Equitable governance of common goods

Evolution and Ecology Program (EEP) research on the equitable governance of common goods analyzes the evolution of cooperation in joint enterprises and resource management, with particular emphasis on the nature and impact of governance measures such as positive or negative incentives.

Carrot on a stick © AndreaAstes | iStock

Carrot on a stick

The bulk of EEP research on this topic is theoretical, and applies the mathematical techniques of evolutionary game theory and adaptive dynamics theory. Complementing this approach, an experimental study investigating social choice between different types of social contracts has just been published [1].  

In research published in the Proceedings of the National Academy of Sciences of the USA, there was an examination of how optional participation in public goods games affects the impacts of institutional incentives such as rewards and penalties. This revealed that, when combined with voluntary participation, surprisingly small fines suffice to ensure fully cooperative behaviors, thus allowing populations to escape from the social trap of free riding [2].

In a similar vein, it was demonstrated that social exclusion (rather than voluntary non-participation) can overcome such social traps, leading to the emergence of a stable cooperative society [3]. The same outcome occurs, according to [4] if, instead of threatening ostracism, agents make voluntary contributions to a bonus system. In a related study it was demonstrated how shared rewards can help groups to escape the social trap of all-out defection in N-person volunteer’s dilemmas [5].

Opening up a new line of game-theoretical research, there was an investigation of how clever combinations of positive and negative incentives ("first carrot, then stick") are more effective and more efficient than either positive or negative incentives alone can be [6].

In a further study published in the Proceedings of the National Academy of Sciences of the USA, cooperation is studied in the traditional context of the iterated prisoner’s dilemma. It is shown that extortion strategies can succeed only in very small populations, or in the interactions between two different populations [7].

Studying spatial games, it was shown how cooperation can be promoted by the social selection of game organizers and by cautious strategy updates, respectively [8] [9].

Similarly an examination took place of the role of reputation-based mutual selection rules for partnering in spatial public goods games [10].

Most simple models of the evolution of cooperation assume that the involved agents all have access to the same level of resources. Published in Nature Communications, a paper showed that cooperation emerges even more easily if the distribution of resources is heterogeneous [11] (Figure 1).

Figure 1

Figure 1. Changes in cooperation levels caused by endowing a fraction p of agents in a cooperation game with c times more resources than others. Highlighting the potential benefits of wealth heterogeneity for a society of agents, the figures shows how, for example, giving just 10% of players three times more resources than others raises cooperation from 0% to 20%.

An investigation of the joint evolution of altruistic cooperation and dispersal strategies in metapopulations consisting of small local populations, showed how this can lead to four qualitatively different evolutionary outcomes [12]. By contrast, there was an analysis of how nonlinear production functions may lead to convergence stable mixed strategies, but not to evolutionary branching [13].

A review of the historic role of Richard Alexander in introducing the concept of a system of indirect reciprocity based on reputation assessment was conducted [14]. Since Alexander’s pioneering contributions, this approach has come a long way, with EEP having added significantly to the last 15 years of burgeoning research. For instance, in 2013 a specific assessment system was analyzed, stern judging, unveiling that it is unfavorably sensitive to assessment errors [15].

From the art of modelling to the modelling of art. Two studies introduced coupled ordinary differential equations to describe the dynamics of interpersonal relationships, and confirming the utility of such descriptions through case studies of famous literary figures [16] [17].


[1] Zhang B, Li C, de Silva H, Bednarik P & Sigmund K (2013). The evolution of sanctioning institutions: An experimental approach to the social contract. Experimental Economics, in press. doi: 10.1007/s10683-013-9367-7.
[2] Sasaki T (2013). The evolution of cooperation through institutional incentives and optional participation. Dynamic Games and Applications, in press. doi: 10.1007/s13235-013-0094-7.
[3] Sasaki T & Uchida S (2013). The evolution of cooperation by social exclusion. Proceedings of the Royal Society B 280: 20122498.
[4] Sasaki T & Uchida S (2014). Rewards and the evolution of cooperation in public good games. Biology Letters 10: 20130903.
[5] Chen XJ, Gross T & Dieckmann U (2013). Shared rewarding overcomes defection traps in generalized volunteer’s dilemmas. Journal of Theoretical Biology 335: 13–21.
[6] Chen XJ, Sasaki T, Brännström Å & Dieckmann U. First carrot, then stick: How the adaptive hybridization of incentives promotes cooperation, in revision.
[7] Hilbe C, Nowak MA & Sigmund K (2013). Evolution of extortion in iterated prisoner’s dilemma games. Proceedings of the National Academy of Sciences of the USA 110: 6913–6918.
[8] Liu YK, Chen XJ, Zhang L, Tao F & Wang L (2013). Social selection of game organizers promotes cooperation in spatial public goods games. EPL 102: 50006.
[9] Liu YK, Zhang L, Chen XJ, Ren L & Wang L (2013). Cautious strategy update promotes cooperation in spatial prisoner’s dilemma game. Physica A: Statistical Mechanics and its Applications 392: 3640–3647.
[10] Wang XF, Chen XJ, Gao J & Wang L (2013). Reputation-based mutual selection rule promotes cooperation in spatial threshold public goods games. Chaos Solutons and Fractals 56: 181–187.
[11] Kun and Dieckmann (2013). Resource heterogeneity can facilitate cooperation. Nature Communications, 4:2453 (3 October 2013).
[12] Parvinen K, Heino M & Dieckmann U (2013). Function-valued adaptive dynamics and optimal control theory. Journal of Mathematical Biology 67: 509–533.
[13] Zhang YL, Wu T, Chen XJ, Xie GM & Wang L (2013). Mixed strategy under generalized public goods games. Journal of Theoretical Biology 334: 52–60.
[14] Sigmund K (2013). The basis of morality: Richard Alexander on indirect reciprocity. In Summers K & Crespi B eds. Human Social Evolution: The Foundational Works of Richard D. Alexander, Oxford University Press, UK, pp. 199–208.
[15] Uchida S & Sasaki T (2013). Effect of assessment error and private information on stern-judging in indirect reciprocity. Chaos Solitons and Fractals 56: 175–180.
[16] Rinaldi S, Della Rossa F & Landi P (2013). A mathematical model of “Gone with the Wind”. Physica A: Statistical Mechanics and its Applications 392: 3231–3239.
[17] Rinaldi S, Della Rossa F & Landi P (2014). A mathematical model of “Pride and Prejudice”. Nonlinear Dynamics, Psychology and Life Sciences 18: 199–211.

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Last edited: 22 May 2014


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