scholarly journals Friendly-rivalry solution to the iterated n-person public-goods game

2021 ◽  
Vol 17 (1) ◽  
pp. e1008217
Author(s):  
Yohsuke Murase ◽  
Seung Ki Baek
Keyword(s):  
Nash Equilibrium ◽  
Public Goods ◽  
The Other ◽  
Fixation Probability ◽  
Public Goods Game ◽  
Excellent Performance ◽  
Repeated Interaction ◽  
Evolutionary Simulation ◽  
Evolutionary Robustness ◽  
Full Cooperation

Repeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a ‘friendly-rivalry’ strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner’s Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n-person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m = 2n − 1 rounds. A friendly-rivalry strategy for n = 2 inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of a neutral mutant. Our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions when n = 2 and 3.

scholarly journals Friendly-rivalry solution to the iterated n-person public-goods game

2020 ◽  
Author(s):  
Yohsuke Murase ◽  
Seung Ki Baek
Keyword(s):  
Public Goods ◽  
Social Dilemma ◽  
Difficult Problem ◽  
The Other ◽  
Public Goods Game ◽  
Neutral Drift ◽  
Repeated Interaction ◽  
Evolutionary Simulation ◽  
Full Cooperation

AbstractRepeated interaction promotes cooperation among rational individuals under the shadow of future, but it is hard to maintain cooperation when a large number of error-prone individuals are involved. One way to construct a cooperative Nash equilibrium is to find a ‘friendly rivalry’ strategy, which aims at full cooperation but never allows the co-players to be better off. Recently it has been shown that for the iterated Prisoner’s Dilemma in the presence of error, a friendly rival can be designed with the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish defection, recover cooperation if you find a chance, and defect in all the other circumstances. In this work, we construct such a friendly-rivalry strategy for the iterated n-person public-goods game by generalizing those five rules. The resulting strategy makes a decision with referring to the previous m = 2n − 1 rounds. A friendly-rivalry strategy inherently has evolutionary robustness in the sense that no mutant strategy has higher fixation probability in this population than that of neutral drift, and our evolutionary simulation indeed shows excellent performance of the proposed strategy in a broad range of environmental conditions.Author summaryHow to maintain cooperation among a number of self-interested individuals is a difficult problem, especially if they can sometimes commit error. In this work, we propose a strategy for the iterated n-person public-goods game based on the following five rules: Cooperate if everyone did, accept punishment for your own mistake, punish others’ defection, recover cooperation if you find a chance, and defect in all the other circumstances. These rules are not far from actual human behavior, and the resulting strategy guarantees three advantages: First, if everyone uses it, full cooperation is recovered even if error occurs with small probability. Second, the player of this strategy always never obtains a lower long-term payoff than any of the co-players. Third, if the co-players are unconditional cooperators, it obtains a strictly higher long-term payoff than theirs. Therefore, if everyone uses this strategy, no one has a reason to change it. Furthermore, our simulation shows that this strategy will become highly abundant over long time scales due to its robustness against the invasion of other strategies. In this sense, the repeated social dilemma is solved for an arbitrary number of players.

scholarly journals Transparency, asymmetric information and cooperation

2020 ◽  
Vol 50 (2) ◽  
pp. 267-294
Author(s):  
Gianna Lotito ◽  
Matteo Migheli ◽  
Guido Ortona
Keyword(s):  
Asymmetric Information ◽  
Public Goods ◽  
Social Behaviour ◽  
Partial Information ◽  
Relative Performance ◽  
The Other ◽  
Competitive Environment ◽  
Full Information ◽  
Public Goods Game ◽  
Per Se

Abstract We inquire experimentally whether asymmetric information in competitive settings and competition per se influence individual social behaviour. Participants perform a task and are remunerated according to two schemes, a non-competitive and a competitive one, then they play a standard public goods game. In the first scheme participants earn a flat remuneration, in the other they are ranked according to their performance and remunerated accordingly. Information about ranking and income before the game is played varies across three different treatments. We find that competition per se does not affect the amount of contribution. The time spent to choose how much to contribute is negatively correlated with the decision of cooperating fully. The main result is that full information about the relative performance in the competitive environment enhances the cooperation, while partial information reduces it.

The Analytics of Human Sociality

2014 ◽  
Author(s):  
Herbert Gintis
Keyword(s):  
Public Goods ◽  
Real Life ◽  
Folk Theorem ◽  
The Other ◽  
Signal Quality ◽  
Public Goods Game ◽  
Average Quality ◽  
The Public ◽  
High Degree

The folk theorem requires that each action taken by each player carry a signal that is conveyed to the other players. A signal is imperfect if all players receive the same signal; the signal is perfect if it accurately reports the player's action. The question of the signal quality required to obtain efficient cooperation is especially critical when the size of the game is considered. Generally, the folk theorem does not even mention the number of players, but in most situations in real life, the larger the number of players participating in a cooperative endeavor, the lower the average quality of the cooperation vs. defection signal because generally a player observes only a small number of other players with a high degree of accuracy, however large the group involved. This chapter explores this issue and illustrates the problem by applying the Fudenberg et al. (1994) framework to the Public Goods Game, which in many respects is representative of contexts for cooperation in humans.

Donating money is not the only way to sustain cooperation in public goods game

2017 ◽  
Vol 28 (12) ◽  
pp. 1750149 ◽  
Author(s):  
Tong Chen ◽  
Zheng-Hong Wu ◽  
Le Wang
Keyword(s):  
Public Goods ◽  
The Other ◽  
Evolution Of Cooperation ◽  
Public Goods Game ◽  
Time Model ◽  
Research Cooperation ◽  
Public Goods Games ◽  
Cooperation Level ◽  
Set Up ◽  
Better Than

Most of the previous studies research cooperation mainly based on donating money in social public goods games. Owing to the lack of income, some people prefer to donate time instead of money to promote the activity, in our daily life. Motivated by this fact, we here investigate the influence of the encouragement of donating time on the evolution of cooperation based on village opera. In our study, we set up two models: one is money-only model (MOM). Donating money is the only choice in MOM. The other is money–time model (MTM). Besides donating money, donating time is an alternative in MTM. Through numerical simulations, we find that compared to MOM, MTM has a faster speed to reach cooperation equilibrium and cost advantage to sustain the same cooperation level, without the effects of income, reputation, satisfaction, emotion and maximum nonmonetary input. However, it should be noted that MTM is better than MOM in a moderate interval of general budget [Formula: see text]. Our results provide stark evidence that the encouragement of donating time can promote and sustain cooperation better than only donating money.

scholarly journals Computing Equilibria in Binary Networked Public Goods Games

2020 ◽  
Vol 34 (02) ◽  
pp. 2310-2317
Author(s):  
Sixie Yu ◽  
Kai Zhou ◽  
Jeffrey Brantingham ◽  
Yevgeniy Vorobeychik
Keyword(s):  
Nash Equilibrium ◽  
Public Goods ◽  
Public Good ◽  
Pure Strategy ◽  
Public Goods Game ◽  
Public Goods Games ◽  
Space Limitation ◽  
Np Complete ◽  
Graphical Structure ◽  
Strategy Nash Equilibrium

Public goods games study the incentives of individuals to contribute to a public good and their behaviors in equilibria. In this paper, we examine a specific type of public goods game where players are networked and each has binary actions, and focus on the algorithmic aspects of such games. First, we show that checking the existence of a pure-strategy Nash equilibrium is NP-complete. We then identify tractable instances based on restrictions of either utility functions or of the underlying graphical structure. In certain cases, we also show that we can efficiently compute a socially optimal Nash equilibrium. Finally, we propose a heuristic approach for computing approximate equilibria in general binary networked public goods games, and experimentally demonstrate its effectiveness. Due to space limitation, some proofs are deferred to the extended version1.

The incumbent, challenger, and population during revolution and civil war

2019 ◽  
Vol 14 (2) ◽  
Author(s):  
Kjell Hausken ◽  
Mthuli Ncube
Keyword(s):  
Civil War ◽  
Public Goods ◽  
Arab Spring ◽  
The Other ◽  
Time Period ◽  
Geographic Regions

We consider revolutions and civil war involving an incumbent, a challenger, and the population. Revolutions are classified into eight outcomes. In four outcomes incumbent repression occurs (viewed as providing sub-threshold benefits such as public goods to the population). Accommodation occurs in the other four outcomes (benefits provision above a threshold). The incumbent and challenger fight each other. The incumbent may win and retain power or else lose, thereby causing standoff or coalition. In a standoff, which is costly, no one backs down and uncertainty exists about who is in power. In a coalition, which is less costly, the incumbent and challenger cooperate, compromise, and negotiate their differences. If the population successfully revolts against the incumbent, the challenger replaces the incumbent. Eighty-seven revolutions during 1961–2011, including the recent Arab spring revolutions, are classified into the eight outcomes. When repressive, the incumbent loses 46 revolutions, remains in power through 21 revolutions, and builds a coalition after 12 revolutions. When accommodative, the incumbent loses seven revolutions and builds a coalition after one revolution. The 87 revolutions are classified across geographic regions and by time-period.

Sign in / Sign up

Export Citation Format

Share Document