Learning in networks: An experimental study using stationary concepts
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- Siegfried K. Berninghaus & Thomas Neumann & Bodo Vogt, 2014. "Learning in Networks—An Experimental Study Using Stationary Concepts," Games, MDPI, Open Access Journal, vol. 5(3), pages 1-20, July.
- Siegried K. Berninghaus & Thomas Neumann & Bodo Vogt, 2011. "Learning in Networks - An Experimental Study using Stationary Concepts," Jena Economic Research Papers 2011-048, Friedrich-Schiller-University Jena.
References listed on IDEAS
- Erev, Ido & Roth, Alvin E, 1998. "Predicting How People Play Games: Reinforcement Learning in Experimental Games with Unique, Mixed Strategy Equilibria," American Economic Review, American Economic Association, vol. 88(4), pages 848-881, September.
- Osborne, Martin J & Rubinstein, Ariel, 1998. "Games with Procedurally Rational Players," American Economic Review, American Economic Association, vol. 88(4), pages 834-847, September.
- Cassar, Alessandra, 2007. "Coordination and cooperation in local, random and small world networks: Experimental evidence," Games and Economic Behavior, Elsevier, vol. 58(2), pages 209-230, February.
- Kirchkamp, Oliver & Nagel, Rosemarie, 2005. "Learning and cooperation in network experiments," Sonderforschungsbereich 504 Publications 05-27, Sonderforschungsbereich 504, Universität Mannheim;Sonderforschungsbereich 504, University of Mannheim.
- Berninghaus, Siegfried K. & Ehrhart, Karl-Martin & Keser, Claudia, 2002. "Conventions and Local Interaction Structures: Experimental Evidence," Games and Economic Behavior, Elsevier, vol. 39(2), pages 177-205, May.
- Reinhard Selten & Thorsten Chmura & Sebastian J. Goerg, 2011. "Stationary Concepts for Experimental 2 X 2 Games: Reply," American Economic Review, American Economic Association, vol. 101(2), pages 1041-1044, April.
- Venkatesh Bala & Sanjeev Goyal, 2000. "A Noncooperative Model of Network Formation," Econometrica, Econometric Society, vol. 68(5), pages 1181-1230, September.
- Urs Fischbacher, 2007. "z-Tree: Zurich toolbox for ready-made economic experiments," Experimental Economics, Springer;Economic Science Association, vol. 10(2), pages 171-178, June.
- Ben Greiner, 2004. "The Online Recruitment System ORSEE 2.0 - A Guide for the Organization of Experiments in Economics," Working Paper Series in Economics 10, University of Cologne, Department of Economics.
- Reinhard Selten & Klaus Abbink & Ricarda Cox, 2005. "Learning Direction Theory and the Winner’s Curse," Experimental Economics, Springer;Economic Science Association, vol. 8(1), pages 5-20, April.
- Ho, Teck H. & Camerer, Colin F. & Chong, Juin-Kuan, 2007. "Self-tuning experience weighted attraction learning in games," Journal of Economic Theory, Elsevier, vol. 133(1), pages 177-198, March.
- Jackson, Matthew O. & Watts, Alison, 2002. "The Evolution of Social and Economic Networks," Journal of Economic Theory, Elsevier, vol. 106(2), pages 265-295, October.
- Reinhard Selten & Thorsten Chmura, 2008. "Stationary Concepts for Experimental 2x2-Games," American Economic Review, American Economic Association, vol. 98(3), pages 938-966, June.
- Kirchkamp, Oliver & Nagel, Rosemarie, 2007. "Naive learning and cooperation in network experiments," Games and Economic Behavior, Elsevier, vol. 58(2), pages 269-292, February.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Edward Cartwright & Anna Stepanova, 2017.
"Efficiency in a forced contribution threshold public good game,"
International Journal of Game Theory,
Springer;Game Theory Society, vol. 46(4), pages 1163-1191, November.
- Edward Cartwright & Anna Stepanova, 2015. "Efficiency in a forced contribution threshold public good game," Studies in Economics 1506, School of Economics, University of Kent.
More about this item
Keywordsexperimental economics; networks; learning;
- C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
- C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
- C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
- D85 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Network Formation
NEP fieldsThis paper has been announced in the following NEP Reports:
- NEP-ALL-2011-04-23 (All new papers)
- NEP-CBE-2011-04-23 (Cognitive & Behavioural Economics)
- NEP-EVO-2011-04-23 (Evolutionary Economics)
- NEP-GTH-2011-04-23 (Game Theory)
- NEP-NET-2011-04-23 (Network Economics)
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