Deliberation-Aware Responder in Multi-proposer Ultimatum Game

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• 关键词：Deliberation effort ; Markov decision process ; Ultimatum game
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9886
• 期：1
• 页码：230-237
• 全文大小：256 KB
• 参考文献：1.Puterman, M.L.: Markov Decision Processes. Wiley, New Jersey (1994)CrossRef MATH
  2.Rubinstein, A.: Perfect equilibrum in a bargaining model. Econometrica 50(1), 97–109 (1982). Wiley, 1994MathSciNet CrossRef MATH
  3.Sulkin, T., Simon, A.F.: Habermas in the lab: a study of deliberation in an experimental setting. Polit. Psychol. 22, 809–826 (2001)CrossRef
  4.Persson, M., Esaiasson, P., Gilljam, M.: The effects of direct voting, deliberation on legitimacy beliefs: an experimental study of small group decision making. Eur. Polit. Sci. Rev., 1–19 (2006)
  5.Beara, A., Randa, D.G.: Intuition, deliberation, and the evolution of cooperation. PNAS 113(4), 936–941 (2016)CrossRef
  6.Loewenstein, G., O’Donoghue, T.: Animal spirits: affective and deliberative processes in economic behavior (2004). http://​papers.​ssrn.​com
  7.Compte, O., Jehiel, P.: Bargaining over Randomly Generated Offers: A new perspective on multi-party bargaining. C.E.R.A.S.-E.N.P.C., C.N.R.S., France (2004)
  8.Ortega, D.A., Braun, P.A.: Information, utility and bounded rationality. In: Schmidhuber, J., Thórisson, K.R., Looks, M. (eds.) AGI 2011. LNCS, vol. 6830, pp. 269–274. Springer, Heidelberg (2011)CrossRef
  9.Horvitz, E.J.: Reasoning about beliefs, actions under computational resource constraints (2013). arXiv:​1304.​2759
  10.Dignum, F., Dignum, V., Prada, R., Jonker, C.M.: A conceptual architecture for social deliberation in multi-agent organizations. Multiagent Grid Syst. 11(3), 147–166 (2015)CrossRef
  11.Gigerenzer, G.: Adaptative Thinking: Rationality in the Real World. Oxford University Press, Oxford (2000)
  12.Bellman, R.: Dynamic programming. Princeton University Press, Princeton (1957)MATH
  13.F. Hůla, Ruman, M., Kárný, M.: Adaptive proposer for ultimatum game. In: Proceedings of ICANN 2016 (2016)
  
• 作者单位：Marko Ruman (16)
  František Hůla (16)
  Miroslav Kárný (16)
  Tatiana V. Guy (16)
  
  16. Department of Adaptive Systems, Institute of Information Theory and Automation, Czech Academy of Sciences, P.O. Box 18, 182 08, Prague, Czech Republic
  
• 丛书名：Artificial Neural Networks and Machine Learning – ICANN 2016
• ISBN：978-3-319-44778-0
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9886

文摘

The article studies deliberation aspects by modelling a responder in multi-proposers ultimatum game (UG). Compared to the classical UG, deliberative multi-proposers UG suggests that at each round the responder selects the proposer to play with. Any change of the proposer (compared to the previous round) is penalised. The simulation results show that though switching of proposers incurred non-negligible deliberation costs, the economic profit of the deliberation-aware responder was significantly higher in multi-proposer UG compared to the classical UG.