1.1 Karplus, W. J.; “The spectrum of mathematical modeling and system simulation, Mathematics and Computers in Simulation “19 (1), 3–10, 1977.
1.2 Rechtin, E., and Maier, M. W.; “The Art of Systems Architecting.” CRC Press,2010, UK,
1.3 Strogatz, S. H.; “Exploring complex networks, Nature,”410(6825),268-276.2001.
1.4 Turcotte, D. L.; “Modeling geocomplexity: A new kind of science.” Geological Society of America Special Papers, 413,39-50. 2006.
1.5 Straughan, R., and Roberts, J.; “Environmental Segmentation Alternatives: A Look at Green Consumer Behavior in the New Millennium.” Journal of Consumer Marketing, 16, 558-575,1999.
1.6 Weibull, J. W.; “Evolutionary game theory,” Cambridge: MIT Press, 1995.
1.7 Neumann, J. V. and Morgenstern, O.; “Theory of games and economic behavior,” Princeton University Press,1994, USA.
1.8 Smith, J. M.; “Evolution and the theory of games.” Cambridge University Press,1982, USA.
1.9 Nowak, M. A.;” Evolutionary Dynamics: Exploring the equations of life.” Harvard University Press, 2006, USA.
1.10 Academy, N.;” Equilibrium Points in n-Person Games.” Proc. Natl. Acad. Sci. United States Am. 36, 48–49, 1950, USA.
1.11 Schmidt, C.; “Game Theory and Economic Analysis: A quiet revolution in economics,” 1995.
1.12 Neumann, J. V.; “On the Theory of Games of Strategy. In Tucker,” Contributions to the Theory of Games. 4, 13–42,1959 (ISBN 0691079374).
1.13 Shubik, M., Arrow, K., and Micheal, “Game Theory Models and Methods in Political Economy,” Handbook of Mathematical Economics, 1. 1,285–330,1981.
1.14 Hofbauer, J., and Sigmund, K. “Evolutionary Games and Population Dynamics” Cambridge University Press, USA, 1998. doi:10.1017/CBO9781139173179.
1.15 Neumann, J. V. and Morgenstern, O.; “Theory of games and economic behavior, “Princeton University Press, Princeton, 1944.
1.16 Gintis, H.; “Classical versus evolutionary game theory.” J. Conscious. Stud. 1–2, 300– 304,2000.
1.17 Traulsen, A., Semmann, D., Sommerfeld, RD., Krambeck, HJ., and Milinskib, M.;” Human strategy updating in evolutionary games. “Proc. Natl. Acad. Sci. U. S. A. 107, 2962–2966,2010.
1.18 Tanimoto, J.;” Evolutionary Games with Socio-physics Analysis of Traffic Flow and Epidemics.” Springer, 2018.
1.19 Haake, C-J., Kashiwada, A., and Su, F.E.;” The shapely value of phylogenetic trees,” working papers, Bielefeld University, Institute of Mathematical Economics, 2005.
1.20 Pintassilgo, P.; "The New Member Problem in the Cooperative Management of the Northern Atlantic Bluefin Tuna", FEUNL Working Paper Series, Universidade Nova de Lisboa, Faculdade de Economia,2000.
1.21 Littlechild, S. C., and Thompson, G. D.; “Aircraft Landing Fees: A Game Theory Approach,” The Bell Journal of Economics and Management Science 8, 186-204 ,1977.
1.22 Brown, L., and Shoham, Y.; “Essentials of game theory,”10–11, Morgan and Claypool, first edition, 2000.
1.23 Tanimoto, J.; “Fundamental of Evolutionary Game Theory and its Applications,” Springer, 2015.
1.24 Tanimoto, J.; “Evolutionary Games with Sociophysics,” Springer, 2018.
1.25 Smith, J. M.;” Evolution and the theory of the games” Cambridge University Press,1982.
1.26 Smith, J. M., and Hofbauer, J.;” The battle of the sexes: a genetic model with limit cycle behavior” Theoretical Population Biology, 32 (1), 1-14 (1987).
1.27 Selten, R.;” A note on evolutionary stable strategies in asymmetric animal conflicts.” Journal of Theoretical Biology, 84(1), 93-101(1980).
1.28 Hauert, C. , Saade, C., and McAvoy, A.; “Asymmetric evolutionary games with environmental Feedback, ”Journal of Theoretical Biology ,462, 347-360(2019).
1.29 Wang, Y. , and Wang, F.; “Evolutionary Game Analysis on Production and Emissions Reduction of Manufacturing Enterprises under Different Carbon Policies,” IOP Conf. Ser. Earth Environ. Sci., 199(2), (2018).
1.30 García Mazo, C. M., Olaya, Y., and Botero Botero, S.; “Investment in renewable energy considering game theory and wind-hydro diversification,” Energy Strateg. Rev., 28, 100447(2020).
1.31 Neumann, J. V., Morgenstern, O., and Rubinstein, A.; “Theory of Games and Economic Behavior “(60th Anniversary Commemorative Edition),Princeton, Oxford: Princeton University,1944.
1.32 Smith, J. M., and Price, G. R.; “The logic of animal conflicts,” Nature, 246,15-18, 1973.
1.33 Nowak, M. A., and Sigmund, K.; “Evolutionary Dynamics of Biological Games.” Science (80). 303, 793–799.2004. (doi:10.1126/science.1093411)
1.34 Turner, PE., and Chao, L.; “Prisoner’s dilemma in an RNA virus.” Nature 398, 441–443,1999. (doi:10.1038/18913)
1.35 Rainey, PB., and Rainey, K.; “Evolution of cooperation and conflict in experimental bacterial populations.” Nature 425, 72–74,2003. (doi:10.1038/nature01906)
1.36 Bendort, J., and Swistakt, P.; “Types of evolutionary stability.” Evolution (N. Y). 92, 3596– 3600,1995.
1.37 Taylor, PD., and Jonker, LB.; “Evolutionarily stable strategies and game dynamics.” Math. Biosci. 40, 145–156,1978. (doi:10.1007/BF00277103)
1.38 Nowak, M. A. and Sigmund, K.; “Evolutionary dynamics of biological games,” science 303, 793799, 2004.
1.39 Tanimoto, J.; “Evolutionary Games with Sociophysics: Analysis of Traffic Flow and Epidemics,” Springer, 2019.
1.40 Nowak, M. A., and May, R. M.; “Evolutionary games and spatial chaos,” Letters to Nature, 359, 826–829,1992.
1.41 Roca, CP., Cuesta, JA., and Sánchez, A.; “Evolutionary game theory: Temporal and spatial effects beyond replicator dynamics.” Phys. Life Rev. 6, 208–249. 2009.(doi: 10.1016/j.plrev.2009.08.001)
1.42 Dorogovtsev, S. N. J.; “Evolution of Networks - From Biological Nets to the Internet and WWW.”2003
1.43 Barabasi, A.; “Network Science: The Scale-free property.”2016.
1.44 Watts, DJ., and Strogatz, SH.; “small world network” Nature, 393, 440–442,1998.
1.45 Cliff, O., Sintchenko, V., Sorrell, TC., Vadlamudi, K., McLean, N. and Prokopenko, M.; “Network properties of salmonella epidemics.” Sci. Rep. 9, 1–6,2019. (doi:10.1038/s41598-019- 42582-3)
1.46 Grilo, C.F.A., and Correia, L.; “Asynchronous stochastic dynamics and the spatial prisoner’s dilemma game.”13th Portuguese Conference on Artificial Intelligence, EPIA 2007. [S.l.]: Springer, 235-246,2007.
1.47 Romano, A. & Balliet, D.; “Reciprocity Outperforms Conformity to Promote Cooperation,” Psychol. Sci. 28, 1490–1502 (2017).
1.48 Richerson, P., Baldini, R., Bell, A., Demps, K., Frost, K., Hillis, V., Zefferman, M.; “Cultural group selection plays an essential role in explaining human cooperation: A sketch of the evidence.” Behavioral & Brain Sciences, 39, e30(2015). doi:10.1017/S0140525X1400106X.
1.49 Asch, S. E.; “Studies of independence and conformity: I. A minority of one against a unanimous majority.” Psychological Monographs: General and Applied, 70, 1–70 (1956). doi:10.1037/h0093718
2.1 Axelrod, R. , and Hamilton, W. D.; “The Evolution of Cooperation,” Evolution (N.Y)., 211 (4489) 1390–1396 (1981).
2.2 Neumann, J.V., and Morgenstern, O.; “Theory of games and economic behavior, ” Princeton University Press, 1953.
2.3 Nowak, M.A., and Coakle, S.; ''Evolution, Games, and God: The Principle of Cooperation,''. Harvard University Press, 2013.
2.4 Tanimoto, J.;''Fundamentals of Evolutionary Game Theory and its Applications,'' Springer, 2015.
2.5 Tanimoto, J.; ''Evolutionary Games with Sociophysics ,'' Springer, 2018.
2.6 Fujisaki, T.; "Evaluation of Green Paradox:Case Study of Japan,"Evergreen.,5(4) 26- 31(2018).
2.7 Dugatkin, L.A. ; “Cooperation in animals: An evolutionary overview.” Biology & Philosophy ,17 459–476 (2002). https://doi.org/10.1023/A:1020573415343.
2.8 Jacobs, G. M.; “Cooperation among animals. “IASCE Newsletter, 36(2), 5-7(2017).
2.9 Cornwallis, C. K.; “Cooperative breeding and the evolutionary coexistence of helper and nonhelper strategies,” Proc. Natl. Acad. Sci. U. S. A., 115( 8) 1684–1686( 2018). doi: 10.1073/pnas.1722395115.
2.10Cheney, D. L. ;“Extent and limits of cooperation in animals,” Proc. Natl. Acad. Sci. U. S. A., 108( 2) 10902–10909( 2011). doi: 10.1073/pnas.1100291108.
2.11Koenig, W. D.; “What drives cooperative breeding?,” PLoS Biol., 15 (6) 1–6(2017). doi: 10.1371/journal.pbio.2002965.
2.12Riehl, C.; “Evolutionary routes to non-kin cooperative breeding in birds,” Proc. R. Soc. B Biol. Sci., 280(1772) 2013. doi: 10.1098/rspb.2013.2245.
2.13 Robinson, E. J. H.; and Barker, J. L.; “Inter-group cooperation in humans and other animals,” Biol. Lett., 13(3) 2017. doi: 10.1098/rsbl.2016.0793.
2.14 Mcauliffe, K., and Thornton, A. ; “The psychology of cooperation in animals: An ecological approach,” J. Zool., 295( 1), 23–35( 2015). doi: 10.1111/jzo.12204.
2.15Peyraud, R., Mbengue, M., Barbacci, A., and Raffaele, S. ; “Intercellular cooperation in a fungal plant pathogen facilitates host colonization,” Proc. Natl. Acad. Sci. U. S. A. 116, 3193–3201 (2019).
2.16Wintermute, E. H. & Silver, P. A.; “Emergent cooperation in microbial metabolism. “Mol. Syst. Biol. 6 1–7 (2010).
2.17Xavier, J. B., & Foster, K. R.; “Cooperation and conflict in microbial biofilms. ”Proc. Natl. Acad. Sci. U. S. A. 104 876–881 (2007).
2.18Yurtsev, E. A., Chao, H. X.Datta, M. S. , Artemova, T., & Gore, J.; “Bacterial cheating drives the population dynamics of cooperative antibiotic resistance plasmids.” Mol. Syst. Biol. 9, 1–7 (2013).
2.19Wilson, C. E., et al.” Cooperation and competition shape ecological resistance during periodic spatial disturbance of engineered bacteria.” Sci. Rep. 7, 1–13 (2017).
2.20Haaijer, SC. ; “Induced cooperation between marine nitrifiers and anaerobic ammoniumoxidizing bacteria by incremental exposure to oxygen. “Syst Appl Microbiol. 33(7) 407-15 (2010). doi: 10.1016/j.syapm.2010.08.003. Epub 2010 Oct 16. PMID: 20956064.
2.21Heuer, L. and Orland, A.; “Cooperation in the Prisoner’s Dilemma: an experimental comparison between pure and mixed strategies,” R. Soc. Open Sci., 6 (7) 182142, (2019).
2.22Capraro, V., Jordan, J. J. , and Rand, D. G.; “Heuristics guide the implementation of social preferences in one-shot Prisoner’s Dilemma experiments,” Sci. Rep., 4 1-5 (2014).
2.23F. Exadaktylos, Espín, A. M., and Brañas-Garza, P. ; “Experimental subjects are not different,” Sci. Rep., 3 (1213) 1–6 (2013).
2.24Antonioni, A., Tomassini, M., and Sánchez, A. “Short-range mobility and the evolution of cooperation: An experimental study,” Sci. Rep., 5 (10282) 1–9 (2015).
2.25 Fort, H ., and Viola, S.''Self-organizationina simple model of adaptive agents playing 2 × 2 games with arbitrary payoff matrices.'' Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 69 (036110) 1-16 (2004).
2.26 Grujic, J. , Fosco, C. , Araujo, L., Cuesta, J. A., and Sanchez, A.; “Social experiments in the mesoscale: Humans playing a spatial prisoner’s dilemma,” PLoS One, 5 (11) (2010).
2.27 Normann, H. T., and Wallace, B.; “The impact of the termination rule on cooperation in a prisoner’s dilemma experiment,” Int. J. Game Theory, 41 ( 3)707–718 (2012).
2.28Hauert, C. H. ; “Effects of space in 2 × 2 games,'' 12(7) 1531–1548 (2002).
2.29 Keil, J. , et al.; “Getting less than their fair share: Maltreated youth are hyper-cooperative yet vulnerable to exploitation in a public goods game,” Dev. Sci.,22 (3) 1–13 (2019).
2.30 Blake, P. R., Rand, D. G., Tingley, D., and Warneken, F.; “The shadow of the future promotes cooperation in a repeated prisoner's dilemma for children,” Sci. Rep., 5 (14559) 1–9 ( 2015).
2.31 Qi, H., Ma, S. Jia, N., and Wang, G.;'' Experiments on individual strategy updating in iterated snowdrift game under random rematching,'' J. Theor. Biol.,368 1-12 (2015).
2.32 Chen, Q., Chen, T. and Yang, R.; “Using rewards reasonably: The effects of stratifiedrewards in public goods game,” Chaos, Solitons and Fractals,120 67–74 (2019).
2.33 Pereda, M., Capraro, V., and Sánchez, A.; “Group size effects and critical mass in public goods games,” Sci. Rep., 9 (5503) 1–10 (2019).
2.34 Kimmel, G. J., Gerlee, P. Brown, J. S., and Altrock, P. M.; “Neighborhood size-effects in nonlinear public goods games,”2 (53) 1–25,( 2019).
2.35 Wang, Q., and Chen, X.; “Stochastically stable equilibria in the nonlinear public goods game,” Phys. D Nonlinear Phenom., 388 33–39 (2019).
2.36 González, L. G., Güth, W. , and Levati, M. V.; “When does the game end? Public goods experiments with non-definite and non-commonly known time horizons,” Econ. Lett., 88 ( 2) 221–226 (2005).
2.37 Suri, S. , and Watts, D. J.;“Cooperation and contagion in web-based, networked public goods experiments,” PLoS One, 6 (3) 1-18 ( 2011).
2.38Milinski, M., and Semmann, D. ;“Stabilizing the Earth ’ s climate is not a losing game :supporting evidence from public goods experiments,” Proceedings of the National Academy of Sciencess, 103(11) 3994-3998 (2006)
2.39Horita, Y. Takezawa, M., Inukai, K., Kita, T., and Masuda, N.; “Reinforcement learning accounts for moody conditional cooperation behavior: experimental results,” Sci. Rep., 7 (39275) 1–10 (2017).
2.40Quan, J., Zheng, J. Wang, X. and Yang, X. “Benefits of asynchronous exclusion for the evolution of cooperation in stochastic evolutionary optional public goods games,” Sci. Rep., 9 (1)1–11 (2019).
2.41 Shi, D.-M., Zhuang, Y.,and Wang, B.-H.;“Group diversity promotes cooperation in the spatial public goods game,” EPL (Europhysics Lett., 90 (5) 58003 (2010).
2.42 Nash, J. F., Nagel, R., Ockenfels, A., and Selten, R. ; “The agencies method for coalition formation in experimental games,” Proc. Natl. Acad. Sci. U. S. A., 109 (50) 20358–20363 (2012)
2.43 Grujić, J. , Eke, B. Cabrales, A., Cuesta, J. A., and Sánchez, A. ;“Three is a crowd in iterated prisoner’s dilemmas: Experimental evidence on reciprocal behavior,” Sci. Rep., 2 (638) 1–7 (2012).
2.44 J. Keil, A.Michel, F.sticca, K.Leipold, A.Klein, S.Sierau, Klitzing, K.V. and White , L.O.; “The Pizzagame: A virtual public goods game to assess cooperative behavior in children and adolescents,” Behav. Res. Methods, 49 (4) 1432–1443 (2017).
2.45Harbaugh, W. T., and Krause, K.; “Children’s altruism in public good and dictator experiments,” Econ. Inq., 38 (1) 95–109 (2000).
2.46Brocas, I. , & Carrillo, J. D.; ” Iterative dominance in young children: Experimental evidence in simple two-person games.” J. Econ. Behav. Organ. 179, 623–637 (2020).
2.47Vogelsang, M., Jensen, K., Kirschner, S., Tennie, C., and Tomasello, M., “Preschoolers are sensitive to free riding in a public goods game,” Front. Psychol., 5 (729) 1-9 (2014).
2.48Ruipérez-Valiente, J. A., & Kim, Y. J.; “ Effects of solo vs. collaborative play in a digital learning game on geometry: Results from a K12 experiment.” Comput. Educ. 159, (2020).
2.49 Zelmer, J. ; “Linear public goods experiments: A meta-analysis,” Exp. Econ.,6 ( 3) 299– 310 ( 2003).
2.50Fréchette, G. R.; “Experimental economics across subject populations,” Handb. Exp. Econ. 2 1–70(2016).
2.51Wang, Y., Chen, X. and Wang, Z.; “Testability of evolutionary game dynamics based on experimental economics data,” Phys. A Stat. Mech. its Appl. 486, 455–464 (2017).
2.52Hagen, E. H., and Hammerstein, P. ;“Game theory and human evolution: A critique of some recent interpretations of experimental games,” Theor. Popul. Biol. 69, 339–348 (2006).
2.53 Liu, T. X., Bednar, J., Chen, Y., and Page, S.; “Directional behavioral spillover and cognitive load effects in multiple repeated games,” Exp. Econ., 22 (3) 705–734 (2019).
2.54Kayaba, Y., Matsushima, H., and Toyama, T.; “Accuracy and retaliation in repeated games with imperfect private monitoring: Experiments,” Games Econ. Behav.,120 193–208(2020).
2.55Jones, G.; “Are smarter groups more cooperative? Evidence from prisoner’s dilemma experiments, 1959-2003,” J. Econ. Behav. Organ., 68 (3–4) 489–497(2008).
2.56Grujić, J. ,& Lenaerts, T.;” Do people imitate when making decisions? Evidence from a spatial Prisoner’s Dilemma experiment.” R. Soc. Open Sci. 7,200618 (2020).
2.57Berger, U.; “Co-action equilibrium fails to predict choices in mixed-strategy settings,” Sci. Rep. 8, 6–10 (2018).
2.58Han, X. et al., “Equal status in Ultimatum Games promotes rational sharing,” Sci. Rep. 8, 1–9 (2018).
2.59Antonioni, A., Pereda, M., Cronin, K. A., Tomassini, M., and Sánchez, A. “Collaborative hierarchy maintains cooperation in asymmetric games,” Sci. Rep. 8, 1–9 (2018).
2.60Gallo, E., Riyanto, Y. E., Teh, T. H., and Roy, N.;s “Strong links promote the emergence of cooperative elites,” Sci. Rep. 9, 1–10 (2019).
2.61Capraro, V. ; “The emergence of hyper-altruistic behaviour in conflictual situations,” Sci. Rep. 4, 1–7 (2015).
2.62Horita, Y., Takezawa, M., Inukai, K., Kita, T., and Masuda, N.; “Reinforcement learning accounts for moody conditional cooperation behavior: experimental results,” Sci. Rep. 7, 1–10 (2017).
2.63Hillenbrand, A. , and Winter, F. ; “Volunteering under population uncertainty,” Games Econ. Behav. 109, 65–81 (2018).
2.64Jackson, J. C., et al., “Synchrony and Physiological Arousal Increase Cohesion and Cooperation in Large Naturalistic Groups,” Sci. Rep. 8, 1–8 (2018).
2.65 Mengel, F.; “Risk and temptation: a meta-study on prisoner’s dilemma games,” Econ. Journal, 128 (616) 3182–3209 (2018).
2.66Jusup, M., Maciel-Cardoso, F., Gracia-Lázaro, C., Liu, C., Wang, Z., and Moreno, Y.; “Behavioural patterns behind the demise of the commons across different cultures: Behavioral patterns behind exploitation,” R. Soc. Open Sci., 7, 201026. 2020.
2.67Hauk, E.; “Multiple prisoner’s dilemma games with(out) an outside option: An experimental study,” Theory Decis. 54, 207–229 (2003).
2.68Cherry, T. L., and McEvoy, D. M.; “Refundable Deposits as Enforcement Mechanisms in Cooperative Agreements: Experimental Evidence with Uncertainty and Non-deterrent Sanctions,” Strateg. Behav. Environ. 7, 9–39 (2017).
2.69Kobayashi, J.; “Mobile social dilemmas in an experiment: Mobility accelerates the cycle, but does not change cooperation,” Sociol. Theory Methods 28, 187–202 (2013).
2.70 Bó, P. D. ; " Cooperation under the Shadow of the Future: experimental evidence from infinitely repeated games,” American Economic Review. 95(5) 2205-29 (2005)
2.71Azar, O. H., Lahav, Y. , and Voslinskyf, A.; “Beliefs and social behavior in a multi-period ultimatum game,” Front. Behav. Neurosci. 9, 1–11 (2015).
2.72Xu, B., Wang, S.,and Wang, Z., “Periodic frequencies of the cycles in 2 × 2 games: Evidence from experimental economics,” Eur. Phys. J. B 87, (2014).
2.73Bó, P., and Fréchette, G.; "The evolution of cooperation in infinitely repeated games: experimental evidence," American Economic Review, 101(1) 411-29(2011).
2.74Kloosterman, A.; “Cooperation in stochastic games: a prisoner’s dilemma experiment.” Exp Econ 23, 447–467 (2020). https://doi.org/10.1007/s10683-019-09619-w
2.75Brosig, J.; “Identifying cooperative behavior: Some experimental results in a prisoner’s dilemma game.” J. Econ. Behav. Organ. 47, 275–290 (2002).
2.76Radlow, R.; “ An experimental study of “Cooperation” in the Prisoner’s dilemma game. ” The Journal of Conflict Resolution,9(2) 221-227(1965).
2.77Cachon, G. P., and Camerer, C. F.; “Loss-Avoidance and Forward Induction in Experimental Coordination Games,” Q. J. Econ., 111(1) 165–194(1996).
2.78 Fehr, E., and Gächter, S. ; “Cooperation and punishment in public goods experiments,” Am. Econ. Rev., 4 980–994 (2000).
2.79Otten, K., Buskens, V. , Przepiorka, W. , & Ellemers, N.; “Heterogeneous groups cooperate in public good problems despite normative disagreements about individual contribution levels.” Scientific Reports, 10(1), 1–12(2020).
2.80Lohse, J., & Waichman, I.; “ The effects of contemporaneous peer punishment on cooperation with the future.” Nat. Commun. 11, 1–8 (2020).
2.81Kamijo, Y., Kira, Y., & Nitta, K.,” Even Bad Social Norms Promote Positive Interactions.” Sci. Rep. 10, 1–6 (2020).
2.82Raihani, N. J., and Bshary, R.; “Third-party punishers are rewarded, but third-party helpers even more so,” Evolution (N. Y). 69, 993–1003 (2015).
2.83Bond, R. M.; “Low-cost, high-impact altruistic punishment promotes cooperation cascades in human social networks,” Sci. Rep. 9, 1–9 (2019).
2.84Trivers, R. L.;” The evolution of reciprocal altruism,” Q. Rev. Biol., 46 (1) 35–57 (1971)
2.85 Axelrod, R.;”The evolution of cooperation,” New York:Basic Books, 1984.
2.86Hauser, O. P., Rand, D. G., Peysakhovich, A., & Nowak, M. A.;“Cooperating with the future” Nature, 511 220–223 (2014).
2.87Cassar, A.; “Coordination and cooperation in local, random and small world networks: Experimental evidence,” Games Econ. Behav. 58, 209–230 (2007).
2.88Suri, S., and Watts, D. J.; “Cooperation and contagion in web-based, networked public goods experiments,” PLoS One 6, (2011).
2.89Rand, D. G., Arbesman, S., and Christakis, N. A.; “Dynamic social networks promote cooperation in experiments with humans,” Proc. Natl. Acad. Sci. U. S. A. 108, 19193–19198 (2011).
2.90Gracia-Lázaro, C. et al., “Heterogeneous networks do not promote cooperation when humans play a prisoner’s dilemma,” Proc. Natl. Acad. Sci. U. S. A. 109, 12922–12926 (2012).
2.91Baldassarri, D., and Grossman, G.; “The Effect of Group Attachment and Social Position on Prosocial Behavior. Evidence from Lab-in-the-Field Experiments,” PLoS One 8, (2013).
2.92Yonenoh, H. , and Akiyama, E.; “Selection of opponents in the prisoner’s dilemma in dynamic networks: An experimental approach,” J. Theor. Biol. 351, 25–36 (2014).
2.93Hirahara, Y., Toriumi, F., and Sugawara, T.; “Cooperation-dominant situations in SNSnorms game on complex and Facebook networks,” Trans. Japanese Soc. Artif. Intell. 30, 782–790 (2015).
2.94Pereda, M. , Capraro, V. , and Sánchez, A.; “Group size effects and critical mass in public goods games,” Sci. Rep. 9, 1–10 (2019).
2.95Rand, D. G., Nowak, M. A., Fowler, J. H., and Christakis, N. A., “Static network structure can stabilize human cooperation,” Proc. Natl. Acad. Sci. U. S. A. 111, 17093–17098 (2014).
2.96Berg, P.V.D., Dewitte, P., Aertgeerts, I.,& Wenseleers, T.;” How the incentive to contribute affects contributions in the one-shot public goods game. “ Sci. Rep. 10, 8–12 (2020).
2.97Haesevoets, T., Bostyn, D. H. , Reinders Folmer, C. , Roets, A., and Van Hiel, A.; “Decision making in the prisoner’s dilemma game: The effect of exit on cooperation and social welfare,” J. Behav. Decis. Mak. 32, 61–78 (2019).
2.98Smith, R. P., et al., “The public and private benefit of an impure public good determines the sensitivity of bacteria to population collapse in a snowdrift game,” Environ. Microbiol. 21, 4330–4342 (2019).
2.99Cárdenas, J. C. , Gómez, S., and Mantilla, C.; “Between-group competition enhances cooperation in resource appropriation games,” Ecol. Econ. 157, 17–26 (2019).
2.100 Becks, L., and Milinski, M. ; “Extortion strategies resist disciplining when higher competitiveness is rewarded with extra gain,” Nat. Commun. 10, 1–10 (2019).
2.101 Zhang, M. , Ma, Y. Tao, Y. , Wang, Z., Shi, L., and Wang, R. W.; “Awareness of wealth inequalities breeds animosity,” Chaos, Solitons and Fractals 130, 109398 (2020).
2.102 Nishi, A., Shirado, H., Rand, D. G. and Christakis, N. A.; “Inequality and visibility of wealth in experimental social networks,” Nature 526, 426–429 (2015)
3.1 Pennisi, E.;“How did cooperative behavior evolve,” Science (80-. )., 309(5731), 93,(2005).
3.2 Nowak, M. A.,“Five rules for the evolution of cooperation,” Science, 314 (5805) , 1560–1563,(2006).
3.3 Szabó , G. and Fáth, G. “Evolutionary games on graphs,” Phys. Rep., 446( 4–6), 97– 216( 2007).
3.4 Perc, M., Gómez-Gardeñes,J., Szolnoki, A., Floría, L. M., and Moreno, Y. ; “Evolutionary dynamics of group interactions on structured populations: A review,” J. R. Soc. Interface, 10,(80), 2013.
3.5 Perc, M. and Szolnoki, A.; “Coevolutionary games-A mini review,” BioSystems, 99,(2), 109–125(2010).
3.6 Tanimoto, J.; “Fundamentals of Evolutionary Game Theory and its Applications,” Springer, 2015.
3.7 Tanimoto, J.; “Evolutionary Games with Sociophysics,” Springer, 2018.
3.8 Wang, Z. et al., “Onymity promotes cooperation in social dilemma experiments,” Sci. Adv., 3(3),1–8( 2017).
3.9 Wang, Z., Jusup, M., Shi, Shi, L., Lee, J. H., Iwasa,Y., and Boccaletti, S.;“Exploiting a cognitive bias promotes cooperation in social dilemma experiments,” Nat. Commun., 9(1),1–7,(2018).
3.10 Tanimoto, J.; “Promotion of cooperation through co-evolution of networks and strategy in a 2 × 2 game,” Phys. A Stat. Mech. its Appl.,388(6),953–960(2009).
3.11Tanimoto, J., Nakata, M., Hagishima, A., and Ikegaya, N.; “Spatially correlated heterogeneous aspirations to enhance network reciprocity,” Phys. A Stat. Mech. its Appl., 391(3), 680–685(2012).
3.12Tanimoto, J.; “Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks,” Phys. A Stat. Mech. its Appl., 392(13), 2955–2964(2013).
3.13 Tanimoto, J.; “The effect of assortativity by degree on emerging cooperation in a 2 × 2 dilemma game played on an evolutionary network,” Phys. A Stat. Mech. its Appl., 389(16,) 3325–3335(2010).
3.14 Kokubo, S., Wang, Z., and Tanimoto, J.; “Spatial reciprocity for discrete, continuous and mixed strategy setups,” Appl. Math. Comput., 259( May), 552–568(2015).
3.15 Yamauchi, A., Tanimoto, J.,and Hagishima, A.; “What controls network reciprocity in the Prisoner’s Dilemma game?,” BioSystems, 102(2–3), 82–87(2010).
3.16 Ogasawara, T. ,Tanimoto, J. ,Fukuda, E., Hagishima, A., and Ikegaya, N.; “Effect of a large gaming neighborhood and a strategy adaptation neighborhood for bolstering network reciprocity in a prisoner’s dilemma game,” J. Stat. Mech. Theory Exp., 2014(12), 2014.
3.17 Li, Y., Sun, H., Han, W., and Xiong, W.; “Evolutionary public goods game on the birandom geometric graph,” Phys. Rev. E 101, 42303 (2020).
3.18 Kurokawa, S. “Disbandment rule sways the evolution of tolerance,” Appl. Math. Comput. 392, 3–8 (2021).
3.19 Deng, L., Zhang, X. and Wang, C.; “Coevolution of spatial ultimatum game and link weight promotes fairness,” Appl. Math. Comput. 392, (2021).
3.20 Kuperman, J., Bárcenas, D. R., and Kuperman, M. N.; “Evolutionary game inspired by Cipolla’s basic laws of human stupidity,” Phys. Rev. E 101, 1–9 (2020).
3.21 Wang, S., Liu, L., and Chen, X.; “Tax-based pure punishment and reward in the public goods game,” Phys. Lett. Sect. A Gen. At. Solid State Phys. 386, 126965 (2021).
3.22 Yule, K. M., Johnson, C. A., Bronstein, J. L. and Ferrière, R.; “Interactions among interactions: The dynamical consequences of antagonism between mutualists,” J. Theor. Biol. 501, 110334 (2020).
3.23 Zhang, B., An, X., and Dong, Y.; “Conditional cooperator enhances institutional punishment in public goods game,” Appl. Math. Comput. 390, 125600 (2021).
3.24 Zhang, J. ,Hu, B., Huang, Y. J., Deng, Z. H., and Wu, T.; “The evolution of cooperation affected by aspiration-driven updating rule in multi-games with voluntary participation,” Chaos, Solitons and Fractals 139, 110067 (2020).
3.25 Zhang, L., Huang, C. Li, H. Dai, Q. and Yang, J.; “Effects of directional migration for pursuit of profitable circumstances in evolutionary games,” Chaos, Solitons and Fractals 144, (2021).
3.26 Xia, C., Gracia-Lázaro, C., and Moreno, Y.; “Effect of memory, intolerance, and secondorder reputation on cooperation,” Chaos 30, 1–12 (2020).
3.27 Gao, S., Du, J. Liang, J. “Evolution of cooperation under punishment,” PRE 101, 062419(2020).
3.28 Li, X., Dai, X., Jia, D., Guo, H. et.al.,” Double explosive transitions to synchronization and cooperation in intertwined dynamics and evolutionary games, “New Journal of Physics, 22(12),2020
3.29 Donahue, K., Hauser, O. P., Nowak, M. A., Hilbe, C.; “Evolving cooperation in multichannel games, Nature Communication,” 11,3885(2020).
3.30 Huang, F., Cao, M., Wang, L.; “Learning enables adaptation in cooperation for multi-player stochastic games,” Journal of The Royal Society Interface,17(172), 2020.
3.31 Wang, X., Chen, X., Wang, L.; “Evolution of egalitarian social norm by resource management, “PLoS One 15 (1), e 0227902 (2020).
3.32 Yang, G., Csikasz-Nagy, A. Waites, W., Xiao, G.; “Cavaliere, M.; Information cascades and the collapse of cooperation,” Scientific Reports 10, 8004(2020).
3.33 Jian, Q., Li, X., Wang, J., Xia, C.;” Impact of reputation assortment on tag mediated altruistic behaviors in the spatial lattice,” Applied Mathematics & Computation,396,125928(2021).
3.34 Broom, M., Krivan, V.” Two-strategy games with time constraints on regular graphs,” JTB 506, 11-426(2020).
3.35 L. Fiaschi, M. Cococcioni,” Non-Archimedean game theory: A numerical approach,” Applied Mathematics & Computation, June,125356(2020).
3.36 Shu, F.; “A Win-Switch-Lose-Stay strategy promotes cooperation in the evolutionary games, “Physica A 555, 124605(2020).
3.37 Yang, G., Cavaliere, M., Zhu, C., Perc, M.;” Ranking the invasions of cheaters in structured populations,” Scientific Reports 10, 2231 (2020).
3.38 Klemm, K., and Khahil, N.; “Altruism in populations at the extinction transition,” Physical Review Research 2, 013374(2020).
3.39 Sun, T. A., and Hilker, F. M.” Comparison between best-response dynamics and replicator dynamics in a social-ecological model of lake eutrophication,” JTB 509, 110491(2021).
3.40 Couto, M. C., Pacheco, J. M., Santos, F. C.;” Governance of risky public goods under graduated punishment, JTB 505, 110423(2020).
3.41 Wang, Z., Jusup, M., Shi, L., Lee, J.-H., Iwasa, Y., Boccaletti, S.;” Exploiting a cognitive bias promotes cooperation in social dilemma experiments,” Nature Communications 9 ,2954(2018).
3.42 Kumar, A., Capraro, V., Perc, M.; “The evolution of trust and trustworthiness, “Journal of Royal Society Interface 17, 20200491(2020).
3.43 Xia, C., Cracia-Lazaro, C., Moreno, Y.; “Effect of memory intolerance and second order reputation on cooperation, “Chaos 30, 063122(2020).
3.44 Xia, K.; “Average abundance function of multi-player threshold public goods without initial endowment evolutionary game model under differential aspiration levels and redistribution mechanism, “Chaos, Solitons & Fractals, 142,110490(2021).
3.45 Van Vliet, S., Hauert, C., Ackermann, M., and Co, A. D.; “Predicting global dynamics of spatial microbial communities from local interaction rules,” bioRxiv 1–17 (2020) doi:10.1101/2020.07.25.220822.
3.46 De Jaegher, K.; “High thresholds encouraging the evolution of cooperation in threshold public-good game, “Scientific Reports 10,5863(2020).
3.47 Otten, K.., Buskens, V., Przepiorka, W., Ellemers, N., “Heterogeneous groups cooperate in public good problems despite normative disagreements about individual contribution levels,” Scientific Repots 10, 16702(2020).
3.48 Anderson, L., “Cooperative between emotional players,” Game 11 (45), 11040045(2020).
3.49 Lohse, J., Waichman, I. “The effects of contemporaneous peer punishment on cooperation with the future, Nature Communications,” 11,1815(2020).
3.50 Vasconcelos, V. V., Hannam, P. M., Levin, S. A. Pacheco, J. M.; “Coalition-structured governance improves cooperation to provide public goods,” Scientific Reports 10,9194(2020).
3.51 Gao, S., Liang, J.; “Cooperation under institutional incentives with perfect and imperfect observation,” Physics Letters A 384, 126723(2020).
3.52 Li, K., Mao, Y. Wei, Z. Cong, R. “Pool-rewarding in N-person snowdrift game, “Chaos, Solitons & Fractals 143, 110591(2021).
3.53 Mittal, S., Mukhopadyay, A., Chakraborty, S.; “Evolutionary dynamics of the delayed replicator-mutator equation: Limit cycle and cooperation,” PRE 101, 042410 (2020).
3.54 Krivan, V., Cressman, R.; “Defectors’ intolerance of others promotes cooperation in the repeated public goods game with opting out, “Scientific Reports 10, 19511(2020).
3.55 Murase, Y., Baek, S.-K.; “Five rules for friendly rivalry in direct reciprocity, “Scientific Reports 10,16904(2020).
3.56 Kaveh, K., McAvoy, A. Chatterjee, K., Nowak, M. A.; “The Moran process on 2-chromatic graphs, “PLOs Computational Biology 16 (11), 1108402(2020).
3.57 Wang, J., Yu, F., Zhao, J., Li, F., He, J.; “How costly altruism survives? The rescue of both cooperation and voluntary sharing, “CSF 143, 110602, 2021.
3.58 Pei, H., Yan, G., Wang, H.; “Reciprocal rewards promote the evolution of cooperation in spatial prisoner’s dilemma game,” Physics Letter A 390, 127108, 2021.
3.59 Wang, S., Kiu, L., Chen, X.; “Tax-based pure punishment and reward in the public goods game, “CSF 386, 126965(2021).
3.60 Newton, Y.; “Maximizing cooperation in the prisoner’s dilemma evolutionary games via optimal control,” PRE 103, 012304(2021).
3.61 Yang, G., Cavaliere, M., Zhu, C., Perc, M.; Strategically positioning cooperators can facilitate the contagion of cooperation, Scientific Reports, 11: 1127(2021).
3.62 Nowak,M. A., and May, R. M.; “Evolutionary games and spatial chaos,” Nature, 359(6398), 826–829( 1992).
3.63 Perc, M., Jordan, J., Rand, D. G., Wang, Z., Boccaletti, S., and Szolnoki, A.; “Statistical physics of human cooperation,” Phys. Rep., 687(May), 1–51(2017).
3.64 Masuda, N., and Aihara, K.; “Spatial prisoner’s dilemma optimally played in small-world networks,” Phys. Lett. Sect. A Gen. At. Solid State Phys., 313(1–2), 55–61(2003).
3.65 Hauert, C., and Szabó, G.; “Game theory and physics,” Am. J. Phys.,73(5), 405–414(2005).
3.66 Tomochi, M. ; “Defectors’ niches: Prisoner’s dilemma game on disordered networks,” Soc. Networks, 26(4), 309–321(2004).
3.67 Ren, J., Wang, W. X., and Qi, F.; “Randomness enhances cooperation: A resonance-type phenomenon in evolutionary games,” Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 75(4,) 1–4(2007).
3.68 Gómez-Gardeñes, J., Campillo, M., Floría, L. M., and Moreno, Y.; “Dynamical organization of cooperation in complex topologies,” Phys. Rev. Lett., 98(10), 1–4(2007).
3.69 Santos, F. C., and Pacheco, J. M.;“Scale-free networks provide a unifying framework for the emergence of cooperation,” Phys. Rev. Lett., 95(9), 1–4(2005).
3.70 Santos, F. C., Rodrigues, J. F. and Pacheco, J. M.;“Graph topology plays a determinant role in the evolution of cooperation,” Proc. R. Soc. B Biol. Sci., 273(1582), 51–55(2006).
3.71 Tang, C. L., Wang, W. X. , Wu, X., and Wang, B. H.; “Effects of average degree on cooperation in networked evolutionary game,” Eur. Phys. J. B,53(3), 411–415(2006).
3.72 Poncela, J., Gómez-Gardeñes, J., Floría, L. M., and Moreno, Y.; “Robustness of cooperation in the evolutionary prisoner’s dilemma on complex networks,” New J. Phys., 9(March), 2007.
3.73 Lin, Z., Xu, H., and Fan, S.; “Evolutionary accumulated temptation game on small world networks,” Phys. A Stat. Mech. its Appl. 553, 124665 (2020).
3.74 Chen, W., Yang, Z., and Wu, T.; “Evolution of cooperation driven by collective interdependence on multilayer networks,” Appl. Math. Comput. 388, (2021).
3.75 Chowdhury, S. N., Kunda, S., Duh, M., Perc, M., Ghosh, D. “Cooperation on interdependent networks by means of migration and stochastic imitation, “Entropy 22, 285, 2020.
3.76 Lv, S., Li, J., Mi, J., Zhao, C.;” The roles of heterogeneous investment mechanism in the public goods game on scale free networks, “Physics Letters A 384, 126343(2020).
3.77 Zhu, X., Su, X., Ma, J., Tian, H., Liu, R.-R.; “Evolutionary cooperation in networked public goods game with dependency groups, Complexity,” 8670802, 2019.
3.78 Shigaki, K., Tanimoto, J., Wang, Z. ,Kokubo, S., Hagishima, A., and Ikegaya, N.; “Referring to the social performance promotes cooperation in spatial prisoner’s dilemma games,” Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 86( 3), 2012.
3.79 Shigaki, K., Wang, Z., Tanimoto, J., and Fukuda, E. ;“Effect of initial fraction of cooperators on cooperative behavior in evolutionary prisoner’s dilemma game,” PLoS One, 8(11), 1–7(2013).
3.80 Wang, Z., Kokubo, S., Tanimoto, J. , Fukuda, E., and Shigaki, K.; “Insight into the socalled spatial reciprocity,” Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 88( 4), 2013.
3.81 You, T., Wang, X., Jia, D., Liu, C. and Sun, B. “Reputation based on edge dynamics promotes cooperative behavior,” Phys. Lett. Sect. A Gen. At. Solid State Phys.,398, 127283(2021).
3.82 Liu, R. R., Jia, C. X., and Rong, Z.; “Effects of strategy-updating cost on evolutionary spatial prisoner’s dilemma game,” Appl. Math. Comput. 386, 125445 (2020).
3.83 Sérgio. A. R., and Schimit, P. H. T., “Interaction characteristics as evolutionary features for the spatial Prisoner’s Dilemma in a population modeled by continuous probabilistic cellular automata and evolutionary algorithm,” Ecol. Complex. 42, 100829 (2020).
3.84 Xie, Y., Zhang, S., Zhang, Z.,and Bu, H. “Impact of binary social status with hierarchical punishment on the evolution of cooperation in the spatial prisoner’s dilemma game,” Chaos, Solitons and Fractals 130, (2020).
3.85 Sendiña-Nadal. I., et al., “Diverse strategic identities induce dynamical states in evolutionary games,” Physical Review Research 2, 043168 (2020).
3.86 Jian, Q., Li, X., Wang, J., Xia, C.; Impact of reputation assortment on tag mediated altruistic behaviors in the spatial lattice, Applied Mathematics & Computation, 2020.
3.87 He, J., Wang, J., Yu, F., Zheng, L.;” Reputation based strategy persistence promotes cooperation in spatial social dilemma, “Physics Letter A 384, 126703,(2020).
3.88 Li, W.-J., Jiang, L.-L., Chen, Z., Perc, M., Slavinec, M.;” Optimization of mobile individuals promotes cooperation in social dilemmas, “Chaos, Solitons & Fractals 141, 110425(2020).
3.89 He, Z., Geng, Y., Shen, C., Shi, L.; “Evolution of cooperation in the spatial prisoner’s dilemma game with extortion strategy under win-stay-lose-move rule,” Chaos, Solitons & Fractals 141, 110421(2020).
3.90 Zhu, H., Ding, H., Zhao, Q.-Y. , Xu, Y.-P., Jin, X., Wang, Z.; ”Reputation-based adjustment of fitness promotes the cooperation under heterogeneous strategy updating rules,” Physics Letters A 384, 126882 (2020).
3.91 Yang, B., Chen, T., Chen, Q.;” Promoting cooperation by reputation-based payoff transfer mechanism in public goods game, “Euro. Phys. J. B 93 (94), 2020.
3.92 You, T., Shi, L. ,Wang, X., Mengibaev, M., Zheng, Y., Zhang, P.;” The effects of aspiration under multiple strategy updating rules on cooperation in prisoner’s dilemma game,” Applied Mathematics and Computation, 394, 125770(2021).
3.93 Pei, H. ,Yan, G., Wang, H.; “Reciprocal rewards promote the evolution of cooperation in spatial prisoner’s dilemma game, “Physics Letter A 390, 127108, (2021).
3.94 Cheng, Y., Xue, Y., and Chang, M.; “Career choice as an extended spatial evolutionary public goods game,” Chaos, Solitons and Fractals 137, (2020).
3.95 Quan, J.; Zhang, M.; Wang, X.; '” Effects of synergy and discounting on cooperation in spatial public goods games, “Physics Letters A 388, 127055 (2021).
3.96 Liu, C., Wang, J. , Li, X. , Xia, C.” Diversity of interaction intensity enhances the cooperation of spatial multi-games on interdependent lattices,” Physics Letters A 384, 126928(2020).
3.97 Han, W., Zheng, Z., Sun, J., Xia, C.; Emergence of cooperation with reputation-updating timescale in spatial public goods game, Physics Letters A 393, 127173, 2021.
3.98 Fu, F., Rosenbloom, D. I., Wang, L., and Nowak, M. A.; “Imitation dynamics of vaccination behaviour on social networks,” Proc. R. Soc. B Biol. Sci., 278(1702), 42–49(2011).
3.99 Traulsen, A., Pacheco, J. M. , and Nowak, M. A.; “Pairwise comparison and selection temperature in evolutionary game dynamics,” J. Theor. Biol., 246(3), 522–529( 2007).
3.100 Matsuzawa, R.Tanimoto, J. and Fukuda, E.; “Spatial prisoner’s dilemma games with zealous cooperators,” Phys. Rev. E, 94( 2), 2016.
3.101 Szolnoki, A., and Perc, M. ; “Conformity enhances network reciprocity in evolutionary social dilemmas,” J. R. Soc. Interface, 12(103), 2–9(2015).
3.102 Shu, F., Liu, Y. Liu, X. and Zhou, X.; “Memory-based conformity enhances cooperation in social dilemmas,” Appl. Math. Comput., 346, 480–490(2019).
3.103 Henrich, J., and Boyd, R.; “Why people punish defectors: Weak conformist transmission can stabilize costly enforcement of norms in cooperative dilemmas,” J. Theor. Biol., 208(1),79–89(2001).
3.104 Zhang, L., Huang, C., Li, H., Dai, Q., and Yang, J.; “Cooperation guided by imitation, aspiration and conformity-driven dynamics in evolutionary games,” Phys. A Stat. Mech. its Appl. 561, 125260 (2021).
3.105 Lin, J., Huang, C., Dai, Q. , and Yang, J.; “Evolutionary game dynamics of combining the payoff-driven and conformity-driven update rules,” Chaos, Solitons and Fractals 140, (2020).
3.106 Wang, Z., Kokubo, S., Jusup, M., and Tanimoto, J. ;“Universal scaling for the dilemma strength in evolutionary games,” Phys. Life Rev., 14,1–30 (2015).
3.107 Tanimoto. J., and Sagara, H.; “Relationship between dilemma occurrence and the existence of a weakly dominant strategy in a two-player symmetric game,” BioSystems, 90(1), (105– 114) 2007.
3.108 Alam, M., Nagashima, K., and Tanimoto, J.;“Various error settings bring different noise- driven effects on network reciprocity in spatial prisoner’s dilemma,” Chaos, Solitons and Fractals, 114, 338–346(2018).
3.109 Habib, MD. A., Kabir, K. M. A., Tanimoto, J.; Do humans play according to the game theory when facing the social dilemma situation? A survey study, Evergreen 07 (01), 7-14, 2020.
4.1 Kazmerski, L. L.; “Photovoltaics R & D : At the Tipping Point,” NREL/CP-520-37553, January, 2005.
4.2 Singh, G.K.;” Solar power generation by PV (photovoltaic) technology: A review” Energy, 53, 1-13(2013).
4.3 Rahman, M. M., Khan, M. M.H., Ullah, M. A., Zhang, X., Kumar. A.;” A hybrid renewable energy system for a North American off-grid community,” Energy, 97, 151-160 (2016).
4.4 Huang, Y., Wang, H., Liu, S.; “Research on ‘near-zero emission’ technological innovation diffusion based on co-evolutionary game approach,” Syst. Sci. Control Eng., 7(2), 23–31 (2019).
4.5 Bushnell, J. , Halseth, A., Read, E. G. , Rogers, J. S.; “An International Comparison of Models for Measuring Market Power in Electricity,” Manage. Sci., 1 (1999) .
4.6 Taylor, P. D. , Jonker, L. B. ; “Evolutionary stable strategies and game dynamics,” J. Math. Biosci., 40(1–2), 145–156 (1978).
4.7 Tanimoto, J. ; “Fundamentals of Evolutionary Game Theory and its Applications,” Springer, 2015.
4.8 Tanimoto, J. ; “Evolutionary Games with Sociophysics,” Springer, 2018.
4.9 Du, W. B. , Bin Cao, X. , Zhao, L., Bin Hu, M.; “Evolutionary games on scale-free networks with a preferential selection mechanism,” Phys. A Stat. Mech. its Appl., 388(20), 4509–4514 (2009).
4.10 Ahsan Habib, M., Ariful Kabir, K. M. , Tanimoto, J.; “‘Do humans play according to the game theory when facing the social dilemma situation?’ A survey study,” Evergreen, 7(1), 7– 14 (2020).
4.11 Ito, H. , Katsumata, Y., Hasegawa, E. , Yoshimura, J. ; “The promotion of cooperation by the poor in dynamic chicken games,” Sci. Rep., 7, 1–10 (2017).
4.12 Ahsan Habib, M., Tanaka, M., Tanimoto, J. ;“How does conformity promote the enhancement of cooperation in the network reciprocity in spatial prisoner’s dilemma games?,” Chaos, Solitons and Fractals, 138, 1-7 (2020).
4.13 Berg, D., Weissing, J. F.; “Evolutionary Game Theory and Personality,” Evol. Psychol.,May, 451-463 (2015).
4.14 Tanimoto, J., Sagara, H. ;“Relationship between dilemma occurrence and the existence of a weakly dominant strategy in a two-player symmetric game,” BioSystems, 90(1),105– 114(2007).
4.15 Ito, H., Tanimoto, J. ; “Scaling the phase-planes of social dilemma strengths shows gameclass changes in the five rules governing the evolution of cooperation,” R. Soc. Open Sci., 5(10),1-9( 2018).
4.16 Tanimoto, J.; “Promotion of cooperation by payoff noise in a 22 game,” Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 76, 041130-7 (2007).
4.17 Wang, Z. , Kokubo, S., Jusup, M., Tanimoto, J.; “Universal scaling for the dilemma strength in evolutionary games,” Phys. Life Rev., 14, 1–30( 2015).
4.18 Tanimoto, J. ; “Dilemma solving by the coevolution of networks and strategy in a 2×2 game,” Phys. Rev. E - Stat. Nonlinear, Soft Matter Phys., 76, 021126( 2007).
4.19 Tanimoto, J.;“Coevolutionary, coexisting learning and teaching agents model for prisoner’s dilemma games enhancing cooperation with assortative heterogeneous networks,” Phys. A Stat. Mech. It Appl., 392(13),2955–2964(2013).
4.20 Tanimoto, J. ;“Promotion of cooperation through co-evolution of networks and strategy in a 2 × 2 game,” Phys. A Stat. Mech. its Appl., 388(6), 953–960(2009).
4.21 Alam, M., Nagashima, K. , Tanimoto, J. ; “Various error settings bring different noisedriven effects on network reciprocity in spatial prisoner’s dilemma,” Chaos, Solitons and Fractals, 114, 338–346 (2018).
4.22 Smith, J. M.;” Evolution and the theory of the games” Cambridge University Press,1982.
4.23 Smith, J. M., Hofbauer, J.;” The battle of the sexes: a genetic model with limit cycle behavior” Theoretical Population Biology, 32 (1), 1-14 (1987).
4.24 Selten, R.;” A note on evolutionary stable strategies in asymmetric animal conflicts.” Journal of Theoretical Biology, 84(1), 93-101(1980).
4.25 Hammerstein, P.;” The role of asymmetry in animal contests.” Animal Behavior, 29(1),193-205 (1981).
4.26 Ohtsuki, H.;” Stochastic evolutionary dynamics of bimatrix games.” Journal of Theoretical Biology, 264(1), 136-142(2010).
4.27 He, J. Z., Zhao,Y., Cai, H. J. , Wang, R. W. ;“Spatial games and the maintenance of cooperation in an asymmetric Hawk-Dove game,” Chinese Sci. Bull., 58(18),2248– 2254(2013).
4.28 McAvoy, A. , Hauert, C. ; “Asymmetric Evolutionary Games,” PLoS Comput. Biol., 11(8), 1–26 (2015).
4.29 Kohli, I. S., and Haslam, M. C.; “An Analysis of the Replicator Dynamics for an Asymmetric Hawk-Dove Game,” Int. J. Differ. Equations 2017, (2017).
4.30 Berg, D.,and Weissing, J. F. ; “Evolutionary Game Theory and Personality,” Evol. Psychol. May 2015, 451–463 (2015) .
4.31 Chang, S. Le. and Prokopenko, M. ; “Instability of mixed nash equilibria in generalized hawk-dove game: A project conflict management scenario,” Games 8, (2017).
4.32 Carlsson, B. and Johansson, S.; “An iterated hawk-and-dove game,” Lect. Notes Comput. Sci. 1441, 179–192 (1998).
4.33 Jianya, Z., Weigang, L.and Li, D. L.; “A game-theory based model for analyzing emarketplace competition,” ICEIS 2015 - 17th Int. Conf. Enterp. Inf. Syst. Proc. 1, 650–657 (2015).
4.34 Guimaraes, T., Sato, O.; “Benefits of Environmental Stewardship,” J. Transnatl. Manag. Dev., 2(3),1996.
4.35 Porter, M. E., Van Der Linde, C.; “Green and Competitive : Ending the Stalemate Green and Competitive,” Harv. Bus. Rev., 73(5),120–134 ,(1995).
4.36 Hauert, C., Saade, C., McAvoy, A. ;“Asymmetric evolutionary games with environmental Feedback, ”Journal of Theoretical Biology ,462, 347-360(2019).
4.37 Wang, C. and Shi, F.; “An evolutionary game model for industrial pollution management under two punishment mechanisms,” Int. J. Environ. Res. Public Health 16, (2019).
4.38 Dijkstra, B. R. and de Vries, F. P.; “Location choice by households and polluting firms: An evolutionary approach,” Eur. Econ. Rev. 50, 425–446 ,(2006).
4.39 Tanimoto, J. ; “Mathematical Analysis of Environmental System,” Springer, 2014.
4.40 Wang, Y. , Wang, F.; “Evolutionary Game Analysis on Production and Emissions Reduction of Manufacturing Enterprises under Different Carbon Policies,” IOP Conf. Ser. Earth Environ. Sci., 199(2), (2018).
4.41 Wang, C. , Shi, F. ;“An evolutionary game model for industrial pollution management under two punishment mechanisms,” Int. J. Environ. Res. Public Health, 16(15), (2019).
4.42 Zhu, G., Pan, G. , Zhang, W.; “Evolutionary game theoretic analysis of low carbon investment in supply chains under governmental subsidies,” Int. J. Environ. Res. Public Health, 15(11),(2018).
4.43 Zhao, R., Zhou, X., Han, J., and Liu, C.; “For the sustainable performance of the carbon reduction labeling policies under an evolutionary game simulation,” Technol. Forecast. Soc. Change 112, 262–274 (2016).
4.44 Chen. W., and Hu, Z. H., “Using evolutionary game theory to study governments and manufacturers’ behavioral strategies under various carbon taxes and subsidies,” J. Clean. Prod. 201, 123–141 (2018).
4.45 Zu, Y., Chen, L., and Fan, Y.; “Research on low-carbon strategies in supply chain with environmental regulations based on differential game,” J. Clean. Prod. 177, 527–546 (2018).
4.46 Wang, S., Fan, J., Zhao, D. and Wu, Y.; “The Impact of Government Subsidies or Penalties for New-energy Vehicles A Static and Evolutionary Game Model Analysis,” J. Transp. Econ. Policy 49, 98–114 (2015).
4.47 Luo, A., and Ruan, Z.; “A Simply Carbon Pricing Model between Government and Enterprises based on Game Theory,” Int. J. u- e-Service, Sci. Technol. 8, 71–78 (2015).
4.48 Zhu, Q. H. , Dou, Y. J. ; “Evolutionary model between governments and core-enterprises in green supply chains,” Xitong Gongcheng Lilun yu Shijian/System Eng. Theory Pract., 27(12),.85–89,(2007).
4.49 Chao, X. , Zongfang, Z.; “The evolutionary game analysis of credit behavior of SME in guaranteed loans organization,” Procedia Comput. Sci., 17, 930–938(2013).
4.50 Ji, P., Ma, X., Li, G. ;“Developing green purchasing relationships for the manufacturing industry: An evolutionary game theory perspective,” Int. J. Prod. Econ., 166, 155–162 (2015).
4.51 Li, Z., Jin, G. , Duan, S.; “Evolutionary Game Dynamics for Financial Risk DecisionMaking in Global Supply Chain,” Complexity, 2018,(2018).
4.52 Hao, C., Du, Q., Huang, Y., Shao, L., Yan, Y.; “Evolutionary game analysis on knowledgesharing behavior in the construction supply chain,” Sustain. ,MDPI, 11(19), 5319 (2019).
4.53 Qin, R., and Jian, Z.; “The Simulation Study of the Change of Accounting Standards for Business Enterprises Based on Evolutionary Game,” Expert Journal of Finance, 3, 31- 39(2015).
4.54 Liu, X., Zhang, Z., Qi, W., and Wang, D.; “Behavior Analysis with an Evolutionary Game Theory Approach for Procurement Bid Evaluation Involving Technical and Business Experts,” IEEE Syst. J. 13, 4374–4385 (2019).
4.55 Ozkan-Canbolat E., and Beraha, A.; “Evolutionary stable strategies for business innovation and knowledge transfer,” Int. J. Innov. Stud. 3, 55–70 (2019).
4.56 Krapohl, S., Ocelík, V., and Walentek, D. M.; “The instability of globalization: applying evolutionary game theory to global trade cooperation,” Public Choice (2020).
4.57 Ozkan-Canbolat, E., Beraha, A., and Bas, A.; “Application of Evolutionary Game Theory to Strategic Innovation,” Procedia - Soc. Behav. Sci. 235, 685–693 (2016).
4.58 Lei. L., and Gao, S.; “Transportation network companies and drivers dilemma in China: An evolutionary game theoretic perspective,” Transport 34, 579–590 (2019).
4.59 Yu, H., Zeng, A. Z. & Zhao, L.; “Analyzing the evolutionary stability of the vendormanaged inventory supply chains,” Comput. Ind. Eng. 56, 274–282 (2009).
4.60 Ji, P., Ma, X. & Li, G. Developing green purchasing relationships for the manufacturing industry: An evolutionary game theory perspective. Int. J. Prod. Econ. 166, 155–162 (2015).
4.61 He, W.; “A Dynamic Evolutionary Game Model of Modular Production Network,” Discret. Dyn. Nat Soc., January,1–9(2016).
4.62 Jianya, Z. , Weigang, L. , Li, D. L.; “A game-theory based model for analyzing emarketplace competition,” ICEIS 2015 - 17th Int. Conf. Enterp. Inf. Syst. Proc., 1, 650– 657,(2015).
4.63 Cong,J.,Shu-Wei,J.,Tan,H-Yong.; “Computer virus propogation model based on bounded rationality evolutionary game theory”Security Comm. Networks,6,210-218, (2013).
4.64 Cai. G., and Kock, N.; “An evolutionary game theoretic perspective on e-collaboration: The collaboration effort and media relativeness,” Eur. J. Oper. Res. 194, 821–833 (2009).
4.65 Madani, K.; “Game theory and water resources,” J. Hydrol.,381, 225–238 ,(2010).
4.66 Mei, Y. , Yang, B. , Yang, J. , Wu, T.; “Evolutionary game analysis of water resources conflict for cascade hydropower stations in multiple power generation subjects,” Int. Conf. Logist. Eng. Manag. Comput. Sci. LEMCS 2014, 947–951(2014).
4.67 Yu, Y., Tang, P., Zhao, J., Liu, B. & Mclaughlin, D.; “Evolutionary Cooperation in Transboundary River Basins,” Water Resour. Res. 55, 9977–9994 (2019).
4.68 Estalaki, S. M., Abed-Elmdoust, A. & Kerachian, R.; “Developing environmental penalty functions for river water quality management: application of evolutionary game theory,” Environ. Earth Sci. 73, 4201–4213 (2015).
4.69 Liu, L., Feng, C., Zhang, H. & Zhang, X.; “Game analysis and simulation of the river basin sustainable development strategy integrating water emission trading,” Sustain. 7, 4952–4972 (2015).
4.70 García Mazo, C. M. , Olaya, Y., Botero Botero, S.; “Investment in renewable energy considering game theory and wind-hydro diversification,” Energy Strateg. Rev., 28, 100447(2020).
4.71 Yin, L., Li, S., and Gao, F.; “Equilibrium Stability of Asymmetric Evolutionary Games of Multi-Agent Systems with Multiple Groups in Open Electricity Market,” IEEE Access 8, 28970–28978 (2020).
4.72 Kim, P.; “Maximum power game as a physical and social extension of classical games,” Sci. Rep. 7, 1–11 (2017).
4.73 Mohammadi. R., and Mashhadi, H. R., “A game theory approach to distribution system reliability improvement based on customer requests,” Iran. J. Electr. Electron. Eng. 15, 1–13 (2019).
4.74 Zhang. Q., and Li, G.; “A Game Theory Energy Management Strategy for a Fuel Cell/Battery Hybrid Energy Storage System,” Math. Probl. Eng., 2019, (2019).
4.75 Mohammadi. A., and Rabinia, S.; “A comprehensive study of Game Theory applications for smart grids, demand side management programs, and transportation networks,” Smart Microgrids,57-64, (2019).
4.76 Chang, E.-C., Cheng, H.-L., and Wu, R.-C.; “Integral Sliding Mode Control Based on Game-Theoretic Approach for UPS Inverters,” Int. J. Comput. Electr. Eng. 11, 62–69 (2019).
4.77 Park, S., Shamma, J. S., and Martins, N. C.; “Passivity and Evolutionary Game Dynamics,” Proc. IEEE Conf. Decis. Control 2018-December, 3553–3560 (2019).
4.78 Mabrok, M. A.; “Passivity Analysis of Replicator Dynamics and its Variations,” IEEE Transactions on Automatic Control, (2020).
4.79 Mabrok, M. A., and Shamma, J. S.; “Passivity analysis of higher order evolutionary dynamics and population games,” 2016 IEEE 55th Conf. Decis. Control. CDC 2016 6129– 6134 (2016).
4.80 Jinliang, H.; “Evolutionary Game Analysis of Financial Regulation and Innovation Under Asymmetric Conditions,” Economics 6, 51 (2017).
4.81 Ran, H. ; “Asymmetric Evolutionary Game between Financial Innovation and Financial Regulation ---- Punishment or Encouragement,” J. Financ. Account. 5, 102 (2017).
4.82 Smojver, S. “Analysis of Banking Supervision via Inspection Game and agent based modeling” Cent. Eur. Conf. Inf. Intell. Syst. 355–361 (2012).
4.83 Soldatos, G.T.;” The Firm-Bank interaction regime and “Softness””MPRA, (2000).
4.84 Song, W., Yan, C., Peng, X. & Zheng, S.; “A Study of Coupling Relationship between Financial Supervision and Innovation: Based on the Data of China’s Commercial Bank Listed in the Form of A Shares,” J. Financ. Risk Manag. 04, 1–10 (2015).
4.85 Zhao, Y., Li, D. & Pan, L.; “Cooperation or competition: An evolutionary game study between commercial banks and big data-based e-commerce financial institutions in China,” Discret. Dyn. Nat. Soc. 2015, (2015).
4.86 Ye, L. & Fang, Y. “Evolutionary game analysis on firms and banks’ behavioral strategies: Impact of environmental governance on interest rate setting,” Environ. Impact Assess. Rev. 86, (2021).
4.87 Antoci, A. & Sacco, P. L.; “A public contracting evolutionary game with corruption,” J. Econ. Zeitschrift für Natl. 61, 89–122 (1995).
4.88 Tsebelis, G.; “The Abuse of Probability in Political Analysis: The Robinson Crusoe Fallacy,” Am. Polit. Sci. Rev. 83, 77–91 (1989).
4.89 Katsikas, S., Kolokoltsov, V. & Yang, W.; “Evolutionary inspection and corruption games,” Games 7, 1–25 (2016).
4.90 Tsebelis, G.; “Penalty has no Impact on Crime:: A Game-Theoretic Analysis,” Ration. Soc. 2, 255–286 (1990).
4.91 Rauhut, H. & Junker, M.; “Punishment deters crime because humans are bounded in their strategic decision-making,” Jasss 12, (2009).
4.92 David, P. A. ;“Clio and the economics of qwerty,” Am. Econ. Rev., 75(2), 332–337(1985).
4.93 Friedman, D.; “On economic applications of evolutionary game theory,” J. Evol. Econ. 8, 15–43 (1998).
4.94 Chen, S. H.; “An evolutionary game model of knowledge workers’ counterproductive work behaviors based on preferences,” Complexity 2017, (2017).
4.95 Lee, V. P. & O’Brien, G.; “Application of Game Theory in Agricultural Economics:Review and Requiem” J. L. Public Util. Econ. 7, 216 (1931).
4.96 Podimata, M. V. & Yannopoulos, P. C.; “Evolution of Game Theory Application in Irrigation Systems,” Agric. Sci. Procedia 4, 271–281 (2015).
4.97 Bullock, D. S. & Hall, M.; “Using Evolutionary Game Theory to Examine U . S . and EU Agricultural Policy Institutions Klaus Mittenzwei Using Evolutionary Game Theory to Examine European and U . S . Agricultural Policy Institutions,” March, 2005.
4.98 Pan, C., Long, Y.; “Evolutionary Game Analysis of Cooperation between Microgrid and Conventional Grid,” Math. Probl. Eng., 2015.
4.99 Khare, V. , Nema, S., Baredar, P.; “Application of Game Theory in PV-Wind Hybrid System,” Int. J. Electr. Electron. Eng. Res., 2(4), 25–32(2012).
4.100 Davidson, B.; “Clean coal technologies for electricity generation,” Power Engineering Journal, vol. 7, no. 6. pp. 257–263, 1993.
4.101 Ratajczak, T. J. , Shahidehpour, M.; “Emerging technology for coal-fired generation,” in Power Engineering Society General Meeting 2006. IEEE, 2006.
4.102 Koka, B. R. , Madhavan, R. , Prescott, J. E. ;“The evolution of interfirm networks: Environmental effects on patterns of network change,” Acad. Manag. Rev.,31(3), 721– 737(2006).
論文の公開元へ
