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The effect of adding a constant to all payoffs: experimental investigation, and implications for reinforcement learning models

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  1. Filipe Costa Souza & Leandro Chaves Rêgo, 2014. "Mixed Equilibrium, Collaborative Dominance and Burning Money: An Experimental Study," Group Decision and Negotiation, Springer, vol. 23(3), pages 377-400, May.
  2. Martin G. Kocher & Matthias Sutter, 2005. "The Decision Maker Matters: Individual Versus Group Behaviour in Experimental Beauty-Contest Games," Economic Journal, Royal Economic Society, vol. 115(500), pages 200-223, January.
  3. Erev, Ido & Roth, Alvin E. & Slonim, Robert L. & Barron, Greg, 2002. "Predictive value and the usefulness of game theoretic models," International Journal of Forecasting, Elsevier, vol. 18(3), pages 359-368.
  4. Ido Erev & Eyal Ert & Alvin E. Roth, 2010. "A Choice Prediction Competition for Market Entry Games: An Introduction," Games, MDPI, vol. 1(2), pages 1-20, May.
  5. Yoella Bereby-Meyer & Alvin E. Roth, 2006. "The Speed of Learning in Noisy Games: Partial Reinforcement and the Sustainability of Cooperation," American Economic Review, American Economic Association, vol. 96(4), pages 1029-1042, September.
  6. Oyarzun, Carlos & Sarin, Rajiv, 2012. "Mean and variance responsive learning," Games and Economic Behavior, Elsevier, vol. 75(2), pages 855-866.
  7. Fernando Lozano & Jaime Lozano & Mario García, 2007. "An artificial economy based on reinforcement learning and agent based modeling," Documentos de Trabajo 3907, Universidad del Rosario.
  8. Duffy, John, 2006. "Agent-Based Models and Human Subject Experiments," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 19, pages 949-1011, Elsevier.
  9. Andreas Flache & Michael W. Macy, 2002. "Stochastic Collusion and the Power Law of Learning," Journal of Conflict Resolution, Peace Science Society (International), vol. 46(5), pages 629-653, October.
  10. Feltovich, Nick & Iwasaki, Atsushi & Oda, Sobei H., 2010. "Payoff levels, loss avoidance, and equilibrium selection in the Stag Hunt: an experimental study," SIRE Discussion Papers 2010-125, Scottish Institute for Research in Economics (SIRE).
  11. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," Papers 2202.05947, arXiv.org.
  12. Eldad Yechiam & Amitay Kauffmann & Nathaniel J S Ashby & Gal Zahavi, 2017. "On the relation between economic bubbles and effort gaps between sellers and buyers: An experimental study," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-15, December.
  13. Lefebvre, Germain & Nioche, Aurélien & Bourgeois-Gironde, Sacha & Palminteri, Stefano, 2018. "An Empirical Investigation of the Emergence of Money: Contrasting Temporal Difference and Opportunity Cost Reinforcement Learning," MPRA Paper 85586, University Library of Munich, Germany.
  14. Nick Feltovich, 2011. "The Effect of Subtracting a Constant from all Payoffs in a Hawk‐Dove Game: Experimental Evidence of Loss Aversion in Strategic Behavior," Southern Economic Journal, John Wiley & Sons, vol. 77(4), pages 814-826, April.
  15. Mitropoulos, Atanasios, 2001. "Learning under minimal information: An experiment on mutual fate control," Journal of Economic Psychology, Elsevier, vol. 22(4), pages 523-557, August.
  16. Faison P. Gibson, 2002. "Is It Better to Forget? Stimulus-Response, Prediction, and the Weight of Past Experience in a Fast-Paced Bargaining Task," Computational and Mathematical Organization Theory, Springer, vol. 8(1), pages 31-47, May.
  17. Haruvy, Ernan & Prasad, Ashutosh, 2005. "Freeware as a competitive deterrent," Information Economics and Policy, Elsevier, vol. 17(4), pages 513-534, October.
  18. Shaun Hargreaves-Heap & Yanis Varoufakis, 2002. "Some Experimental Evidence On The Evolution Of Discrimination, Co--Operation And Perceptions Of Fairness," Economic Journal, Royal Economic Society, vol. 112(481), pages 679-703, July.
  19. Walter Gutjahr, 2006. "Interaction dynamics of two reinforcement learners," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 14(1), pages 59-86, February.
  20. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Gotts, Nicholas M. & Polhill, J. Gary, 2007. "Transient and asymptotic dynamics of reinforcement learning in games," Games and Economic Behavior, Elsevier, vol. 61(2), pages 259-276, November.
  21. Todd Guilfoos & Andreas Pape, 2016. "Predicting human cooperation in the Prisoner’s Dilemma using case-based decision theory," Theory and Decision, Springer, vol. 80(1), pages 1-32, January.
  22. Enrique Fatás & Francisca Jiménez & Antonio Morales, 2011. "Controlling for initial endowment and experience in binary choice tasks," Journal of Risk and Uncertainty, Springer, vol. 43(3), pages 227-243, December.
  23. Ido Erev & Alvin Roth & Robert Slonim & Greg Barron, 2007. "Learning and equilibrium as useful approximations: Accuracy of prediction on randomly selected constant sum games," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 33(1), pages 29-51, October.
  24. W Chen & Y Chen & D Levine, 2015. "A Unifying Learning Framework for Building Artificial Game-Playing Agents," Levine's Working Paper Archive 786969000000001002, David K. Levine.
  25. Yechiam, Eldad & Busemeyer, Jerome R., 2008. "Evaluating generalizability and parameter consistency in learning models," Games and Economic Behavior, Elsevier, vol. 63(1), pages 370-394, May.
  26. Atanasios Mitropoulos, 2001. "On the Measurement of the Predictive Success of Learning Theories in Repeated Games," Experimental 0110001, University Library of Munich, Germany.
  27. Segismundo S. Izquierdo & Luis R. Izquierdo & Nicholas M. Gotts, 2008. "Reinforcement Learning Dynamics in Social Dilemmas," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 11(2), pages 1-1.
  28. Martino Banchio & Giacomo Mantegazza, 2022. "Artificial Intelligence and Spontaneous Collusion," Papers 2202.05946, arXiv.org, revised Sep 2023.
  29. Katherine Burson & David Faro & Yuval Rottenstreich, 2013. "Multiple-Unit Holdings Yield Attenuated Endowment Effects," Management Science, INFORMS, vol. 59(3), pages 545-555, November.
  30. Roth, Alvin E. & Herzog, Stefan & Hau, Robin & Hertwig, Ralph & Erev, Ido & Ert, Eyal & Haruvy, Ernan & Stewart, Terrence & West, Robert & Lebiere, Christian, 2009. "A Choice Prediction Competition: Choices From Experience and From Description," Scholarly Articles 5343169, Harvard University Department of Economics.
  31. Martino Banchio & Andrzej Skrzypacz, 2022. "Artificial Intelligence and Auction Design," NBER Chapters, in: Economics of Artificial Intelligence, National Bureau of Economic Research, Inc.
  32. Anufriev, M. & Tuinstra, J. & Bao, T., 2013. "Fund Choice Behavior and Estimation of Switching Models: An Experiment," CeNDEF Working Papers 13-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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