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Software for continuous game experiments

Published online by Cambridge University Press:  14 March 2025

James Pettit*
Affiliation:
Economics Department, University of California Santa Cruz, Santa Cruz, USA
Daniel Friedman*
Affiliation:
Economics Department, University of California Santa Cruz, Santa Cruz, USA
Curtis Kephart*
Affiliation:
Economics Department, University of California Santa Cruz, Santa Cruz, USA
Ryan Oprea*
Affiliation:
Department of Economics, University of California Santa Barbara, Santa Barbara, USA

Abstract

ConG is software for conducting economic experiments in continuous and discrete time. It allows experimenters with limited programming experience to create a variety of strategic environments featuring rich visual feedback in continuous time and over continuous action spaces, as well as in discrete time or over discrete action spaces. Simple, easily edited input files give the experimenter considerable flexibility in specifying the strategic environment and visual feedback. Source code is modular and allows researchers with programming skills to create novel strategic environments and displays.

Type
Original Paper
Copyright
Copyright © 2014 Economic Science Association

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References

Cason, T., Friedman, D., & Hopkins, E. (2013, forthcoming). Cycles and instability in a rock-paper-scissors population game: a continuous time experiment. Review of Economic Studies.CrossRefGoogle Scholar
Cox, J. C., Swarthout, J. T. Hess, C., & Ostrom, E. (2006). EconPort: creating and maintaining a knowledge commons. Understanding knowledge as a commons: from theory to practice, Cambridge: MIT Press.Google Scholar
Fischbacher, U. (2007). Z-tree: Zurich toolbox for ready-made economic experiments. Experimental Economics, 10(2), 171178. 10.1007/s10683-006-9159-4CrossRefGoogle Scholar
Friedman, D., & Oprea, R. (2012). A continuous dilemma. The American Economic Review, 102(1), 337363. 10.1257/aer.102.1.337CrossRefGoogle Scholar
Goeree, J. K., & Holt, C. A. (2001). Ten little treasures of game theory and ten intuitive contradictions. The American Economic Review, 91(5), 14021422. 10.1257/aer.91.5.1402CrossRefGoogle Scholar
Kagel, J. H., & Roth, A. E. (1997). Handbook of experimental economics, Princeton: Princeton University Press.Google Scholar
Lipps, D. B., Galecki, A. T., & Ashton-Miller, J. A. (2011). On the implications of a sex difference in the reaction times of sprinters at the Beijing Olympics. PLoS ONE, 6(10), 10.1371/journal.pone.0026141CrossRefGoogle ScholarPubMed
Oprea, R., Friedman, D., & Henwood, K. (2012). Separating the Hawks from the Doves: evidence from continuous time laboratory games. Journal of Economic Theory, 146(6), 22062225. 10.1016/j.jet.2011.10.014CrossRefGoogle Scholar
Rapoport, A., & Orwant, C. (1962). Experimental games: a review. Behavioral Science, 7, 137. 10.1002/bs.3830070102CrossRefGoogle ScholarPubMed
Schwarz, M., & Takhteyev, Y. (2010). Half a century of public software institutions: open source as a solution to hold-up problem. NBER Working Paper Series, No. 14946.CrossRefGoogle Scholar
Simon, L. K., & Stinchcombe, M. B. (1989). Extensive form games in continuous time: pure strategies. Econometrica, 57(5), 11711214. 10.2307/1913627CrossRefGoogle Scholar
Thrall, R. M., Coombs, C. H., & Davis, R. L. (1954). Decision processes, New York: Wiley.Google Scholar