Hawk-Dove Game Research Articles

Evolutionary game for incentivizing social cooperation of prosumers in transactive energy communities

Transactive energy communities offer significant potential for the smart grid’s transition to renewable energy. However, they typically rely on fixed trading contracts between prosumers, which limits flexibility and engagement. Extensive research has been conducted on the mechanisms for implementing transactive energy communities, but there is still limited focus on prosumers’ trading behaviours and their social cooperation in peer-to-peer trading. In this work, we are exploring the potential of evolutionary game theory for modelling the evolution of trading behaviours among community prosumers over time aiming to define a blockchain market mechanism that promotes social cooperation-based P2P interactions. The model, inspired by the Hawk-Dove game, incentivizes prosumers’ cooperative behaviours (Doves) and penalizes prosumers with self-centred trading behaviours (Hawks), fostering social cooperation despite the temptation of higher payoffs from defection. In trading, Doves avoid conflicts and are open to cooperation, while Hawks are not. During a market session, if both prosumers choose the Hawk trading strategy, they are penalized with higher trading costs. If one chooses the Hawk and the other Dove, the Hawk gains all the benefits, and the Dove gains nothing. If both choose Dove, they share the benefits equally. We have evaluated the effectiveness of the solution with a blockchain-based energy marketplace considering realistic scenarios using energy data from prosumers. Results suggest that matched pairs of prosumers in P2P energy transactions gradually shift towards altruistic behaviours. Additionally, at the end of the market session, over 92% of the transactions involve altruistic behaviours, therefore, the prosumers are effectively incentivized to change their behaviour. Moreover, it may significantly increase traded energy in market sessions by up to 50% driven by cooperative trading behaviours of prosumers which unlock higher levels of energy flexibility. Finally, it outperforms the market clearing mechanism in transactions energy prices by up to 3%.

Correlated equilibria and forecasts based on Naïve play in Hawk–Dove games

Correlated equilibria and forecasts based on Naïve play in Hawk–Dove games

The effects of herding and dispersal behaviour on the evolution of cooperation on complete networks

Evolutionary graph theory has considerably advanced the process of modelling the evolution of structured populations, which models the interactions between individuals as pairwise contests. In recent years, these classical evolution models have been extended to incorporate more realistic features, e.g. multiplayer games. A recent series of papers have developed a new evolutionary framework including structure, multiplayer interactions, evolutionary dynamics, and movement. However, so far, the developed models have mainly considered independent movement without coordinated behaviour. Although the theory underlying the framework has been developed and explored in various directions, several movement mechanisms have been produced which characterise coordinated movement, for example, herding. By embedding these newly constructed movement distributions, within the evolutionary setting of the framework, we demonstrate that certain levels of aggregation and dispersal benefit specific types of individuals. Moreover, by extending existing parameters within the framework, we are not only able to develop a general process of embedding any of the considered movement distributions into the evolutionary setting on complete graphs but also analytically produce the probability of fixation of a mutant on a complete N-sized network, for the multiplayer Public Goods and Hawk–Dove games. Also, by applying weak selection methods, we extended existing previous analyses on the pairwise Hawk–Dove Game to encompass the multiplayer version considered in this paper. By producing neutrality and equilibrium conditions, we show that hawks generally do worse in our models due to the multiplayer nature of the interactions.

Game theory elucidates how competitive dynamics mediate animal social networks

BackgroundWhile most game theoretical models assume that individuals randomly interact with all other group members, strong evidence indicates that individuals tend to preferentially interact with some of them. The position of an individual in a network affects, among other factors related to survival, its predation risk and competitive success. Here I then modified the Hawk-Dove game to explore the effect of social network structure on competitive strategy of individuals that differ in their fighting ability and may adjust their use of the Hawk, Dove and Assessor tactics to maximize their foraging success when they meet opponents they are connected with.ResultsFrom randomly generated networks, I demonstrate that phenotypic assortment by fighting ability reduces individuals’ aggressiveness and, as such, favours cooperative interactions. Furthermore, the success of individuals with the weakest fighting ability is usually highest within networks where they most frequently meet opponents with the same fighting ability as their own, suggesting they might benefit from breaking connections with strong contestants. This might be the case when strong contestants systematically rely on the aggressive Hawk tactic or the risk of being predated is low and independent of the number of neighbours. Thus, I extended the model and built a dynamic model to allow individuals not only to adjust their behaviour to local conditions but also to modify the structure of the social network. The number of connections and degree of phenotypic assortment are then affected by ecological factors (e.g. resources value and predation risk), but above all by whether individuals can reliably assess the competitive ability of their opponents and adjust their behaviour accordingly.ConclusionsThese findings provide strong evidence that behaviour can play a key role in shaping network structure and highlight the importance of considering the coevolution of network and behaviour to apprehend its consequences on population dynamics.

The evolutionary consequences of learning under competition.

Learning is a taxonomically widespread process by which animals change their behavioural responses to stimuli as a result of experience. In this way, it plays a crucial role in the development of individual behaviour and underpins substantial phenotypic variation within populations. Nevertheless, the impact of learning in social contexts on evolutionary change is not well understood. Here, we develop game theoretical models of competition for resources in small groups (e.g. producer-scrounger and hawk-dove games) in which actions are controlled by reinforcement learning and show that biases in the subjective valuation of different actions readily evolve. Moreover, in many cases, the convergence stable levels of bias exist at fitness minima and therefore lead to disruptive selection on learning rules and, potentially, to the evolution of genetic polymorphisms. Thus, we show how reinforcement learning in social contexts can be a driver of evolutionary diversification. In addition, we consider the evolution of ability in our games, showing that learning can also drive disruptive selection on the ability to perform a task.

Social antagonism, identity-driven beliefs, and loss avoidance: Evidence from Guinea

We use a lab-in-the-field experiment to study identity preferences, other-regarding beliefs, and conflict behavior among the Fulani and Malinke in Guinea, Sub-Saharan Africa. In a hawk-dove game, we explore the existence of out-group hostility and ingroup cooperation compared to the baseline where pairs are uninformed of each other's region of origin. We observe that ethnic identity, especially among the Malinke, encourages loss aversion in situations where negative earnings are possible. Identitydriven beliefs, i.e. expectations of others, lead to either reciprocity among homogeneous pairs or materialism in diverse pairs. Using complementary survey data, we also find that high out-group trust and less linguistic diversity are correlated with conflict avoidance.

Interaction intensity in strategic fitness: A quantifying yardstick of selection optimization for evolutionary game

The notion of the fitness of a strategy has been assimilated as the reproductive success in the evolutionary game. Initially, this fitness was tied to the game’s pay-off and the strategy’s relative frequency. However, density dependence becomes exigent in order to make ecologically reliable fitness. However, the contributions of each different type of interaction to the species’s overall growth process were surprisingly under-explored. This oversight has occasionally led to either more or less prediction of strategy selection compared to the actual possibility. Moreover, density regulation of the population has always been analysed in a general way compared to strategy selection. In this context, our study introduces the concept of mean relative death payoff, which helps in assessing interaction intensity coefficients and integrates them into strategic fitness. Based on this fitness function, we develop the frequency-density replicator dynamics, which eventually provides distinguishing criteria for directional and balancing selection. Our optimized, evolutionarily stable strategy emerges as a superior alternative to the conventional trade-off between selection forces and ecological processes. More significantly, mean relative death pay-off has both conditional and quantitative roles in getting a stable population size. As a case study, we have extensively analysed the evolution of aggression using the Hawk-Dove game. We have shown that pure Dove selection is always beneficial for species growth rather than pure Hawk selection, and the condition of selection is dependent on external mortality pressure. However, the condition of coexistence is independent of external mortality pressure, representing a strong evolutionary selection that optimizes population density governed by interaction intensity.

Evolutionarily stable payoff matrix in hawk–dove games

BackgroundClassical matrix game models aim to find the endpoint of behavioural evolution for a set of fixed possible interaction outcomes. Here, we introduce an evolutionary model in which not only the players’ strategies but also the payoff matrix evolves according to natural selection.ResultsWe start out from the hawk–dove matrix game and, in a way that is consistent with the monomorphic model setup of Maynard Smith and Price, introduce an evolving phenotypic trait that quantifies fighting ability and determines the probability of winning and the cost of losing escalated hawk–hawk fights. We define evolutionarily stable phenotypes as consisting of an evolutionarily stable strategy and an evolutionarily stable trait, which in turn describes a corresponding evolutionarily stable payoff matrix.ConclusionsWe find that the maximal possible cost of escalating fights remains constant during evolution assuming a separation in the time scales of fast behavioural and slow trait selection, despite the fact that the final evolutionarily stable phenotype maximizes the payoff of hawk–hawk fights. Our results mirror the dual nature of Darwinian evolution whereby the criteria of evolutionary success, as well as the successful phenotypes themselves, are a product of natural selection.

Stable Mixing in Hawk–Dove Games under Best Experienced Payoff Dynamics

Stable Mixing in Hawk–Dove Games under Best Experienced Payoff Dynamics

The Rise of Conformism in the Hawk-dove Game

The Rise of Conformism in the Hawk-dove Game

Equilibrium Selection in Hawk–Dove Games

We apply three equilibrium selection techniques to study which equilibrium is selected in a hawk–dove game with a multiplicity of equilibria. By using a uniform-price auction as an illustrative example, we find that when the demand in the auction is low or intermediate, the tracing procedure method of Harsanyi and Selten (1988) and the quantal response method of McKelvey and Palfrey (1998) select the same equilibrium. When the demand is high, the tracing procedure method does not select any equilibrium, but the quantal response method still selects the same equilibrium as when the demand is low or intermediate. The robustness to strategic uncertainty method of Andersson, Argenton and Weibull (2014) selects two of the multiple equilibria irrespective of the demand size. We also analyze the impact of an increase in the minimum bid allowed by the auctioneer in the equilibrium selection.

Early Evolution in Cancer: A Mathematical Support for Pathological and Genomic Evidence in Clear Cell Renal Cell Carcinoma.

Clear cell renal cell carcinoma (CCRCC) is an aggressive form of cancer and a paradigmatic example of intratumor heterogeneity (ITH). The hawk-dove game is a mathematical tool designed to analyze competition in biological systems. Using this game, the study reported here analyzes the early phase of CCRCC development, comparing clonal fitness in homogeneous (linear evolutionary) and highly heterogeneous (branching evolutionary) models. Fitness in the analysis is a measure of tumor aggressiveness. The results show that the fittest clone in a heterogeneous environment is fitter than the clone in a homogeneous context in the early phases of tumor evolution. Early and late periods of tumor evolution in CCRCC are also compared. The study shows the convergence of mathematical, histological, and genomics studies with respect to clonal aggressiveness in different periods of the natural history of CCRCC. Such convergence highlights the importance of multidisciplinary approaches for obtaining a better understanding of the intricacies of cancer.

Game-theoretical description of the go-or-grow dichotomy in tumor development for various settings and parameter constellations

A medically important feature of several types of tumors is their ability to “decide” between staying at a primary site in the body or leaving it and forming metastases. The present theoretical study aims to provide a better understanding of the ultimate reasons for this so-called “go-or-grow” dichotomy. To that end, we use game theory, which has proven to be useful in analyzing the competition between tumors and healthy tissues or among different tumor cells. We begin by determining the game types in the Basanta–Hatzikirou–Deutsch model, depending on the parameter values. Thereafter, we suggest and analyze five modified variants of the model. For example, in the basic model, the deadlock game, Prisoner’s Dilemma, and hawk-dove game can occur. The modified versions lead to several additional game types, such as battle of the sexes, route-choice, and stag-hunt games. For some game types, all cells are predicted to stay on their original site (“grow phenotype”), while for other types, only a certain fraction stay and the other cells migrate away (“go phenotype”). If the nutrient supply at a distant site is high, all the cells are predicted to go. We discuss our predictions in terms of the pros and cons of caloric restriction and limitations of the supply of vitamins or methionine. Our results may help devise treatments to prevent metastasis.

Effects of Heterogeneity on Cancer: A Game Theory Perspective

In this study, we explore interactions between cancer cells by using the hawk–dove game. We analyze the heterogeneity of tumors by considering games with populations composed of 2 or 3 types of cell. We determine what strategies are evolutionarily stable in the 2-type and 3-type population games and what the corresponding expected payoffs are. Our results show that the payoff of the best-off cell in the 2-type population game is higher than that of the best-off cell in the 3-type population game. When these mathematical findings are transferred to the field of oncology they suggest that a tumor with low intratumor heterogeneity pursues a more aggressive course than one with high intratumor heterogeneity. Some histological and genomic data on clear cell renal cell carcinomas is consistent with these results. We underline the importance of identifying intratumor heterogeneity in routine practice and suggest that therapeutic strategies that preserve heterogeneity may be promising as they may slow down cancer growth.

Beyond sanctions and anti-sanctions: examining the impact on sustainable competition and China’s responses

Abstract Unilateral economic sanctions are increasingly utilized as a tool for strategic competition among states. The lack of stringent regulations in international law has encouraged states to counter such sanctions by enacting domestic legislatures such as blocking and anti-sanction laws. The complex network of sanctions, blocking statutes, and anti-sanctions has rendered cross-border trade and investment activities more challenging. Sustainable development has a competitive dimension, which requires states and entities to be commercially competitive and to pursue sustainable development goals. Unfortunately, the abuse of sanctions and anti-sanctions, as prognosticated by the Hawk-Dove game theory, has promoted lawfare instead of healthy competition among states. Research has shown that the abuse of these sanctions and anti-sanctions has worsened competitive patterns among nations, leading to a decrease in their resilience ability and severely damaging sustainable development goals. In recent years, China has faced increased pressure from economic sanctions due to trade frictions with other regions, particularly the United States. This paper aims to examine China’s approach in responding to unilateral economic sanctions, supplemented by an analysis of China’s recently enacted anti-sanction and blocking laws. This paper will also further the understanding of how states should respond to and apply unilateral economic sanctions through international law based on China’s experience.

Evolutionary game model of migraine based on the human brain hypersensitivity.

Based on all studies published up to 2020, the prevalence of migraine worldwide is approximately 14%, although it varies regionally. Despite being one of the most disabling diseases, migraine still exists through natural selection and is prevalent today. This raises the question of what evolutionary advantages have led to the survival of migraine. The ultimate answer to this question should be found in evolution; however, there is no clear explanation yet. Notably, all the genes that cause migraine make the sensory organs and cortex of the migraine sufferer hypersensitive. In a state of hypersensitivity, the brain could recognize external threats easily. Game theory is a useful tool for explaining evolution in terms of genes. Just as the Hawk-Dove game, which has two strategies (aggressive and passive) and four fitness values, an evolutionary game between a migraineur and a non-migraineur, which shows two phenotypes (more sensitive and less sensitive) and four fitness values, can be played if a migraineur quickly recognizes a predator and informs a non-migraineur of its appearance and the non-migraineur later helps the migraineur escape from danger. This study aimed to explore the evolutionary mechanics of migraine that can be modeled. Furthermore, it tried to define why the human brain's hypersensitivity is a prerequisite for developing this evolutionary game model.

Half a century of evolutionary games: a synthesis of theory, application and future directions.

Half a century of evolutionary games: a synthesis of theory, application and future directions.

Heuristics Facilitates the Evolution of Transitive Inference and Social Hierarchy in a Large Group

Transitive inference (TI) refers to social cognition that facilitates the discernment of unknown relationships between individuals using known relationships. It is extensively reported that TI evolves in animals living in a large group because TI could assess relative rank without deducing all dyadic relationships, which averts costly fights. The relationships in a large group become so complex that social cognition may not be developed adequately to handle such complexity. If members apply TI to all possible members in the group, TI requires extremely highly developed cognitive abilities especially in a large group. Instead of developing cognitive abilities significantly, animals may apply simplified TI we call reference TI in this study as heuristic approaches. The reference TI allows members to recognize and remember social interactions only among a set of reference members rather than all potential members. Our study assumes that information processes in the reference TI comprises (1) the number of reference members based on which individuals infer transitively, (2) the number of reference members shared by the same strategists, and (3) memory capacity. We examined how information processes evolve in a large group using evolutionary simulations in the hawk–dove game. Information processes with almost any numbers of reference members could evolve in a large group as long as the numbers of shared reference member are high because information from the others’ experiences is shared. TI dominates immediate inference, which assesses relative rank on direct interactions, because TI could establish social hierarchy more rapidly applying information from others’ experiences.

Prediction of groundwater pollution diffusion path based on multi-source data fusion

In order to improve the prediction accuracy of groundwater pollution diffusion path, this paper combines multivariate data fusion technology to predict and analyze the groundwater pollution diffusion path. Under the special two-strategy swarm game model of water pollution particle swarm, this paper introduces replication dynamics with bounded continuous time-delay. Moreover, considering the dynamic behavior in both cases of constant kernel function and exponential kernel function, the hawk-dove game model is a special case of the model we are discussing. In addition, this paper proposes a method combining leaching surface and flux concentration, and applies numerical simulation method to simulate and analyze transient leakage monitoring of similar point and line source pollution in planar two-dimensional heterogeneous aquifers. The experimental study verifies that the multivariate data fusion proposed in this paper can play an important role in the prediction of groundwater pollution diffusion path.

A Contractarian View on Homann’s Ethical Approach

Homann’s method is a sophisticated theoretical model. As a result, it contains a normative foundation upon which Homann bases his endeavor, as well as numerous conclusions following his positive analysis. We propose extensions to both the normative and positive aspects of Homann’s theory in this article. On a normative basis, we recommend taking into account our approach to New Ordoliberalism. In addition to the prisoner’s dilemma, we consider the moral dilemma of the hawk-dove game on a positive footing. Additionally, we also present an experimental design.