scholarly journals Direct Reciprocity and Model-Predictive Strategy Update Explain the Network Reciprocity Observed in Socioeconomic Networks

Games ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 16
Author(s):  
Fabio Della Rossa ◽  
Fabio Dercole ◽  
Anna Di Meglio
Keyword(s):  
Evolutionary Process ◽  
Theoretical Models ◽  
Evolution Of Cooperation ◽  
Conditional Cooperation ◽  
Social Experiments ◽  
Best Response ◽  
Cooperative Agents ◽  
Influential Paper ◽  
Tit For Tat ◽  
Response Rule

Network reciprocity has been successfully put forward (since M. A. Nowak and R. May’s, 1992, influential paper) as the simplest mechanism—requiring no strategical complexity—supporting the evolution of cooperation in biological and socioeconomic systems. The mechanism is actually the network, which makes agents’ interactions localized, while network reciprocity is the property of the underlying evolutionary process to favor cooperation in sparse rather than dense networks. In theoretical models, the property holds under imitative evolutionary processes, whereas cooperation disappears in any network if imitation is replaced by the more rational best-response rule of strategy update. In social experiments, network reciprocity has been observed, although the imitative behavior did not emerge. What did emerge is a form of conditional cooperation based on direct reciprocity—the propensity to cooperate with neighbors who previously cooperated. To resolve this inconsistency, network reciprocity has been recently shown in a model that rationally confronts the two main behaviors emerging in experiments—reciprocal cooperation and unconditional defection—with rationality introduced by extending the best-response rule to a multi-step predictive horizon. However, direct reciprocity was implemented in a non-standard way, by allowing cooperative agents to temporarily cut the interaction with defecting neighbors. Here, we make this result robust to the way cooperators reciprocate, by implementing direct reciprocity with the standard tit-for-tat strategy and deriving similar results.

Evolution of extortion in the social-influenced prisoner’s dilemma

2016 ◽  
Vol 30 (04) ◽  
pp. 1650029 ◽  
Author(s):  
Zhipeng Wang ◽  
Miao Li ◽  
Dan Wang ◽  
Qinghe Chen
Keyword(s):  
Social Influence ◽  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Evolution Of Cooperation ◽  
Complete Knowledge ◽  
Best Response ◽  
The Social ◽  
Mixed Populations ◽  
Evolutionarily Stable ◽  
Response Rule

The introduction of extortion strategy has attracted much attention since it dominates any evolutionary opponent in iterated prisoner’s dilemma games. Despite several studies argue that extortion is difficult to survive under strategy imitation and birth–death updating rules in well-mixed populations, it has recently been proven that a myopic best response rule facilitate the evolution of cooperation and extortion. However, such updating rules require a strong assumption of complete knowledge of all players, which is unlikely to hold in social networks in reality. To solve this problem, we introduce the concept of social influence into the model to limit players’ knowledge within their neighborhood. It turns out that this myopia initiated by social influence prevents players from observing superior strategies and therefore enables cooperators and extortioners to be evolutionarily stable. We also suggest that heterogeneous networks contribute to the evolution of cooperation and extortion under such social influence.

TIT FOR TAT in sticklebacks and the evolution of cooperation

Nature ◽  
1987 ◽  
Vol 325 (6103) ◽  
pp. 433-435 ◽  
Author(s):  
Manfred Milinski
Keyword(s):  
Evolution Of Cooperation ◽  
Tit For Tat

scholarly journals Negotiation and appeasement can be more effective drivers of sociality than kin selection

2016 ◽  
Vol 371 (1687) ◽  
pp. 20150089 ◽  
Author(s):  
Andrés E. Quiñones ◽  
G. Sander van Doorn ◽  
Ido Pen ◽  
Franz J. Weissing ◽  
Michael Taborsky
Keyword(s):  
Genetic Relatedness ◽  
Structured Populations ◽  
Evolution Of Cooperation ◽  
Conditional Cooperation ◽  
Negotiation Strategies ◽  
Structured Population ◽  
The Face ◽  
Kin Structure ◽  
Invasion Analysis ◽  
Individual Based Simulation

Two alternative frameworks explain the evolution of cooperation in the face of conflicting interests. Conflicts can be alleviated by kinship, the alignment of interests by virtue of shared genes, or by negotiation strategies, allowing mutually beneficial trading of services or commodities. Although negotiation often occurs in kin-structured populations, the interplay of kin- and negotiation-based mechanisms in the evolution of cooperation remains an unresolved issue. Inspired by the biology of a cooperatively breeding fish, we developed an individual-based simulation model to study the evolution of negotiation-based cooperation in relation to different levels of genetic relatedness. We show that the evolution of negotiation strategies leads to an equilibrium where subordinates appease dominants by conditional cooperation, resulting in high levels of help and low levels of aggression. This negotiation-based equilibrium can be reached both in the absence of relatedness and in a kin-structured population. However, when relatedness is high, evolution often ends up in an alternative equilibrium where subordinates help their kin unconditionally. The level of help at this kin-selected equilibrium is considerably lower than at the negotiation-based equilibrium, and it corresponds to a level reached when responsiveness is prevented from evolving in the simulations. A mathematical invasion analysis reveals that, quite generally, the alignment of payoffs due to the relatedness of interaction partners tends to impede selection for harsh but effective punishment of defectors. Hence kin structure will often hamper rather than facilitate the evolution of productive cooperation.

scholarly journals Optimal Tag-Based Cooperation Control for the “Prisoner’s Dilemma”

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Rui Dong ◽  
Xinghong Jia ◽  
Xianjia Wang ◽  
Yonggang Chen
Keyword(s):  
Social Sciences ◽  
Rate Control ◽  
Prisoner's Dilemma ◽  
Replicator Dynamics ◽  
Prisoner’S Dilemma ◽  
Evolutionary Process ◽  
Evolution Of Cooperation ◽  
Optimal Timing ◽  
Terminal Time ◽  
Cooperation Rate

A long-standing problem in biology, economics, and social sciences is to understand the conditions required for the emergence and maintenance of cooperation in evolving populations. This paper investigates how to promote the evolution of cooperation in the Prisoner’s Dilemma game (PDG). Differing from previous approaches, we not only propose a tag-based control (TBC) mechanism but also look at how the evolution of cooperation by TBC can be successfully promoted. The effect of TBC on the evolutionary process of cooperation shows that it can both reduce the payoff of defectors and inhibit defection; although when the cooperation rate is high, TBC will also reduce the payoff of cooperators unless the identified rate of the TBC is large enough. An optimal timing control (OTC) of switched replicator dynamics is designed to consider the control costs, the cooperation rate at terminal time, and the cooperator’s payoff. The results show that the switching control (SC) between an optimal identified rate control of the TBC and no TBC can properly not only maintain a high cooperation rate but also greatly enhance the payoff of the cooperators. Our results provide valuable insights for some clusters, for example, logistics parks and government, to regard the decision to promote cooperation.

Three Perspectives on Multi-Agent Reinforcement Learning

2011 ◽  
pp. 234-246 ◽  
Author(s):  
Yang Gao ◽  
Hao Wang
Keyword(s):  
Reinforcement Learning ◽  
General Framework ◽  
Mutual Interaction ◽  
Equilibrium Solutions ◽  
Best Response ◽  
Cooperative Agents ◽  
Multi Agent

This chapter concludes three perspectives on multi-agent reinforcement learning (MARL): (1) cooperative MARL, which performs mutual interaction between cooperative agents; (2) equilibrium-based MARL, which focuses on equilibrium solutions among gaming agents; and (3) best-response MARL, which suggests a no-regret policy against other competitive agents. Then the authors present a general framework of MARL, which combines all the three perspectives in order to assist readers in understanding the intricate relationships between different perspectives. Furthermore, a negotiation-based MARL algorithm based on meta-equilibrium is presented, which can interact with cooperative agents, games with gaming agents, and provides the best response to other competitive agents.

scholarly journals Evolution of Groupwise Cooperation: Generosity, Paradoxical Behavior, and Non-Linear Payoff Functions

Games ◽  
2018 ◽  
Vol 9 (4) ◽  
pp. 100 ◽  
Author(s):  
Shun Kurokawa ◽  
Joe Yuichiro Wakano ◽  
Yasuo Ihara
Keyword(s):  
Prisoner's Dilemma ◽  
Prisoner’S Dilemma ◽  
Evolutionary Model ◽  
Repeated Game ◽  
Evolution Of Cooperation ◽  
Fixation Probability ◽  
Non Linear ◽  
Repeated Prisoner’S Dilemma ◽  
Tit For Tat ◽  
Repeated Prisoner's Dilemma

Evolution of cooperation by reciprocity has been studied using two-player and n-player repeated prisoner’s dilemma games. An interesting feature specific to the n-player case is that players can vary in generosity, or how many defections they tolerate in a given round of a repeated game. Reciprocators are quicker to detect defectors to withdraw further cooperation when less generous, and better at maintaining a long-term cooperation in the presence of rare defectors when more generous. A previous analysis on a stochastic evolutionary model of the n-player repeated prisoner’s dilemma has shown that the fixation probability of a single reciprocator in a population of defectors can be maximized for a moderate level of generosity. However, the analysis is limited in that it considers only tit-for-tat-type reciprocators within the conventional linear payoff assumption. Here we extend the previous study by removing these limitations and show that, if the games are repeated sufficiently many times, considering non-tit-for-tat type strategies does not alter the previous results, while the introduction of non-linear payoffs sometimes does. In particular, under certain conditions, the fixation probability is maximized for a “paradoxical” strategy, which cooperates in the presence of fewer cooperating opponents than in other situations in which it defects.

International Cooperation: Testing Evolution of Cooperation Theories

2017 ◽  
Vol 23 (1) ◽  
Author(s):  
Jeremy Bowling
Keyword(s):  
International Cooperation ◽  
Evolution Of Cooperation ◽  
Indirect Reciprocity ◽  
Cooperative Action ◽  
Tit For Tat

AbstractThe evolution of cooperation scholarship develops evolutionary stable theories that explain the presence of cooperation when there are many reasons to defect from cooperation. In this analysis, these theories are tested using the relations between states. Focusing on the direct reciprocity strategies of Tit-for-Tat and Win-stay/Lose-shift and the indirect reciprocity strategies of Cooperative Reputation and Tag, Tit-for-Tat and Cooperative Reputation are found to be robust, while Tags have mixed results. In the end, it is the direct cooperative action by states and their cooperative reputation and not shared characteristics that are most likely to elicit cooperative action in return.

scholarly journals The interplay of cognition and cooperation

2010 ◽  
Vol 365 (1553) ◽  
pp. 2699-2710 ◽  
Author(s):  
Sarah F. Brosnan ◽  
Lucie Salwiczek ◽  
Redouan Bshary
Keyword(s):  
Cognitive Abilities ◽  
Cognitive Complexity ◽  
Convincing Evidence ◽  
The Other ◽  
Evolution Of Cooperation ◽  
Social Environments ◽  
Average Gain ◽  
Central Nervous Systems ◽  
Tit For Tat ◽  
Key Variables

Cooperation often involves behaviours that reduce immediate payoffs for actors. Delayed benefits have often been argued to pose problems for the evolution of cooperation because learning such contingencies may be difficult as partners may cheat in return. Therefore, the ability to achieve stable cooperation has often been linked to a species' cognitive abilities, which is in turn linked to the evolution of increasingly complex central nervous systems. However, in their famous 1981 paper, Axelrod and Hamilton stated that in principle even bacteria could play a tit-for-tat strategy in an iterated Prisoner's Dilemma. While to our knowledge this has not been documented, interspecific mutualisms are present in bacteria, plants and fungi. Moreover, many species which have evolved large brains in complex social environments lack convincing evidence in favour of reciprocity. What conditions must be fulfilled so that organisms with little to no brainpower, including plants and single-celled organisms, can, on average, gain benefits from interactions with partner species? On the other hand, what conditions favour the evolution of large brains and flexible behaviour, which includes the use of misinformation and so on? These questions are critical, as they begin to address why cognitive complexity would emerge when ‘simple’ cooperation is clearly sufficient in some cases. This paper spans the literature from bacteria to humans in our search for the key variables that link cooperation and deception to cognition.

scholarly journals Social eavesdropping and the evolution of conditional cooperation and cheating strategies

2010 ◽  
Vol 365 (1553) ◽  
pp. 2675-2686 ◽  
Author(s):  
Ryan L. Earley
Keyword(s):  
Selection Pressure ◽  
Evolution Of Cooperation ◽  
Condition Dependence ◽  
Cooperative Behaviour ◽  
Conditional Cooperation ◽  
Positive Selection Pressure ◽  
Social Animals ◽  
Signalling Systems ◽  
Evolutionarily Stable ◽  
Behavioural Strategies

The response of bystanders to information available in their social environment can have a potent influence on the evolution of cooperation and signalling systems. In the presence of bystanders, individuals might be able to increase their payoff by exaggerating signals beyond their means (cheating) or investing to help others despite considerable costs. In doing so, animals can accrue immediate benefits by manipulating (or helping) individuals with whom they are currently interacting and delayed benefits by convincing bystanders that they are more fit or cooperative than perhaps is warranted. In this paper, I provide some illustrative examples of how bystanders could apply added positive selection pressure on both cooperative behaviour and dishonest signalling during courtship or conflict. I also discuss how the presence of bystanders might select for greater flexibility in behavioural strategies (e.g. conditional or condition dependence), which could maintain dishonesty at evolutionarily stable frequencies under some ecological conditions. By recognizing bystanders as a significant selection pressure, we might gain a more realistic approximation of what drives signalling and/or interaction dynamics in social animals.

The spatial struggle of tit-for-tat and defect

1995 ◽  
Vol 348 (1326) ◽  
pp. 393-404 ◽  
Keyword(s):  
Game Theory ◽  
Stationary State ◽  
Evolution Of Cooperation ◽  
Space And Time ◽  
Stable Coexistence ◽  
Spatially Inhomogeneous ◽  
Biological Reality ◽  
Tit For Tat ◽  
Spatially Homogeneous ◽  
Homogeneous Environment

The pioneering work by Trivers (1971), Axelrod (1984) and Axelrod & Hamilton (1981) has stimulated continuing interest in explaining the evolution of cooperation by game theory, in particular, the iterated prisoner’s dilemma and the strategy of tit-for-tat. However these models suffer from a lack of biological reality, most seriously because it is assumed that players meet opponents at random from the population and, unless the population is very small, this excludes the repeated encounters necessary for tit-for-tat to prosper. To meet some of the objections, we consider a model with two types of players, defectors (D) and tit-for-tat players (T), in a spatially homogeneous environment with player densities varying continuously in space and time. Players only encounter neighbours but move at random in space. The analysis demonstrates major new conclusions, the three most important being as follows. First, stable coexistence with constant densities of both players is possible. Second, stable coexistence in a pattern (a spatially inhomogeneous stationary state) may be possible when it is impossible for constant distributions (even unstable ones) to exist. Third, invasion by a very small number of T-players is sometimes possible (in contrast with the usual predictions) and so a mutation to tit-for-tat may lead to a population of defectors being displaced by the T-players.

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