive systems, provide a basis for important critiques of standard approaches in political science. Students are taught how to use PS-1, an agent-based computer simulation platform, to develop their own models, conduct experiments, test hypotheses, or produce existence proofs in relation to popular theoretical positions in contemporary political science. No previous knowledge of computer programming is required.

RepastJ Self-Study Guide (Tesfatsion, Iowa State University):

Repast (REcursive Porous Agent Simulation Toolkit) is an agent-based simulation toolkit developed by researchers at the University of Chicago and Argonne National Laboratory for social science applications. The latest version of Repast supports model development in many different languages and on virtually all modern computing platforms. Leigh Tesfatsion (Economics, Iowa State University, Ames, IA) has prepared a RepastJ Self-Study Guide for use by newcomers to RepastJ (Repast based on Java). Topics covered in this self-study guide include: Intro to Agent-Based Modeling; Intro to Agent-Oriented Programming; Intro to Java; Getting Acquainted with RepastJ; Programming with RepastJ; and Possible RepastJ Modeling Application Areas. Extensive links are provided to on-line resource materials. Although some prior programming experience is desirable, the study guide does not presume such experience.

Social Dynamics and Self-Organizing Systems (White, UC-Irvine):

Douglas White (Anthropology, UC-Irvine, CA) has organized a course (Anthro 179A) titled Social Dynamics and Self-Organizing Systems. This course focuses on the newly emergent sciences of complexity to study the principles of self-organization of social systems. Fundamental principles of complex adaptive systems are reviewed in the context of cutting edge research ranging in topic from studies of Renaissance Florence to studies of contemporary market systems.

Social Ecology and Evolutionism Course (Hughes, Chicago):

In 1994 James Hughes (Changesurfer Consulting, Chicago) taught a course titled Social Ecology and Evolutionism at the University of Chicago. The course is an introduction to the ecological and evolutionary concepts that have influenced the social sciences. Topics covered include: Introduction to Social Ecology; Hardware and Software; Organizational Ecology and Evolution; Social Organicism and Early Sociological Evolutionism; and Modern Social Ecology.

Social Science Simulation (Marks, University of New South Wales):

Robert Marks (Austalian Graduate School of Management, University of New South Wales) has developed a Ph.D. course titled Simulation in the Social Sciences. Topics covered include: Introduction to simulation in the social sciences; System dynamics; Micro-analysis and cellular automata; Agent-based models; and Learning and evolutionary models. Annotated pointers to software and other links are also provided.

Social Science Simulation (Cederman, Zurich)

Lars-Erik Cederman (International Conflict Research, Zurich) has developed a course titled Introduction to Computational Modeling of Social Systems. The course begins with an introduction to the rationale and principles of agent-based modeling. It also briefly covers the basics of object-oriented programming using Java, and it introduces Repast, an agent-based toolkit designed specifically for social science applications. The remainder of the course focuses on the computational modeling of social systems, drawing on a number of concrete examples from political science, economics, and sociology implemented in Repast/Java. Most course materials are freely provided on-line, including lectures and Repast/Java tutorials.

Program Information

Center for the Study of Complex Systems (University of Michigan, Ann Arbor)

The Center for the Study of Complex Systems (CSCS) at the University of Michigan, Ann Arbor, offers a graduate curriculum leading to a Graduate Certificate in Complex Systems. The CSCS also supports a wide variety of other activities related to complex systems, including: a weekly seminar series; research workshops; an annual symposium; and a workshop in collaboration with the Santa Fe Institute.

Centre for Computational Finance and Economic Agents (University of Essex, UK)

The Centre for Computational Finance and Economic Agents (CCFEA) is an interdisciplinary laboratory-based center located at the University of Essex, UK. CCFEA is a showcase for cutting-edge computational and evolutionary methods to simulate artificially intelligent agents in markets and other complex economic environments. CCFEA offers programmes leading to an MSc in Computational Finance, an MSc in High-Frequency Finance and Trading, an MSc in Financial Software Engineering, a PhD in Computational Finance, and a PhD in Computational Economics. Students pursuing these programmes will receive rigorous training in the principles of quantitative finance and microeconomics along with computational skills.

Complex Systems (Northwestern University, Evanston, IL)

The Northwestern Institute on Complex Systems (NICO) offers 1-3 year post-doc fellowship opportunities to young researchers who have interest in the study of complex systems and in interdisciplinary collaborations. Applicants must be self-motivated and goal-oriented individuals who have recently obtained their Ph.D. and who possess outstanding potential. Applicants must be able to successfully communicate ideas to diverse audiences, build on existing strengths, bridge different fields, and be motivated to work with NICO faculty on interdisciplinary complex systems projects.

Computable and Experimental Economics (University of Trento, Italy):

The Computable and Experimental Economics Laboratory (CEEL) (Department of Economics, University of Trento, Italy) offers intensive summer courses on selected topics related to computational economics. Past years' topics have included: computable economics; experimental economics; adaptive economic processes; behavioral economics; institutional economics; and evolutionary economic dynamics. The course is targeted at Ph.D. students and postdocs. Participation at the summer school is free of charge for accepted applicants. The deadline for receipt of applications is typically early in March.

Leigh Tesfatsion and Rob Axtell co-directed the VII Trento Summer School (July 3-21), an intensive course on Agent-based Computational Economics (ACE) for graduate students and professors interested in teaching ACE themselves. If interested, you can access the schedule of topics covered by regular and guest lecturers as well as an on-line syllabus of supporting materials for the particular topics covered by Leigh Tesfatsion.

Computational Economics Workshop and Research Community (New York)

A group of faculty and students from CUNY, Columbia, Rutgers, and the New School have formed a Computational Economics Workshop to be held at the New School (CEPA, 5th Floor, 80 Fifth Avenue - corner of 14th and 5th, 3:00pm). The focus of the workshop will be on agent-based computational economics, heterogeneous-agent modeling, social network analysis, and related areas. The group is seeking people in the New York area that might be interested in participating in this workshop and interacting with this research community. For more information, and to join the mailing list for receiving workshop announcements, contact Jason Barr ( jmbarr AT andromeda.rutgers.edu).

Computational Intelligence (University of Plymouth, UK):

The Centre for Robotics and Intelligent Systems at the University of Plymouth (UK) conducts a broad array of research activities related to computational intelligence and multi-agent systems.

Computational Social Sciences (George Mason U, Fairfax, VA):

The Center for Social Complexity at George Mason University (Fairfax, Virginia) offers a PhD Program in Computational Social Science. The core objective of this program is to train graduate students to be professional computational social scientists in academia, government, or business. The program offers students a unique and innovative interdisciplinary environment for systematically exploring, discovering, and developing their skills to successfully follow careers in one of the areas of computational social science. For more information, visit here.

Economics Group (Northwestern University, Evanston, IL):

The Economics Group in the Electrical Engineering and Computer Science Department at Northwestern University studies the interplay between the algorithmic, economic, and social aspects of the Internet and related systems, and develops ways to facilitate users' interactions in these systems. This work draws upon a wide variety of techniques from theoretical and experimental computer science to traditional economic frameworks. By applying these techniques to economic and social systems in place today, we can shed light on interesting phenomena and, ideally, provide guidance for future developments of these systems. This interdisciplinary effort is undertaken jointly with the Managerial Economics and Decision Sciences Department in the Kellogg School of Management, The Center for Mathematical Studies in Economics and Management Science, and other institutions at Northwestern University and the greater Chicago area.

Graduate Workshop in Computational Social Science Modeling and Complexity (SFI, Santa Fe):

Each summer since 2001, John Miller (Carnegie Mellon U) and Scott E. Page (U of Michigan) have conducted the Graduate Workshop in Computational Social Science and Modeling at the Santa Fe Institute (SFI) in Santa Fe, New Mexico. The workshop brings together small groups of advanced graduate students and faculty for an intensive two-week study of computational social science modeling and complexity. Workshop activities include lectures by regular faculty, guest speaker lectures, and presentations of course projects by students. The primary goal of the workshop is to assist graduate students pursuing research agendas which include a computational modeling component. For more information, visit here.

Harvard EconCS Group:

The Harvard EconCS group is pursuing research, both theoretical and experimental, at the intersection between computer science and economics. We draw on methodologies from AI, multi-agent systems, computer science theory, microeconomic theory, optimization and distributed systems. We are interested in electronic auctions, mechanisms and markets, peer production and social computing, and in the constructive use of economic methodologies within computational systems. A central challenge is to resolve conflicts between game-theoretic and computational constraints. Current topics of interest include: incentive-based environment design; dynamic mechanisms; the design of mechanism infrastructures and currencies for distributed and peer-to-peer systems; preference elicitation; information aggregation; applications to e-commerce and social computing; cryptographically secure auctions; and network formation games. For more information, visit here.

Human-Computer Interaction Graduate Program (Iowa State University, Ames):

From the homepage of the ISU Human-Computer Interaction Program: "The study of the relationship between humans and increasingly powerful, portable, interconnected and ubiquitous computers is becoming one of the most dynamic and significant fields of technical investigation. The Interdepartmental Graduate Major in Human Computer Interaction is an interdisciplinary training program created to provide advanced training and foster research excellence in Human Computer Interaction at Iowa State University." Both an M.S. and Ph.D. degree in Human Computer Interaction are offered.

IEEE Computational Finance & Economics Network (Multiple Program Listing):

The IEEE Computational Finance and Economics Technical Committee supports a number of task forces focusing on computational finance and economics issues, including a Task Force on Agent-Based Computational Economics.

Individual/Agent-Based Modeling and Ecology (Humboldt State University, CA):

The Individual/Agent-Based Modeling and Ecology program at Humboldt State University (Arcata, California) stresses research on the use of individual-based models (IBMs) for applied and theoretical ecology. The program is affiliated with the Mathematical Modeling Program, HSU Mathematics Department. This research is a collaboration of mathematicians, ecologists and biologists, environmental engineers, and software professionals.

Institute of Computational Economics (U of Chicago/Argonne):

The Economic Research Center at the University of Chicago in conjunction with the Argonne National Laboratory (Argonne, Illinois) have formed an Institute on Computational Economics (ICE). The primary function of the ICE is to train young scholars (advanced graduate students and junior faculty) in state-of-the-art numerical methods and computer technology, and their application to economic modeling and analysis. The following topics will be stressed: Numerical optimization; Dynamic programming; Solution methods for dynamic economic models; and Statistical computing. The ICE will host a summer program of activities for young scholars that includes tutorials, seminars, and workshops featuring recent advances in quantitative economic policy research. Application information can be obtained at the ICE website.

International Doctoral Program in Economics (Scuola Superiore Sant'Anna, Italy, and University of Strasbourg, France)

The International Doctoral Program in Economics (IDPE) is jointly offered by Scuola Superiore Sant'Anna, Pisa, Italy and by the University of Strasbourg, France. The IDPE is a three-year program designed for highly qualified and motivated students who wish to acquire the research and analytical skills of the international scientific community in economics. It is designed for students pursuing jobs in academia as well as those who wish to acquire the skills of professional academic research to work in government agencies, financial institutions, international agencies, private companies. Students will be offered one year and a half of intensive course work by an international Faculty composed of both permanent staff of the School and a large group of Visiting Scholars. All teaching is in English. Courses will focus on both standard mainstream economics, as well as more "heterodox" approaches, such as evolutionary economics and agent-based computational economics. Some scholarships are available; see the IDPE website for application information.

Nonlinear Dynamics in Economics and Finance (University of Amsterdam):

The Center for Nonlinear Dynamics in Economics and Finance (CeNDEF) is a multi-disciplinary research institute started in 1998 and located at the Department of Economics and Econometrics at the University of Amsterdam. Research topics addressed by CeNDEF participants include: endogenous fluctuations; bounded rationality; expectation formation and learning, evolutionary dynamics, bifurcations and chaos, nonlinear time series analysis, and nonlinear prediction methods.

Santa Fe Institute Complex Systems Summer School:

The SFI Complex Systems Summer School held annually each June at the Santa Fe Institute (SFI) in Santa Fe, New Mexico, USA, is an intensive introduction to complex behavior in mathematical, physical and living systems for graduate students and postdoctoral fellows. Tuition is waived for graduate students and postdocs who attend the full program. Postdocs are charged half of the cost for room and board. Travel assistance is not available. The first week of the school typically consists of toolkit courses and lectures to acquaint students with some of the theoretical tools they will need for research in complex systems. During each of the second, third, and fourth weeks there are typically lecture courses with lectures in the morning followed by selected seminars in the afternoons. Generally there is also time set aside for students to work on projects and to self-organize into working groups on particular topics.

The deadline for applications is typically set at around February 7th of each year for the subsequent summer course. In past years, applicants have been asked to provide a current resume with a publications list, a statement of current research interests, comments about why the applicant wants to attend the school, two letters of recommendation from scientists who know the applicant's work, and complete applicant address information (including email and fax number). Applicants have been requested to send their complete application packages by postal mail to: Summer School, Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico, USA 87501, Tel: 505-984-8800, ext 235 (v); 505-982-0565. Incomplete application packages are generally not considered. If you are interested in applying for the next Complex Systems Summer School, it would be wise to first obtain up-to-date information about current application requirements either at the above Complex Systems Summer School homepage or by sending an email request to summerschool@santafe.edu.

Social Complexity Studies (University of Groningen):

The Groningen Center for Social Complexity Studies (GCSCS) serves as a platform connecting researchers at or affiliated with the University of Groningen working in the field of social complexity. The aim of the GCSCS is to provide high quality research and education, interacting actively with business, government and the public, and in particular to address the goal of stimulating cross-border research and education. A key focus of GCSCS researchers is how interactions between individual people or animals give rise to group phenomena such as the diffusion of new behaviours, social networks, societial polarisation, crowd behaviours and spatial arrangements.

Teaching Individual/Agent-Based Modeling (Humboldt State University):

Humboldt University (California) is offering a one week summer course organized around a 2011 book by Steven Railsback and Volker Grimm, titled Agent-Based and Individual Modeling: A Practical Introduction. The purpose of the course is to prepare college professors and instructors to add individual-based modeling (IBM) -- also known as agent-based modeling (ABM) -- to their teaching and research skills. Topics to be covered include: when and why to use IBMs, for both theoretical and applied science; strategies for designing models that are "as simple as possible, but not simpler"; software techniques: programming IBMs, testing software, and running simulation experiments; model analysis and publication: how to produce science once a model is built; and linking your empirical research to individual-based science.

Copyright © 2012 Leigh Tesfatsion. All Rights Reserved.