Chapter 4. Concluding Remarks
A.3 Fitness of strategies
A.3.1 Simple Social Norm
A.3.1 Simple Social Norm
Figure A.3.1: The calculation of the expected payoffs of strategies for the Simple Social Norm (GGBG).
According to the rule of game in the simple social norm, there are three strategies
as choice. The agent has chance of being a donor and chance of being a recipient. On one hand, when the agent be a donor, the ratio he meets good (G) recipient is and meets bad (B) recipient is , and may take cooperation (C) action cost , , or 0 cost; On the other hand, when the agent be a recipient, he meets CC, CD, DD players with probabilities , respectively, and is expected to obtain , , or 0 revenue, respectively. So we calculate the expected payoff in CC, CD, DD, respectively. The interpretation form is .
The different expected payoff effect in three strategies is in donor action. The CC donor will always cooperate no matter the recipient whose reputation is good or bad;
The CD donor will cooperate only when the recipient is good, otherwise they will no cooperate and no cost; The DD donor will never donate and no cost.
Due to the asynchronous updating method, the expected payoff of each strategy in each agent is separately calculated. Then we sum up and take average for the total expected payoff each agent in each strategy, respectively. The expected payoff
107
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
calculation way in simple social norm is the same in later weakly augmented social norm and strongly augmented social norm.
The expected payoff of strategy CC is:
The expected payoff of strategy CD is:
The expected payoff of strategy DD is:
To sum up, the expected payoff of all strategies in the simple social norm (GGBG) is:
, , ,
The calculation process is in Appendix 2.1
108
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
A.3.2 Weakly Augmented Norm
In simple social norm, the cooperation (C) strategy has a cooperation cost in donor and cooperation benefit in recipient. The same calculation rule in weakly augmented social norm, the punishment (P) strategy has a punishment cost α in donor and punishment fine β in recipient.
Figure A.3.2: Calculation of the expected revenue of strategies for the Weakly Augmented Social Norm (GGBGBG).
The calculation of the expected revenue of strategies for the weakly augmented
social norm (GGBGBG) in CC, CD, CP and DD strategies are similar with simple social norm but add punishment action. In the payoff tree, the upper branch represents the donor branch and the lower branch represents the recipient branch. The donor branch keeps the same structure but the recipient branch turns to be more options. The lower branches that agents meet CC, CD, CP and DD respectively in CC,
109
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
CD, CP and DD strategies are the same in recipient’s revenue. While the upper branches that agents donate or not are different in donor’s cost. In the lower branch, for the recipient encounters with the CC or DD agents, this reputation is irrelevant, while it matters for the encounter with the CD or CP agents. Expected payoff depends on both the donor’s action and recipient’s reputation in all branches.
The expected payoff CC, CD, CP and DD in weakly augmented social norm (GGBGBG) are summarized as follows:
Substitution previously calculated values of g:
, ,
,
The calculation process is in Appendix 2.2
110
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
A.3.3 Strongly Augmented Norm
In simple social norm, the cooperation (C) strategy has a cooperation cost in donor and cooperation benefit in recipient. The same calculation rule in strongly augmented social norm, the punishment (P) strategy has a punishment cost α in donor and punishment fine β in recipient.
Figure A.3.3: Calculation of the expected revenue of strategies for the Strongly Augmented Social Norm (GGBBBG).
The calculation of the expected revenue of strategies for the weakly augmented
social norm (GGBBBG) in CC, CD, CP and DD strategies are similar with weakly augmented social norm with punishment action addition. In the payoff tree, the upper branch represents the donor branch and the lower branch represents the recipient branch. The donor branch and recipient branch keep the same structure. The lower branches that agents meet CC, CD, CP and DD respectively in CC, CD,
111
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
CP and DD strategies are the same in recipient’s revenue. While the upper branches that agents donate or not are different in donor’s cost. In the lower branch, for the recipient encounters with the CC or DD agents, this reputation is irrelevant, while it matters for the encounter with the CD or CP agents. Expected payoff depends on both the donor’s action and recipient’s reputation in all branches.
The expected payoff CC, CD, CP and DD in strongly augmented social norm (GGBBBG) are summarized as follows:
Substitution previously calculated values of g:
, , , ,
, The calculation process is in Appendix 2.3
112
‧
Tongkui Yu, Shu-heng Chen, Honggang Li, "Social Norm, Costly Punishment and the Evolution to Cooperation," 17th International Conference on Computing in Economics and Finance. 2011
R.N. Mantegna, H.E. Stanley, “An Introduction to Econophysics: Correlations and Complexity in Finance”, Cambridge University Press, Cambridge, 1999.
H.E. Stanley, L.A.N. Amaral, D. Canning, P. Gopikrishnan, Y. Lee , Y. Liu,
“Econophysics: Can physicists contribute to the science of economics?” Center for Polymer Studies, Department of Physics, Boston University, Boston, MA 02215, USA, Harvard Institute for International Development, Harvard University, Cambridge, MA 02138, USA, Received 3 May 1999
Y. Liu, P. Gopikrishnan, P. Cizeau, M. Meyer, C.-K. Peng, H.E. Stanley, Physical Review E 60 (1999) 1390-1400 (1990), “Statistical properties of the volatility of price fluctuations” Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215. Margret and H. A. Rey Laboratory for Nonlinear Dynamics in Medicine, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215. Received 22 February 1999;
published in the issue dated August 1999
W.C. Zhou, H.C. Xu, Z.Y. Cai, J.R. Wei, X.Y. Zhu, W. Wang, L. Zhao, J.P. Huang*,
“Peculiar statistical properties of Chinese stock indices in bull and bear market
113
‧
phases”. Department of Physics and Surface Physics Laboratory (National Key Laboratory), Fudan University, Shanghai, 200433, China, Physica A 388 (2009) 891-899
B.K. Chakrabarti, A. Chakraborti, and A. Chatterjee (Eds.), “Econophysics and Sociophysics: Trends and Perspectives” (Wiley VCH, Berlin, 2006).
B.K. Chakrabarti, A. Chatterjee, and Y. Sudhakar (Eds.), “Econophysics of Wealth Distributions” (Springer, Milan, 2005).
史建平,韓復齡《改革之路:金融證券與中國經濟》China, 2008.
L.A.N. Amaral, P. Cizeau, P. Gopikrishnan, Y. Liu, M. Meyer, C.-K Peng, H.E.
Stanley. “Econophysics: can statistical physics contribute to the science of economics?” Center for Polymer Studies and Department of Physics, Boston University, Boston, MA 02215, USA. Computer Physics Communications 121-122 (1999) 145-152.
W. C. Zhou, H. C. Xu, Z. Y. Cai, J. R. Wei, X. Y. Zhu, W. Wang, L. Zhao, and J. P.
Huang “Peculiar statistical properties of Chinese stock indices in bull and bear market phases ”Physica A volume 388, 891-899 (2009).
C. Ye and J. P. Huang “Non-classical oscillator model for persistent fluctuations in stock markets” Physica A volume 387, 1255 (2008).
Anirban Chakraborti, Ioane Muni Toke, Marco Patriarca, Frederic Abergel
114
‧
“Econophysics: Empirical facts and agent-based models” (Submitted on 10 Sep 2009 (v1), last revised 21 Jun 2010 (this version, v2))
John Von Neumann, and Oskar Morgenstern, “Theory of games and economic behavior”, Princeton, Princeton University Press, 1953.
Wei Wang, Yu Chen, and Jiping Huang, “Heterogeneous preferences, decision-making capacity, and phase transitions in a complex adaptive system”, Fudan University, Shanghai, China, 2009.
Robert Axelrod, The Complexity of Cooperation: Agent-Based Models of Competition and Collaboration, Princeton. Princeton University Press. 1997. ISBN 978-0-691-01567-5
Agent-Based Models of Industrial Ecosystems. Rutgers University, Oct. 2003.
Agent-based modeling: Methods and techniques for simulating human systems.
Proceedings of the National Academy of Sciences. May 2002.
Aoki, M. and Yoshikawa, H. (2012) Non-self-averaging in macroeconomics models:
a criticism of modern micro-founded macroeconomics. Journal of Economic Interaction and Coordination 7(1): 1-22
Ormrod, J.E. (1999). Human learning (3rd ed.). Upper Saddle River, NJ:
Prentice-Hall
115
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Artino, A. R. (2007). Bandura, Ross, and Ross: Observational learning and the Bobo doll. (ERIC Document Reproduction Service No. ED499095)
Landau, Lev Davidovich; and Lifshitz, Evgeny Mikhailovich (1980) [1976].
Statistical Physics 5 (3 ed.). Oxford: Pergamon Press. ISBN 0-7506-3372-7.
---
Andreoni, J., Harbaugh, W., Vesterlund, L., 2003. The carrot or the stick:Rewards, punishments, and cooperation. The American Economic Review93 (3), 893–902.
Axelrod, R., 1984. The Evolution of Cooperation. Basic Books, New York.
Bergstrom, T. C., 2002. Evolution of social behavior: Individual and group selection.
The Journal of Economic Perspectives 16 (2), 67–88.
Bochet, O., Page, T., Putterman, L., 2006. Communication and punishment involuntary contribution experiments. Journal of Economic Behavior and Organization 60 (1), 11–26.
Boehm, C., 1993. Egalitarian behavior and reverse dominance hierarchy. Current Anthropology 34 (3), 227.
Bowles, S., Gintis, H., 2004. The evolution of strong reciprocity: Cooperation in heterogeneous populations. Theoretical Population Biology 65 (1), 17–28.
116
‧
Boyd, R., Gintis, H., Bowles, S., Richerson, P. J., 2003. The evolution of altruistic punishment. Proceedings of the National Academy of Sciences of the United States of America 100 (6), 3531–3535.
Dawid, H., 2007. Evolutionary game dynamics and the analysis of agent-based imitation models: The long run, the medium run and the importance of global analysis.
Journal of Economic Dynamics and Control 31 (6), 2108–2133.
de Quervain, D. J.-F., Fischbacher, U., Treyer, V., Schellhammer, M., Schnyder, U., Buck, A., Fehr, E., 2004. The neural basis of altruistic punishment. Science 305 (5688), 1254–1258.
Dreber, A., Rand, D. G., Fudenberg, D., Nowak, M. A., 2008. Winners don’t punish.
Nature 452 (7185), 348–351.
Egas, M., Riedl, A., 2008. The economics of altruistic punishment and the maintenance of cooperation. Proceedings of the Royal Society B: Biological Sciences 275 (1637), 871–878.
Falk, A., Fehr, E., Fischbacher, U., 2005. Driving forces behind informal sanctions.
Econometrica 73 (6), 2017–2030.
Fehr, E., Fischbacher, U., 2003. The nature of human altruism. Nature425 (6960), 785–791.
Fehr, E., Fischbacher, U., 2004. Social norms and human cooperation. Trends in Cognitive Sciences 8 (4), 185–190.
117
‧
Fehr, E., Fischbacher, U., Gachter, S., 2002. Strong reciprocity, human cooperation, and the enforcement of social norms. Human Nature 13 (1), 1–25.
Fehr, E., Gachter, S., 2002. Altruistic punishment in humans. Nature415 (6868), 137–
140.
Fehr, E., Simon, G., 2000. Cooperation and punishment in public goods experiments.
The American Economic Review 90 (4), 980–994.
Fowler, J. H., 2005. Altruistic punishment and the origin of cooperation. Proceedings of the National Academy of Sciences of the United States of America 102 (19), 7047–
7049.
Gachter, S., Herrmann, B., 2009. Reciprocity, culture and human cooperation:
previous insights and a new cross-cultural experiment. Philosophical Transactions of the Royal Society B: Biological Sciences 364 (1518), 791–806.
Gintis, H., 2000. Strong reciprocity and human sociality. Journal of Theoretical Biology 206 (2), 169–179.
Gurerk, O., Irlenbusch, B., Rockenbach, B., 2006. The competitive advantage of sanctioning institutions. Science 312 (5770), 108–111.
Henrich, J., 2004. Cultural group selection, coevolutionary processes and large-scale cooperation. Journal of Economic Behavior and Organization53 (1), 3–35.
118
‧
Henrich, J., 2006. Cooperation, punishment, and the evolution of human institutions.
Science 312 (5770), 60–61.
Henrich, J., Boyd, R., 2001. Why people punish defectors: Weak conformist transmission can stabilize costly enforcement of norms in cooperative dilemmas.
Journal of Theoretical Biology 208 (1), 79–89, doi: DOI:10.1006/jtbi.2000.2202.
Henrich, J., Boyd, R., Bowles, S., Camerer, C., Fehr, E., Gintis, H., McElreath, R., Alvard, M., Barr, A., Ensminger, J., Henrich, N. S., Hill, K.,Gil-White, F., Gurven, M., Marlowe, F. W., Patton, J. Q., Tracer, D.,2005. “Economic man” in cross-cultural perspective: Behavioral experimentsin 15 small-scale societies. Behavioral and Brain Sciences 28 (06),795–815.
Henrich, J., Ensminger, J., McElreath, R., Barr, A., Barrett, C., Bolyanatz, A., Cardenas, J. C., Gurven, M., Gwako, E., Henrich, N., Lesorogol, C., Marlowe, F., Tracer, D., Ziker, J., 2010. Markets, religion, communitysize, and the evolution of fairness and punishment. Science 327 (5972),1480–1484.
Henrich, J., McElreath, R., Barr, A., Ensminger, J., Barrett, C., Bolyanatz,A., Cardenas, J. C., Gurven, M., Gwako, E., Henrich, N., Lesorogol, C., Marlowe, F., Tracer, D., Ziker, J., 2006. Costly punishment across humansocieties. Science 312 (5781), 1767–1770.
Herrmann, B., Thoeni, C., Gachter, S., 2008. Antisocial punishment across societies.
Science 319, 1362–1367.
119
‧
Hofbauer, J., Sigmund, K., 1998. Evolutionary Games and Population Dynamics.
Cambridge University Press, Cambridge.
Knauft, B. M., Abler, T. S., Betzig, L., Boehm, C., Dentan, R. K., Kiefer, T. M., Otterbein, K. F., Paddock, J., Rodseth, L., 1991. Violence and sociality in human evolution [and comments and replies]. Current Anthropology32 (4), 391–428.
Marlowe, F. W., Berbesque, J. C., Barr, A., Barrett, C., Bolyanatz, A., Cardenas,J. C., Ensminger, J., Gurven, M., Gwako, E., Henrich, J., Henrich,N., Lesorogol, C., McElreath, R., Tracer, D., 2008. More ”altruistic” punishment in larger societies.
Proceedings of the Royal Society B: Biological Sciences 275 (1634), 587–592.
Milinski, M., Rockenbach, B., 2008. Punisher pays. Nature 452 (7185), 297–298.
Nowak, M. A., 2006. Five rules for the evolution of cooperation. Science314 (5805), 1560–1563.
Nowak, M. A., Sigmund, K., 2005. Evolution of indirect reciprocity. Nature437 (7063), 1291–1298.
Ohtsuki, H., Iwasa, Y., 2007. Global analyses of evolutionary dynamics and exhaustive search for social norms that maintain cooperation by reputation. Journal of Theoretical Biology 244 (3), 518–531.
Ohtsuki, H., Iwasa, Y., Nowak, M. A., 2009. Indirect reciprocity provides only a narrow margin of efficiency for costly punishment. Nature 457 (7225),79–82.
120
‧
Olson, M., 1965. The Logic of Collective Action: Public Goods and te Theory of Groups. Harvard University Press, Cambridge, MA.
Oosterbeek, H., Sloof, R., van de Kuilen, G., 2004. Cultural differences in ultimatum game experiments: Evidence from a meta-analysis. Experimental Economics 7 (2), 171–188.
Ostrom, E., 2000. Collective action and the evolution of social norms. The Journal of Economic Perspectives 14 (3), 137–158.
Ostrom, E., Walker, J., Gardner, R., 1992. Covenants with and without as word:
Self-governance is possible. The American Political Science Review86 (2), 404–417.
Rockenbach, B., Milinski, M., 2006. The efficient interaction of indirect reciprocity and costly punishment. Nature 444 (7120), 718–723.
Singer, T., Seymour, B., O’Doherty, J. P., Stephan, K. E., Dolan, R. J., Frith, C. D., 2006. Empathic neural responses are modulated by the perceived fairness of others.
Nature 439 (7075), 466–469.
Taylor, C., Nowak, M. A., 2007. Transforming the dilemma. Evolution61 (10), 2281–
2292.
Tesfatsion, L., 2001. Introduction to the special issue on agent-based computational economics. Journal of Economic Dynamics and Control 25 (3-4), 281–293.
121
‧
國立 政 治 大 學
‧
N a tio na
l C h engchi U ni ve rs it y
Wu, J.-J., Zhang, B.-Y., Zhou, Z.-X., He, Q.-Q., Zheng, X.-D., Cressman, R.,Tao, Y., 2009. Costly punishment does not always increase cooperation. Proceedings of the National Academy of Sciences 106 (41), 17448–17451.
Young, H. P., 2008. Social Norms. Palgrave Macmillan, Basingstoke.
122