Evolution Of Cooperation Research Articles

Ecology and the evolution of cooperation by partner choice and reciprocity

Organisms help each other to get resources, protection from enemies, and other goods, but not as much as would be best for their population. Partner choice, direct reciprocity and indirect reciprocity foster cooperation and help to align individual interests with the social good. However, we still do not know what ecological variables affect their success and interaction. I simulated the evolution of partner choice, direct reciprocity and indirect reciprocity, and the production of a good that partners donate to each other. I show that, with few exceptions, partner choice evolves whenever there is an initial social dilemma, under a wider range of conditions than direct reciprocity. Direct reciprocity is deleterious when the shared good is highly essential or very influential. Both partner choice and direct reciprocity compel individuals to produce close to the socially optimal quantity of the shared good. Direct reciprocity does so even when it is deleterious and reciprocators are rare. Indirect reciprocity succeeds when individuals can also choose partners, and in most cases contributes less than partner choice or direct reciprocity to alleviating social dilemmas. Partner choice may have allowed humans to use a set of collectively produced goods including clothing, fire, hunting tools, housing, and shared knowledge, to the point that they became essential.

Repeated games with partner choice.

Repetition is a classic mechanism for the evolution of cooperation. The standard way to study repeated games is to assume that there is an exogenous probability with which every interaction is repeated. If it is sufficiently likely that interactions are repeated, then reciprocity and cooperation can evolve together in repeated prisoner's dilemmas. Who individuals interact with can however also be under their control, or at least to some degree. If we change the standard model so that it allows for individuals to terminate the interaction with their current partner, and find someone else to play their prisoner's dilemmas with, then this limits the effectiveness of disciplining each other within the partnership, as one can always leave to escape punishment. The option to leave can however also be used to get away from someone who is not cooperating, which also has a disciplining effect. We find that the net effect of introducing the option to leave on cooperation is positive; with the option to leave, the average amount of cooperation that evolves in simulations is substantially higher than without. One of the reasons for this increase in cooperation is that partner choice creates endogenous phenotypic assortment. Compared to the standard models for the co-evolution of reciprocity and cooperation, and models of kin selection, our model thereby produces a better match with many forms of human cooperation in repeated settings. Individuals in our model end up interacting, not with random others that they cannot separate from, once matched, or with others that they are genetically related to, but with partners that they choose to stay with, and that are similarly dependable not to play defect as they are themselves.

Evolutionary dynamics of cooperation driven by a mixed update rule in structured prisoner's dilemma games.

How to understand the evolution of cooperation remains a scientific challenge. Individual strategy update rule plays an important role in the evolution of cooperation in a population. Previous works mainly assume that individuals adopt one single update rule during the evolutionary process. Indeed, individuals may adopt a mixed update rule influenced by different preferences such as payoff-driven and conformity-driven factors. It is still unclear how such mixed update rules influence the evolutionary dynamics of cooperation from a theoretical analysis perspective. In this work, in combination with the pairwise comparison rule and the conformity rule, we consider a mixed updating procedure into the evolutionary prisoner's dilemma game. We assume that individuals adopt the conformity rule for strategy updating with a certain probability in a structured population. By means of the pair approximation and mean-field approaches, we obtain the dynamical equations for the fraction of cooperators in the population. We prove that under weak selection, there exists one unique interior equilibrium point, which is stable, in the system. Accordingly, cooperators can survive with defectors under the mixed update rule in the structured population. In addition, we find that the stationary fraction of cooperators increases as the conformity strength increases, but is independent of the benefit parameter. Furthermore, we perform numerical calculations and computer simulations to confirm our theoretical predictions.

Spatial reciprocity under reinforcement learning mechanism.

At present, the research on the dynamics of cooperative behavior of agents under reinforcement learning mechanism either assumes that agents have global interaction, that is, agents interact with all other agents in the population, or directly study the influence of relevant factors on cooperation evolution based on the local interaction in a network structure. It neglects to formally study how the limitation of agents that only interact with local agents affects their strategy choice. Thus, in this paper, we study the cooperative behavior of agents in a typical social decision-making environment with conflicts between individual interests and collective interests. On the one hand, a programmed game model in game theory, namely, prisoner's dilemma game, is used to capture the essence of real-world dilemmas. On the other hand, the effects of local and global strategy learning on the cooperative evolution of agents are investigated separately, and the nature of spatial reciprocity under the reinforcement learning mechanism is found. Specifically, when there is no inherent connection between the interacting agents and the learning agents within the system, the network structure has a limited effect on promoting cooperation. It is only when there is an overlap between the interacting agents and the learning agents that the spatial reciprocity effect observed in the traditional evolutionary game theory can be fully realized.

Cooperative evolution with reward-based heterogeneous tax in spatial public goods games

Cooperative evolution with reward-based heterogeneous tax in spatial public goods games

High Cost of Survival Promotes the Evolution of Cooperation

High Cost of Survival Promotes the Evolution of Cooperation

Donations triggered by inequality tolerance affect the evolution of cooperation in spatial public goods game.

Generosity through donation plays a crucial role in reducing inequality and influencing human behavior. However, previous research on donation has overlooked individuals' acceptance of the extent of inequality, which acts as a trigger for donation. To address this gap, this paper systematically explores the impact of donation based on inequality tolerance on the evolution of cooperation in spatial public goods game. Specifically, donation occurs only when an individual's payoff advantage exceeds her inequality tolerance. The results show that donation patterns are crucial for the emergence and stability of cooperation. In the enduring period, the defector-to-cooperator donation pattern helps to form cooperative clusters. In the expanding period, cooperator-to-cooperator, defector-to-defector, and defector-to-cooperator donation patterns create a stable three-layer structure through self-organization, providing a payoff advantage to boundary cooperators. As donation ratio increases, the three-layer structure provides a greater payoff advantage to boundary cooperators, leading to an increase in cooperation. As inequality tolerance increases, changes in donation patterns weaken the three-layer structure, causing cooperation to decrease or disappear through discontinuous phase transitions. Subsequently, all critical points of discontinuous phase transitions are identified by specific spatial configurations. In addition, the influence of donation patterns on the evolution of cooperation is robust, even in heterogeneous small-world networks. This paper offers valuable insights into the dynamics of cooperation evolution and the role of donation in shaping behavior.

Cooperating or Kicking Out: Defending against Poisoning Attacks in Federated Learning via the Evolution of Cooperation

Cooperating or Kicking Out: Defending against Poisoning Attacks in Federated Learning via the Evolution of Cooperation

Fabrication of core-shell Prussian blue analogue@ZnIn2S4 nanocubes for efficient photocatalytic hydrogen evolution coupled with biomass furfuryl alcohol oxidation.

Utilizing photocatalytic technology for the value-added conversion of biomass derivatives, alongside the production of clean hydrogen energy, represents a viable approach to addressing energy and environmental challenges. However, the design of cost-effective and efficient photocatalysts remains a significant obstacle. In this work, we employed open-framework Prussian blue analogs as co-catalytic centers and combined them with ZnIn2S4 to construct a series of core-shell nanocube photocatalysts with varying metal compositions. This unique structure provides abundant photocatalytic redox-active sites and effectively facilitates the separation and transfer of photoinduced charges. By examining the oxidation of furfuryl alcohol (FOL) to furfural (FAL) with cooperative H2 evolution, the optimal Ni-Co PBA@ZnIn2S4 sample exhibited remarkable catalytic activity, achieving H2 and FAL yields of 739.3 and 705.2 μmol g-1 h-1, respectively, which is approximately four times greater than that achieved with bare ZnIn2S4. This study offers valuable insights into the design of photocatalysts and the selection of co-catalytic metal centers.

Effects of third-order reputation mechanism on the dynamic evolution of cooperation in mixed-games

Effects of third-order reputation mechanism on the dynamic evolution of cooperation in mixed-games

Evolutionary game on mutually influenceing double-layer network.

In recent years, coupled double-layer networks have played an increasingly critical role in evolutionary game theory. Research indicates that these networks more accurately reflect real-world relationships between individuals. However, current studies mainly focus on unidirectional influence within double-layer networks. Based on this, we propose a strongly coupled double-layer network cooperation evolution model. Strength individuals are located in the upper network layer, influencing the strategy choices of ordinary individuals in the lower layer, and vice versa. Monte Carlo simulations show that strength individuals can effectively enhance overall group cooperation. Under low temptation to defect, the group maintains a high cooperation rate; under high temptation, the presence of strength individuals prevents the group from falling into total defection, helping ordinary individuals escape the defection dilemma and improve cooperation levels.

Evolution of cooperation in multichannel games on multiplex networks.

Humans navigate diverse social relationships and concurrently interact across multiple social contexts. An individual's behavior in one context can influence behavior in other contexts. Different payoffs associated with interactions in the different domains have motivated recent studies of the evolution of cooperation through the analysis of multichannel games where each individual is simultaneously engaged in multiple repeated games. However, previous investigations have ignored the potential role of network structure in each domain and the effect of playing against distinct interacting partners in different domains. Multiplex networks provide a useful framework to represent social interactions between the same set of agents across different social contexts. We investigate the role of multiplex network structure and strategy linking in multichannel games on the spread of cooperative behavior in all layers of the multiplex. We find that multiplex structure along with strategy linking enhances the cooperation rate in all layers of the multiplex compared to a well-mixed population in Prisoners' Dilemma games, provided the network structure is identical across layers. The effectiveness of strategy linking in enhancing cooperation depends on the degree of similarity of the network structure across the layers and perception errors due to imperfect memory. Higher cooperation rates are achieved when the degree of structural overlap of the different layers is sufficiently large, and the probability of perception error is relatively low. Our work reveals how the social network structure in different layers of a multiplex can affect the spread of cooperation by limiting the ability of individuals to link strategies across different social domains.

The Evolution of US-Qatar Political-Military Co-operation: From a Security Agreement to a Strategic Partnership

In recent years, Russia has paid special attention to co-operation with the Arab monarchies of the Gulf. Despite pressure from the United States and Western countries, the states of the region have not joined the diplomatic pressure and sanctions regimes. However, not all countries from the Gulf Cooperation Council (GCC) are equally open to deepening co-operation with Russia. For example, Qatar has a more restrained stance on cooperation with Moscow. This is due to special relationship between Doha and Washington. Moments that have contributed to the formation of an essentially allied relationship between the two states are highlighted. Regional situations in which Washington and Doha have acted as close and trusting partners are examined. The study also examines the implications of the evolving of US-Qatar relations for the Middle East..

Density amplifiers of cooperation for spatial games

Spatial games provide a simple and elegant mathematical model to study the evolution of cooperation in networks. In spatial games, individuals reside in vertices, adopt simple strategies, and interact with neighbors to receive a payoff. Depending on their own and neighbors' payoffs, individuals can change their strategy. The payoff is determined by the Prisoners' Dilemma, a classical matrix game, where players cooperate or defect. While cooperation is the desired behavior, defection provides a higher payoff for a selfish individual. There are many theoretical and empirical studies related to the role of the network in the evolution of cooperation. However, the fundamental question of whether there exist networks that for low initial cooperation rate ensure a high chance of fixation, i.e., cooperation spreads across the whole population, has remained elusive for spatial games with strong selection. In this work, we answer this fundamental question in the affirmative by presenting network structures that ensure high fixation probability for cooperators in the strong selection regime. Besides, our structures have many desirable properties: (a) they ensure the spread of cooperation even for a low initial density of cooperation and high temptation of defection, (b) they have constant degrees, and (c) the number of steps, until cooperation spreads, is at most quadratic in the size of the network.

The evolution and hotspots of radioactive iodine therapy in hyperthyroidism: a bibliometric analysis.

Hyperthyroidism, a prevalent endocrine disorder, disrupts metabolic balance and cardiovascular health, affecting millions globally. Radioactive iodine (RAI), a treatment for hyperthyroidism, employs high-energy beta particles to reduce thyroid tissue, lowering volume and hormone levels. This study utilizes bibliometric analysis to outline RAI's evolution and identify hotspots in hyperthyroidism treatment. A total of 2904 articles and reviews published between 1981 and 2023 were retrieved from the Web of Science Core Collection using the research strategy. Bibliometric analyses, employing VOSviewer and CiteSpace, were performed to visualize the cooperation network, evolution, and hot topics. Annual publications rose in waves, 2904 papers from 2564 institutions, and 84 countries. The USA led, contributing the largest share, with the journal Thyroid dominating publication. The University of Pisa contributed the most articles. Co-occurrence analysis classified keywords into five clusters: treatment mechanism, safety, effectiveness assessment, individualized radioactive dosage, and management. The development of RAI therapy for hyperthyroidism can be divided into three stages: safety and efficacy assessment, personalized treatment plans, and treatment of drug-resistant and surgery-resistant hyperthyroidism. Attention to RAI in hyperthyroidism should be significantly increased. It is necessary to establish collaborations between authors, countries, and institutions to promote the development of this field. Recent research has focused on personalized radioactive dosage formulation and follow-up. Future studies are likely to concentrate on drug-resistant and surgery-resistant hyperthyroidism, which is also worthy of investigation. These findings provide a new perspective on the study of RAI in hyperthyroidism, potentially contributing to the improvement of the quality of life for patients with hyperthyroidism.

Conditional cooperation with longer memory

Direct reciprocity is a wide-spread mechanism for the evolution of cooperation. In repeated interactions, players can condition their behavior on previous outcomes. A well-known approach is given by reactive strategies, which respond to the coplayer's previous move. Here, we extend reactive strategies to longer memories. A reactive-n strategy takes into account the sequence of the last n moves of the coplayer. A reactive-n counting strategy responds to how often the coplayer cooperated during the last n rounds. We derive an algorithm to identify the partner strategies within these strategy sets. Partner strategies are those that ensure mutual cooperation without exploitation. We give explicit conditions for all partner strategies among reactive-2, reactive-3 strategies, and reactive-n counting strategies. To further explore the role of memory, we perform evolutionary simulations. We vary several key parameters, such as the cost-to-benefit ratio of cooperation, the error rate, and the strength of selection. Within the strategy sets we consider, we find that longer memory tends to promote cooperation. This positive effect of memory is particularly pronounced when individuals take into account the precise sequence of moves.

Evolution of cooperation with early social influence for explaining collective action.

The logic of collective action has laid a foundation for the research of public choice, and the success of collective action has been a long-term discussion when free-riding mechanism is considered in the dynamics. This study proposes a , which provides a novel dimension for explaining the logic of collective action. Under the framework, the accumulation of early social influence, conformity, and the pressure of relationship updating in small groups is discussed. The experiment results show that the accumulation of early social influence indirectly promotes the participants of collective action; conformity is conducive to stimulating collective action, but relies on the accumulation of early social influence; the pressure of relationship updating plays the small-group role, which promotes the participation of collective actions; all these effects are helpful in forming the cascade of cooperators, and prevent the coexistence of participants and non-participants of collective action.

Effects of value-driven social learning on cooperation in the prisoner's dilemma games.

Despite the growing attention and research on the impact of Q-learning-based strategy updating on the evolution of cooperation, the joint role of individual learners and social learners in evolutionary games has seldom been considered. Here, we propose a value-driven social learning model that incorporates a shape parameter, β, to characterize the degree of radicalism or conservatism in social learning. Using the prisoner's dilemma game on a square lattice as a paradigm, our simulation results show that the cooperation level has a non-trivial dependence of β, density ρ, and dilemma strength b. We find that both β and ρ have nonmonotonic effects on cooperation; specifically, moderate levels of radicalism in social learning can facilitate cooperation remarkably, and when slightly conservative, can form a favorable cooperation region with the appropriate ρ. Moreover, we have demonstrated that social learners play a key role in the formation of network reciprocity, whereas individual learners play a dual role of support and exploitation. Our results reveal a critical balance between individual learning and social learning that can maximize cooperation and provide insights into understanding the collective behavior in multi-agent systems.

Value-behavior inconsistency is robust to promote cooperative behavior in structured populations.

The evolution of cooperation is a theme commonly studied in biology, psychology, sociology, and economics. Mechanisms that promote cooperative behavior in structured populations have been intensively studied. However, individuals' values, specifically, their opinions have been rarely taken into account so far. Inspired by cognition dissonance theory, we assume that individuals pay the cost of guiltiness if the behavior is defection but the opinion deviates from defection, and pay the cost of regret if the behavior is cooperation but the opinion deviates from cooperation. For all general stochastic evolutionary dynamics on arbitrary static networks with multiple opinions, we prove in the weak selection limit that: (i) value-behavior inconsistency cost promotes cooperative behavior if and only if the average cost of regret is less than that of guiltiness; (ii) individuals with value-behavior consistency are more abundant than that with value-behavior inconsistency. This is in contrast with other mechanisms that are at work for cooperation for one population structure but not others. Furthermore, it is also validated on an empirical network and for non-weak selection intensity. The value-behavior inconsistency is thus a robust mechanism to promote cooperative behavior in structured populations. Our results shed light on the importance of the co-evolutionary dynamics of opinion and behavior, which opens an avenue for cooperation.

Promotion of cooperation in a structured population with environmental feedbacks.

Cooperation is a representative altruistic behavior in which individuals contribute public goods to benefit their neighborhoods and even larger communities in social networks. The defective behavior is more likely to bring higher payoffs than the cooperative behavior, which makes the cooperative behavior hard to maintain and sustain. Many mechanisms were proposed to promote cooperation within a social dilemma, in which some recent studies introduced the impact of dynamically changing environments on players' payoffs and strategies in social-ecological systems, and evolutionary-ecological systems. However, degree heterogeneity, an important structural property of many real-world complex networks such as social networks, academic collaboration networks, and communication networks, is rarely explored and studied in such eco-evolutionary games. In this research, we propose a Public Goods Game model on social networks with environmental feedback and analyze how the environmental factor and network structure affect the evolution of cooperation. It is found that as the initial environmental factors and the cooperation-enhancement defection-degradation ratio increase, the steady cooperation level of the social network significantly increases, and the dynamic environment will eventually evolve into a high-return environment; On the other hand, even if the initial environmental benefit coefficient is high, when the cooperation-enhancement defection-degradation ratio is less than a threshold, the dynamic environment will gradually degrade into a low-return environment. The steady cooperation level of the social network first gradually increases as the network structure becomes more heterogeneous, but it will decrease once the heterogeneity of the social network exceeds a certain threshold.