Coveting thy neighbors fitness as a means to resolve social dilemmas

In spatial evolutionary games the fitness of each individual is traditionally determined by the payoffs it obtains upon playing the game with its neighbors. Since defection yields the highest individual benefits, the outlook for cooperators is gloomy. While network reciprocity promotes collaborative efforts, chances of averting the impending social decline are slim if the temptation to defect is strong. It is therefore of interest to identify viable mechanisms that provide additional support for the evolution of cooperation. Inspired by the fact that the environment may be just as important as inheritance for individual development, we introduce a simple switch that allows a player to either keep its original payoff or use the average payoff of all its neighbors. Depending on which payoff is higher, the influence of either option can be tuned by means of a single parameter. We show that, in general, taking into account the environment promotes cooperation. Yet coveting the fitness of one's neighbors too strongly is not optimal. In fact, cooperation thrives best only if the influence of payoffs obtained in the traditional way is equal to that of the average payoff of the neighborhood. We present results for the prisoner's dilemma and the snowdrift game, for different levels of uncertainty governing the strategy adoption process, and for different neighborhood sizes. Our approach outlines a viable route to increased levels of cooperative behavior in structured populations, but one that requires a thoughtful implementation.Comment: 10 two-column pages, 5 figures; accepted for publication in Journal of Theoretical Biolog

The “self-bad, partner-worse” strategy inhibits cooperation in networked populations

The emergence and maintenance of cooperation is a popular topic in studies of information sciences and evolutionary game theory. In two-player iterated games, memory in terms of the outcome of previous interactions and the strategy choices of co-players are of great referential significance for subsequent strategy actions. It is generally recognized that there is no single simple and overarching strategy whereby one player X can unilaterally achieve a higher payoff than his opponent Y, irrespective of Y's strategy and response. In this paper, we demonstrate that such strategies do exist in diverse networked populations. More precisely, (i) such strategies can obtain a low payoff for the focal player, however, they also lead to an even lower payoff for that player's partner, in turn lowering benefits of the overall populations; (ii) they are capable of winning with a high probability against opponents with an unknown strategy; and (iii) they have a survival advantage and robust fitness in terms of evolutionary processes. We refer to these as the “self-bad, partner-worse” (SBPW) strategies. Results presented here add to previous studies on strategy evolution in the context of social dilemmas and hint at some insights concerning cooperation promotion mechanisms among networked populations

Prosocial effects of coordination - What, how and why?

A wealth of research in recent decades has investigated the effects of various forms of coordination upon prosocial attitudes and behavior. To structure and constrain this research, we provide a framework within which to distinguish and interrelate different hypotheses about the psychological mechanisms underpinning various prosocial effects of various forms of coordination. To this end, we introduce a set of definitions and distinctions that can be used to tease apart various forms of prosociality and coordination. We then identify a range of psychological mechanisms that may underpin the effects of coordination upon prosociality. We show that different hypotheses about the underlying psychological mechanisms motivate different predictions about the effects of various forms of coordination in different circumstances

Introspection dynamics: a simple model of counterfactual learning in asymmetric games

Social behavior in human and animal populations can be studied as an evolutionary process.Individuals often make decisions between different strategies, and those strategies that yield afitness advantage tend to spread. Traditionally, much work in evolutionary game theory considerssymmetric games: individuals are assumed to have access to the same set of strategies, and theyexperience the same payoff consequences. As a result, they can learn more profitable strategies byimitation. However, interactions are oftentimes asymmetric. In that case, imitation may beinfeasible (because individuals differ in the strategies they are able to use), or it may be undesirable(because individuals differ in their incentives to use a strategy). Here, we consider an alternativelearning process which applies to arbitrary asymmetric games,introspection dynamics. Accordingto this dynamics, individuals regularly compare their present strategy to a randomly chosenalternative strategy. If the alternative strategy yields a payoff advantage, it is more likely adopted. Inthis work, we formalize introspection dynamics for pairwise games. We derive simple and explicitformulas for the abundance of each strategy over time and apply these results to severalwell-known social dilemmas. In particular, for the volunteer’s timing dilemma, we show that theplayer with the lowest cooperation cost learns to cooperate without delay

The psychological foundations of reputation-based cooperation

Humans care about having a positive reputation, which may prompt them to help in scenarios where the return benefits are not obvious. Various game-theoretical models support the hypothesis that concern for reputation may stabilize cooperation beyond kin, pairs or small groups. However, such models are not explicit about the underlying psychological mechanisms that support reputation-based cooperation. These models therefore cannot account for the apparent rarity of reputation-based cooperation in other species. Here, we identify the cognitive mechanisms that may support reputation-based cooperation in the absence of language. We argue that a large working memory enhances the ability to delay gratification, to understand others' mental states (which allows for perspective-taking and attribution of intentions) and to create and follow norms, which are key building blocks for increasingly complex reputation-based cooperation. We review the existing evidence for the appearance of these processes during human ontogeny as well as their presence in non-human apes and other vertebrates. Based on this review, we predict that most non-human species are cognitively constrained to show only simple forms of reputation-based cooperation. This article is part of the theme issue ‘The language of cooperation: reputation and honest signalling’

Aspects of goods market integration: A two-country-two-sector analysis

Economic Integration;Fiscal Policy;Models

Stochastic Evolutionary Dynamics of Trust Games with Asymmetric Parameters

Trusting in others and reciprocating that trust with trustworthy actions are crucial to successful and prosperous societies. The Trust Game has been widely used to quantitatively study trust and trustworthiness, involving a sequential exchange between an investor and a trustee. The deterministic evolutionary game theory predicts no trust and no trustworthiness whereas the behavioural experiments with the one-shot anonymous Trust Game show that people substantially trust and respond trustworthily. To explain these discrepancies, previous works often turn to additional mechanisms, which are borrowed from other games such as Prisoner's Dilemma. Although these mechanisms lead to the evolution of trust and trustworthiness to an extent, the optimal or the most common strategy often involves no trustworthiness. In this paper, we study the impact of asymmetric demographic parameters (e.g. different population sizes) on game dynamics of the Trust Game. We show that, in weak-mutation limit, stochastic evolutionary dynamics with the asymmetric parameters can lead to the evolution of high trust and high trustworthiness without any additional mechanisms in well-mixed finite populations. Even full trust and near full trustworthiness can be the most common strategy. These results are qualitatively different from those of the previous works. Our results thereby demonstrate rich evolutionary dynamics of the asymmetric Trust Game.Comment: 17 pages, 15 figure

Social Dynamics Modeling of Chrono-nutrition

Gut microbiota and human relationships are strictly connected to each other. What we eat reflects our body-mind connection and synchronizes with people around us. However, how this impacts on gut microbiota and, conversely, how gut bacteria influence our dietary behaviors has not been explored yet. To quantify the complex dynamics of this interplay between gut and human behaviors we explore the ``gut-human behavior axis'' and its evolutionary dynamics in a real-world scenario represented by the social multiplex network. We consider a dual type of similarity, homophily and gut similarity, other than psychological and unconscious biases. We analyze the dynamics of social and gut microbial communities, quantifying the impact of human behaviors on diets and gut microbial composition and, backwards, through a control mechanism. Meal timing mechanisms and ``chrono-nutrition'' play a crucial role in feeding behaviors, along with the quality and quantity of food intake. Considering a population of shift workers, we explore the dynamic interplay between their eating behaviors and gut microbiota, modeling the social dynamics of chrono-nutrition in a multiplex network. Our findings allow us to quantify the relation between human behaviors and gut microbiota through the methodological introduction of gut metabolic modeling and statistical estimators, able to capture their dynamic interplay. Moreover, we find that the timing of gut microbial communities is slower than social interactions and shift-working, and the impact of shift-working on the dynamics of chrono-nutrition is a fluctuation of strategies with a major propensity for defection (e.g. high-fat meals). A deeper understanding of the relation between gut microbiota and the dietary behavioral patterns, by embedding also the related social aspects, allows improving the overall knowledge about metabolic models and their implications for human health, opening the possibility to design promising social therapeutic dietary interventions

From Digital Twins to Digital Selves and Beyond

This open access book aims at deepening the understanding of the relation between cyber-physical systems (CPSs) as socio-technical systems and their digital representations with intertwined artificial intelligence (AI). The authors describe why it is crucial for digital selves to be able to develop emotional behavior and why a humanity-inspired AI is necessary so that humans and humanoids can coexist. The introductory chapter describes major milestones in computer science which form the basis for the implementation of digital twins and digital selves. The subsequent Part I then lays the foundation to develop a socio-technical understanding of the nature of digital twins as representations and trans-human development objects. Following the conceptual understanding of digital twins and how they could be engineered according to cognitive and organizational structures, Part II forms the groundwork for understanding social behavior and its modeling. It discusses various perception-based socio-emotional approaches before sketching behavior-relevant models and their simulation capabilities. In particular, it is shown how emotions can substantially influence the collective behavior of artificial actors. Part III eventually presents a symbiosis showing under which preconditions digital selves might construct and produce digital twins as integrated design elements in trans-human ecosystems. The chapters in this part are dedicated to opportunities and modes of co-creating reflective socio-trans-human systems based on digital twin models, exploring mutual control and continuous development. The final epilog is congenitally speculative in its nature by presenting thoughts on future developments of artificial life in computational substrates. The book is written for researchers and professionals in areas like cyber-physical systems, robotics, social simulation or systems engineering, interested to take a speculative look into the future of digital twins and autonomous agents. It also touches upon philosophical aspects of digital twins, digital selves and humanoids