Agent-Based Computational Economics and Market Design:
the Fourth Herbert Simon Lectures
National Chengchi University, Taipei
National Kaohsiung University of Applied Sciences, Kaohsiung
October 23-28, 2005
The five lectures, Agent-Based Computational Economics (ACE) and Market Design, are an intensive introduction to Agent-Based Computational Economics modelling: the reasons for ACE, the methods of ACE, the strengths and weaknesses of ACE, and the applications of ACE to the emerging discipline of Market Design. The readings accompanying the lectures are available at the links below.
Simulation of social interactions focuses on the complex adaptive behavior that emerges in social systems. To better understand the behavior of such complex adaptive social systems, "artificial worlds" composed of interacting adaptive agents can be created and analyzed. Such models often exhibit properties that are strikingly similar to the actual social world, e.g., cooperation, social norms, and social stratification into different classes, and provide a unique window into understanding such phenomena. Using simulation methods, previously inaccessible, yet fundamental, questions are now becoming amenable to analysis. There is much research to be done in this area---along with creating and understanding these types of complex systems, efforts need to be directed toward developing accessible versions of these models for the classroom.
The AI-Econ Research Center, National Chengchi University, Here.
- Prime Reference: Nigel Gilbert and Klaus G. Troitzsch, Simulation for the Social Scientist, Buckingham: Open University Press, 2nd edition, 2005. See its web site here.
- A glossary of terms encountered in these lectures is here.
- An informative reading on the Monte Carlo method here.
- NetLogo is a programmable environment for exploring the workings of decentralised systems, specifically designed to be user-friendly for students: here. (NetLogo 3.0 was released on September 15, 2005.)
- Lecture 1: Introduction, models, framework.
Simulations: concepts and grand challenges.
G&T: Ch 1 and 2.
Bob's Introductory overheads: OHs || Printable
Bob's Model lecture overheads, after March & Lave: OHs || Printable
Bob's Simulation lecture overheads: OHs || Printable
- Andrea Schertler reviews Simulation for the Social Scientist by Gilbert and Troitzsch, 1999, Here.
- Axelrod: Advancing the art of simulation in the social sciences (revised 2003). Here
The Replication of Eight Simulation Models from Axelrod 2003: Here.
- R. Axtell, R. Axelrod, J.M. Epstein, and M.D. Cohen, Aligning Simulation Models: A Case Study and Results, Computational & Mathematical Organization Theory 1(2): 123-141, 1996. Here.
- James G. March, Charles A. Lave Introduction to Models in the Social Sciences, New York: HarperCollins, 1975. Extract Here.
- Schelling, T. (1978). Micromotives and macrobehavior. New York: W. W. Norton. (See especially 137-55.) Here.
- J.P. Marney and Heather F.E. Tarbert (2000), Why do simulation? Towards a working epistemology for practitioners of the dark arts, Journal of Artificial Societies and Social Simulation vol. 3, no. 4, , Here.
- Paul E. Johnson reviews Tools and Techniques for Social Science Simulation, edited by Suleiman, Troitzsch & Gilbert, 2000. Here.
- Robert Marks, Simulating economics, Australian Journal of Management, Vol. 27, No. 1, June 2002, pp. i-iii. Here.
- Robert Marks, Models rule, Australian Journal of Management, Vol. 28, No. 1, June 2003, pp. i-iii. Here.
- Scott Moss, Canonical Task Environments for Social Simulation: Here.
- John H. Miller, Active non-linear tests (ANTs) of complex simulation models, Management Science, 44(6): 820-830, 1998. Here.
- Lecture 2: Agent-Based Models
G&T: Ch 8 and 9.
Bob's Model lecture overheads: OHs || Printable
- Robert Axelrod and Leigh Tesfatsion, On-Line Guide for Newcomers to Agent-Based Modeling in the Social Sciences, forthcoming in Leigh Tesfatsion and Kenneth L. Judd (Eds.), Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics, Handbooks in Economics Series, North-Holland, Amsterdam, 2006, to appear, Here.
Web support materials (readings and demonstration software). Here.
- Pietro Terna (2001), Creating Artificial Worlds: A Note on Sugarscape and Two Comments, Journal of Artificial Societies and Social Simulation 4(2). Here.
- Gilbert, N., Terna P., How to build and use agent-based models in social science, Mind & Society, no. 1, 2000, Here.
- Sallach D.L., Macal C.M., Introduction: The Simulation of Social Agents, Social Science Computer Review, 19(3): 245-248, August 2001. Here.
- Robert Axtell: Why agents? On the varied motivations for agent computing in the social sciences, Center on Social and Economic Dynamics Working Paper No. 17, November 2000, in Agent Simulation: Applications, Models, and Tools, 1999. Here.
- GulyÁs, L. On the Transition to Agent-Based Modeling: Implementation Strategies From Variables to Agents, Social Science Computer Review 20(4): 389-399, 2002.
- Bankes, S. Lempert, R. Popper, S., Making Computational Social Science Effective: Epistemology, Methodology, and Technology, Social Science Computer Review 20(4): 377-388, 2002.
- Adaptive Agents, Intelligence, and Emergent Human Organization: Capturing Complexity through Agent-Based Modeling: a supplement of the PNAS 99(3): May, 2002: Contents listed here, including:
- E. Bonabeau, Agent-based modeling: Methods and techniques for simulating human systems, Proc. National Academy of Sciences, 99(suppl. 3): 7280-7287, 2002. Here.
- Leigh Tesfatsion's information on application areas for agent-based model, from her course at Iowa State. Here.
- Roberto Leombruni, Matteo Richiardi, Why are economists sceptical about agent-based simulations? Physica A, 355 (2005) 103-109.
- SimWorld Ltd, a UK consulting company that includes "Innovative Business Solutions in Forecasting, Optimisation and Planning. Neural Nets, Genetic Algorithms, Fuzzy Logic and Complex Adaptive Systems Simulations."
- The Icosystem Game, a simple agent-based simulation to demonstrate emergent behaviour.
- Play the Game of Life on-line: Here.
- A Game of Life exhibit, with many patterns: Here.
Examine the MWSSGUN. Be sure to look in the Patterns Collection under "Rakes and Breeders" and "Ships and Trains" -- but don't stop there because there are lots more interesting things to do.
- On-line tool for playing with the Game of Life Here.
A Java-based program with which to study the Game of Life. Play this game at least five times. When you see the game either stop or cycle, hit the "Pause" button, and record how many generations have been played and how many are in the population.
What would happen if this game board wrapped around, instead of ending at the edges?
- A Probabilistic Life Here.
- Two 3D versions of Life: Here and Here.
- Lecture 3: Learning: GAs, RL, etc.
Bob's lecture overheads: OHs || Printable
G&T: Ch 10.
- Marks, R.E. (1988) Niche strategies: the Prisoner's Dilemma computer tournaments revisited, Here.
- Marks, R.E. (1992) Breeding optimal strategies: optimal behaviour for oligopolists, Journal of Evolutionary Economics, 2: 17-38. Here.
- Midgley, D.F., Marks, R.E., and Cooper, L.G. (1997) Breeding competitive strategies, Management Science, 43(3): 257-275. [The lead article.]
- Marks, R.E. (1998), Evolved perception and behaviour in oligopolies, Journal of Economic Dynamics and Control. 22(8-9): 1209-1233. Here.
- Marks R.E., Midgley D.F., Cooper L.G., Co-evolving better strategies in oligopolistic price wars, Here.
- Robert Hoffmann (2000), Twenty Years on: The Evolution of Cooperation Revisited, Journal of Artificial Societies and Social Simulation vol. 3, no. 2, Here.
- Edmund Chattoe (1998) Just How (Un)realistic are Evolutionary Algorithms as Representations of Social Processes? Journal of Artificial Societies and Social Simulation vol. 1, no. 3 Here.
- The Uses of Genetic Programming in Social Simulation: A Review of Five Books by Bruce Edmonds, Here.
- Carl Henning Reschke (2001), Evolutionary Perspectives on Simulations of Social Systems, Journal of Artificial Societies and Social Simulation vol. 4, no. 4 Here.
- Nicolaas J. Vriend, An illustration of the essential difference between individual and social learning, and its consequences for computational analyses, Journal of Economic Dynamics & Control, vol, 24: 1-19, 2000 Here.
- Szpiro G., The emergence of risk aversion, Complexity, 2(4), 31-39, 1997. Here.
- N.N. Schraudolf & J.J. Grefenstette, A User's Guide to GAucsd 1.4, Technical Report CS92-249, CSE Department, UC San Diego, 1992 Here.
- Marks R.E., and Schnabl H. (1999) Genetic Algorithms and Neural Networks: a comparison based on the Repeated Prisoner's Dilemma, Thomas Brenner (ed.), Computational Techniques for Modelling Learning in Economics, in the series Advances in Computational Economics 11, (Dordrecht: Kluwer Academic Publishers), pp. 197-219. Here.
- Lecture 4: Market Design
Bob's lecture overheads: OHs || Printable
- R.E. Marks: Market Design using Agent-Based Models, forthcoming in Leigh Tesfatsion and Kenneth L. Judd (Eds.), Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics, Handbooks in Economics Series, North-Holland, Amsterdam, 2006, to appear, Here
- Edmonds, B., and J. J. Bryson (2003), Beyond the Design Stance: The Intention of Agent-Based Engineering, Centre for Policy Modelling, CPM Report No.: CPM-03-126. Here.
- Phelps, S., P. McBurney, S. Parsons, and E. Sklar (2002a), Co-evolutionary auction mechanism design: a preliminary report, Lecture Notes In Computer Science: Revised Papers from the Workshop on Agent-Mediated Electronic Commerce IV, Designing Mechanisms and Systems, ed. by J. A. Padget, O. Shehory, D. C. Parkes, N. M. Sadeh, and W. E. Walsh, Berlin: Springer, pp. 123-142. Here.
- Phelps, S., S. Parsons, and P. McBurney (2004), An evolutionary game-theoretic comparison of two double-auction market designs, presented at the Workshop on Agent-Mediated Electronic Commerce VI: Theories for and Engineering of Distributed Mechanisms and Systems, New York, July 19. Here.
- Roth, A.E., (1991), Game Theory as a Part of Empirical Economics, Economic Journal, 101(401): 107-14. Here.
- Roth, A.E., (2000), Game theory as a tool for market design, in F. Patrone, I. Garcia-Jurado, S. Tijs (eds.) Game Practice: Contributions from Applied Game Theory, Kluwer, pp. 7-18. Here.
- Roth, A.E., (2002), The economist as engineer: game theory, experimentation, and computation as tools for design economics, Econometrica, 70(4): 1341-1378. Here.
- Walia, V., A. Byde, and D. Cliff (2002), Evolving Market Design in Zero- Intelligence Trader Markets, HPL-2002-290 Here.
- Tesfatsion, L., (2002), Agent-Based Computational Economics: Growing Economies from the Bottom Up, Artificial Life, 8(1): 55-82, October 2001, pp. 504-523.
- Lecture 5: Applications: Designing Electricity Markets and other Markets.
Bob's lecture overheads: OHs || Printable || References
- A. Hailu & S. Schilizzi, Are auctions more efficient than fixed price schemes when bidders learn? Australian Journal of Management, vol 29, no 2, Dec 2004. Here.
- Byde, A., Applying Evolutionary Search to a Parametric Family of Auction Mechanisms, Australian Journal of Management, vol 31, no 1, June 2006. (forthcoming) Here.
- Derek Bunn & Augusto Rupérez Micola, Agent-Based Models for Electricity Policy Design, June, 2005. Here.
Other Software and Platforms:
- Download Repast software from Here.
- Leigh Tesfatsion's RePast Study Group: Here.
- First steps with RePast : Here
- D.A. Robertson, Using RePast to Simulate Banking Firms in a Turbulent Environment: Here.
- Druckenmiller et al on Agent-Based Modeling and Simulation of Strategic Scenarios with RePast 2.0. Here
- Robert Tobias and Carole Hofmann (2004), Evaluation of free Java-libraries for social-scientific agent based simulation, Journal of Artificial Societies and Social Simulation vol. 7, no. 1 Here.
- Dugdale's An Evaluation of Seven Software Simulation Tools for Use in the Social Sciences: Here.
- Complete text of Dynamics of Complex Systems, by Yaneer Bar-Yam, (Westview, 2003) in PDF Here. Some of Leigh Tesfatsion's pages:
- Koblenz pages:
- The Journal of Artificial Societies and Social Simulation: Here
- Social Science Computer Review: Here and here.
- Computational & Mathematical Organization Theory Here.
- The International Journal of Microsimulation Here.
- The Electronic Journal of Evolutionary Modeling and Economic Dynamics (e-JEMED) Here.
- Journal of Economic Interaction and Coordination Here.
- The University of Michigan's Center for the Study of Complex Systems Computer Lab documentation: Here.
- Applications of AI to the Social Sciences. Here.
- Centre for Research on Simulation in the Social Sciences, Surrey University Here.
- Edmund Chattoe's Simulation Bibliography: Here.
Last Updated 8 November, 2005 Robert Marks, firstname.lastname@example.org