Evolutionary Game Theory

Morality is serious yet it needs to be reconciled with the free play of alternatives that characterizes rational and ethical agency. Beginning with a sketch of the seriousness of morality modeled as a constraint, this paper introduces a technical conception of play as degrees of freedom. We consider two ways to apply game theory to ethics, rationalist and evolutionary game theory, contrasting the way they model moral constraint. Freedom in the rationalist account is problematic, subverting willful commitment. In the evolutionary account, freedom is also problematic, leading to an infinity of possible social norms with dubious normative force. While these two approaches complement each other, we argue that the evolutionary approach is superior on both theoretical and practical grounds.

One can restructure institutions, but if individual-level motivations for corrupt behavior are not understood, these restructuring may not be effective. We introduce an evolutionary-game modeling to deal with the problem of corruption driven by imitative behavior.

Abstract Next-generation wireless networks will integrate multiple wireless access technologies to provide seamless mobility to mobile users with high-speed wireless connectivity. This will give rise to a heterogeneous wireless access environment where ...

The broader adoption of the EPR in healthcare settings has brought with it much greater attention to the significant issues regarding security, confidentiality and privacy of healthcare information. The economic, social and political impact of these issues is also of major concern. In this paper, it is suggested that the application of contemporary evolutionary game theory has high utility for understanding the actual behaviour of stakeholders in such settings. Contemporary evolutionary game theory can explain the effects of cultural norms, institutional policies and economics on behavior. I also suggest that contemporary evolutionary game theory is sufficiently robust as to be useful in the rational design of a policy to encourage certain socially desired behaviour in this area.

The analysis of equilibrium points in biological dynamical systems has been of great interest in a variety of mathematical approaches to biology, such as population genetics, theoretical ecology or evolutionary game theory. The maximal number of equilibria and their classification based on stability have been the primary subjects of these studies, for example in the context of two-player games with multiple strategies. Herein, we address a different question using evolutionary game theory as a tool. If the payoff matrices are drawn randomly from an arbitrary distribution, what are the probabilities of observing a certain number of (stable) equilibria? We extend the domain of previous results for the two-player framework, which corresponds to a single diploid locus in population genetics, by addressing the full complexity of multi-player games with multiple strategies. In closing, we discuss an application and illustrate how previous results on the number of equilibria, such as the famous Feldman–Karlin conjecture on the maximal number of isolated fixed points in a viability selection model, can be obtained as special cases of our results based on multi-player evolutionary games. We also show how the probability of realizing a certain number of equilibria changes as we increase the number of players and number of strategies.

Both conventional wisdom and empirical evidence suggest that arranging a prior commitment or agreement before an interaction takes place enhances the chance of reaching mutual cooperation. Yet it is not clear what mechanisms might underlie the participation in and compliance with such a commitment, especially when participation is costly and non-compliance can be profitable. Here, we develop a theory of participation and compliance with respect to an explicit commitment formation process and to institutional incentives where individuals, at first, decide whether or not to join a cooperative agreement to play a one-shot social dilemma game. Using a mathematical model, we determine whether and when participating in a costly commitment, and complying with it, is an evolutionary stable strategy, resulting in high levels of cooperation. We show that, given a sufficient budget for providing incentives, rewarding of commitment compliant behaviours better promotes cooperation than punishment of non-compliant ones. Moreover, by sparing part of this budget for rewarding those willing to participate in a commitment, the overall level of cooperation can be significantly enhanced for both reward and punishment. Finally, the presence of mistakes in deciding to participate favours evolutionary stability of commitment compliance and cooperation.

Indirect reciprocity is an important mechanism for promoting cooperation among self-interested agents. Simplified, it means you help me, therefore somebody else will help you (in contrast to direct reciprocity: you help me, therefore I will help you). Indirect reciprocity can be achieved via reputation and norms. Strategies, such as the so-called leading eight, relying on these principles can maintain high levels of cooperation and remain stable against invasion, even in the presence of errors. However, this is only the case if the reputation of an agent is modeled as a shared public opinion. If agents have private opinions and hence can disagree if somebody is good or bad, even rare errors can cause cooperation to break apart. We show that most strategies can overcome the private assessment problem by applying pleasing. A pleasing agent acts in accordance with others' expectations of their behavior (i.e. pleasing them) instead of being guided by their own, private assessment. As such, a pleasing agent can achieve better reputations than previously considered strategies when there is disagreement in the population. Pleasing is effective even if only the opinions of few other individuals are considered and when it bears additional costs. Finally, through a more exhaustive analysis of the parameters' space than previous studies, we show that some of the leading eight still function under private assessment, i.e. that cooperation rates are well above an objective baseline. Yet, pleasing strategies supersede formerly described ones and enhance cooperation.

Evolutionary game models normally have a finite set of strategies. Recently, evo- lutionary games with continuous spaces of strategies have been introduced by Dan Friedman and Joel Yellin, under the name landscape dynamics. In one example extensively studied by them, conspicuous consumption, a simple (gradient) dynamical system is introduced on the strategy space. In this article, we translate a landscape dynamic system into a complex dy- namical system, and then into an agent based model. The conspicuous consumption model of Friedman and Yellin is realized as an agent based model in NetLogo to illustrate the concepts of this new modeling strategy.

In this paper we present the design and implementation of a small-scale marine sensor network. The network monitors the temperature in the Baltic Sea on different heights from the water surface down to the bottom. Unlike many other wireless sensor networks, this network contains both a wired and a wireless part. One of the major challenges is that the network is hard to access after its deployment and hence both hard-and software must be robust and reliable. We also present the design of an advanced buoy system featuring a diving unit that achieves a better vertical resolution and discuss remaining challenges of sensor networking in aquatic environments.

This paper examines the role of pro-social behavior as a mechanism for the establishment and maintenance of cooperation in resource use under variable social and environmental conditions. By coupling resource stock dynamics with social dynamics concerning compliance to a social norm prescribing non-excessive resource extraction in a common pool resource (CPR), we show that when reputational considerations matter and a sufficient level of social stigma affects the violators of a norm, sustainable outcomes are achieved. We find large parameter regions where norm-observing and norm-violating types coexist, and analyze to what extent such coexistence depends on the environment.

In this paper we will solve some linear programming problems by solving systems of differential equations using game theory. The linear programming problem must be a classical constraints problem or a classical menu problem, i.e. a maximization/minimization problem in the canonical form with all the coefficients (from objective function, constraints matrix and right sides) positive. Firstly we will transform the linear programming problem such that the new problem and its dual have to be solved in order to find the Nash equilibrium of a matriceal game. Next we find the Nash equilibrium by solving a system of differential equations as we know from evolutionary game theory, and we express the solution of the obtained linear programming problem (by the above transformation of the initial problem) using the Nash equilibrium and the corresponding mixed optimal strategies. Finally, we transform the solution of the obtained problem to obtain the solution of the initial problem. We make als...

The handicap principle is one of the most influential ideas in evolutionary biology. It asserts that when there is conflict of interest in a signaling interaction signals must be costly in order to be reliable. We show how the handicap principle is a limiting case of honest signaling, which can also be sustained by other mechanisms. This fact has gone unnoticed because in evolutionary biology it is a common practice to distinguish between cues, indexes and fakable signals, where cues provide information but are not signals and indexes are signals that cannot be faked. We find that the dichotomy between indexes and fakable signals is an artifact of the existing signaling models. Our results suggest that one cannot adequately understand signaling behavior by focusing solely on cost. Under our reframing, cost becomes one-and probably not the most important-of a collection of factors preventing deception.

ABSTRACT. This paper critically reviews Ken Binmore's non-utilitarian and game theoretic solution to the Arrow problem. Binmore's solution belongs to the same family as Rawls' maximin criterion and requires the use of Nash bargaining theory, empathetic preferences, and results in ...

This book is about the three identities of the videogame, the gamer, and Game Studies. I write that there are no definitive truths but rather discourses and constructions; ideas, actions, beliefs, and practices related to videogames are discourses that merge and shape our perception of videogames as an area of study of its own right. These discursive responses meet and clash creating what we call truths, which are temporary and negotiable.

This perspective is inspired by Foucauldian ideas and present few questions about videogame-related identities in and outside of academe. Does Game Studies have a conceptual core? What makes game studies difficult to be disciplined in academe? What do we learn from the scholarly and popular discourses on videogames that would help understand the identity questions related to games?

I go on to describe what makes the videogame identity according to game studies: aesthetics, fictions, meaning-making, performance, transformation, etc. and what makes it difficult for game studies being an open market of ideas and an academic "un-discipline". This leads me to the gamer's identity: an aficionado first, and a connoisseur of fictional worlds.

A substantial effort has been devoted to various adaptive techniques of systems. Most of these concepts work in the control domain, where every system only has one controller. Yet, for the multi-controller counterpart -dynamic games, adaptations are usually considered from a perspective of systems, for an example, evolutionary games. In this paper, we propose a new adaptive approach for linear quadratic discrete-time games with scalar inputs and state feedback Nash strategies. We consider the effort of adaptation under a Fictitious Play (FP) framework with learning algorithms derived from conventional adaptive control methods. Convergence to Nash strategies is proved with the condition that there exists a unique state feedback strategy, which implies that the associated coupled discrete-time algebraic Riccati equations (DAREs) have a unique positive semi-definite solution. The requirement of Persistency of Excitation (PE) is satisfied by proper reference signals to be tracked.

Colman, AM, & Wilson, JC (1997). Antisocial personality disorder: An evolutionary game theory analysis. Legal and Criminological Psychology, 2, 23-34. [Discussed in R. Matthews, “Game Theory Backs Crackdown on Petty Crime”, New Scientist, 1997, 154(2078), 18; “La ...

I use sim-max games to investigate the conditions under which real world properties will be categorized together perceptually.  I argue that given this work we should neither expect perceptual categories to be perfect dependable, or entirely unknowable.

The goal of this thesis is twofold. First, intention recognition is studied from an Artificial Intelligence (AI) modeling perspective. We present a novel and efficient intention recognition method that possesses several important features: (i) The method is context-dependent and incremental, enabled by incrementally construct- ing a three-layer Bayesian Network model as more actions are observed, and in a context-dependent manner, relying on a logic programming knowledge base concern- ing the context; (ii) The Bayesian Network is composed from a knowledge base of readily specified and readily maintained Bayesian Network fragments with simple structures, enabling an efficient acquisition of the corresponding knowledge base (ei- ther from domain experts or else automatically from a plan corpus); and, (iii) The method addresses the issue of intention change and abandonment, and can appro- priately resolve the issue of multiple intentions recognition. Several aspects of the method are evaluated experimentally, achieving some definite success. Furthermore, on top of the intention recognition method, a novel framework for intention-based decision making is provided, illustrating several ways in which an ability to recognize intentions of others can enhance a decision making process.
A second subgoal of the thesis concerns that, whereas intention recognition has been extensively studied in small scale interactive settings, there is a major shortage of modeling research with respect to large scale social contexts, namely evolution- ary roles and aspects of intention recognition. Employing our intention recognition method and the tools of evolutionary game theory, this thesis explicitly addresses the roles played by intention recognition in the final outcome of cooperation in large populations of self-regarding individuals. By equipping individuals with the capacity for assessing intentions of others in the course of social dilemmas, we show how in- tention recognition is selected by natural selection, opening a window of opportunity for cooperation to thrive, even in hard cooperation prone games like the Prisoner’s Dilemma.
In addition, there are cases where it is difficult, if not impossible, to recognize the intentions of another agent. In such cases, the strategy of proposing commitment, or of intention manifestation, can help to impose or clarify the intentions of others. Again using the tools of evolutionary game theory, we show that a simple form of commitment can lead to the emergence of cooperation; furthermore, the combination of commitment with intention recognition leads to a strategy better than either one by itself.

Social scientists and folk views have long had it that there is an association between religiosity and prosocial behaviour, but hard evidence for such a relationship is limited. Studies show that religiosity is correlated with self-reported prosociality, however this relationship is not very clear when it comes to observed prosocial behaviours. Experimental studies reveal a link between religious priming and prosocial behaviours, and remarkably such effects hold irrespectively of degrees of religiosity. Building on and combining the strengths of previous field designs, I report here the results of a field experiment in Mauritius examining the effects of religious environments on cooperation in a naturalistic setting. These results were consistent with previous findings that religious cues may increase cooperation. Importantly, this effect was not dependent on degrees of prior religiosity. Plausible interpretations of such effects are discussed.

Game theory is one of the key paradigms behind many scientific disciplines from biology to behavioral sciences to economics. In its evolutionary form and especially when the interacting agents are linked in a specific social network the underlying solution concepts and methods are very similar to those applied in non-equilibrium statistical physics. This review gives a tutorial-type overview of the field for physicists. The first four sections introduce the necessary background in classical and evolutionary game theory from the basic definitions to the most important results. The fifth section surveys the topological complications implied by non-mean-field-type social network structures in general. The next three sections discuss in detail the dynamic behavior of three prominent classes of models: the Prisoner's Dilemma, the Rock-Scissors-Paper game, and Competing Associations. The major theme of the review is in what sense and how the graph structure of interactions can modify and enrich the picture of long term behavioral patterns emerging in evolutionary games.

Game theory is the mathematical study of strategy and conflict. It has wide applications in economics, political science, sociology, and, to some extent, in philosophy. Where rational choice theory or decision theory is concerned with individual agents facing games against nature, game theory deals with games in which all players have preference orderings over the possible outcomes of the game. This paper gives an informal introduction to the theory and a survey of applications in diverse branches of philosophy. No criticism is reviewed. Game theory is shown at work in discussions about epistemological dependence (prisoner's dilemma), liberalism and efficiency (Nash equilibrium), Hume's concept of convention (correlated equilibrium), morality and rationality (bargaining games), and distributive justice and egalitarianism (evolutionary game theory). A guide to the literature provides hints at applications in collective intentionality, epistemology, ethics, history of philosophy, logic, philosophy of language, and political philosophy.

Why are we good? Why are we bad? Questions regarding the evolution of morality have spurred an astoundingly large interdisciplinary literature. Some significant subset of this body of work addresses questions regarding our moral psychology: how did humans evolve the psychological properties which underpin our systems of ethics and morality? Here I do three things. First, I discuss some methodological issues, and defend particularly effective methods for addressing many research questions in this area. Second, I give an in-depth example, describing how an explanation can be given for the evolution of guilt—one of the core moral emotions—using the methods advocated here. Last, I lay out which sorts of strategic scenarios generally are the ones that our moral psychology evolved to 'solve', and thus which models are the most useful in further exploring this evolution.

Coevolution in economic systems plays a key role in the
dynamics of contemporary societies. Coevolution operates when,
considering several evolving realms within a socioeconomic system,
these realms mutually shape their respective innovation, replication
and/or selection processes. The processes that emerge from
coevolution should be analyzed as being globally codetermined in
dynamic terms. The notion of coevolution appears in the literature on
modern innovation economics since the neo-Schumpeterian inception
four decades ago. In this Element, these antecedents are drawn on to
formally clarify and develop how the coevolution notion can expand
the analytical and methodological scope of evolutionary economics,
allowing for further unification and advance of evolutionary subfields.

Reservoir systems with multiple operators can benefit from coordination of operation policies. To maximize the total benefit of these systems the literature has normally used the social planner’s approach. Based on this approach operation decisions are optimized using a multi-objective optimization model with a compound system’s objective. While the utility of the system can be increased this way, fair allocation of benefits among the operators remains challenging for the social planner who has to assign controversial weights to the system’s beneficiaries and their objectives. Cooperative game theory provides an alternative framework for fair and efficient allocation of the incremental benefits of cooperation. To determine the fair and efficient utility shares of the beneficiaries, cooperative game theory solution methods consider the gains of each party in the status quo (non-cooperation) as well as what can be gained through the grand coalition (social planner’s solution or full cooperation) and partial coalitions. Nevertheless, estimation of the benefits of different coalitions can be challenging in complex multi-beneficiary systems. Reinforcement learning can be used to address this challenge and determine the gains of the beneficiaries for different levels of cooperation, i.e., non-cooperation, partial cooperation, and full cooperation, providing the essential input for allocation based on cooperative game theory. This paper develops a game theory–reinforcement learning (GT–RL) method for determining the optimal operation policies in multi-operator multi-reservoir systems with respect to fairness and efficiency criteria. As the first step to underline the utility of the GT–RL method in solving complex multi-agent multi-reservoir problems without a need for developing compound objectives and weight assignment, the proposed method is applied to a hypothetical three-agent three-reservoir system.

In this paper we survey the basics of Reinforcement Learning and (Evolutionary) Game Theory, applied to the field of Multi-Agent Systems. This paper contains three parts. We start with an overview on the fundamentals of Reinforcement Learning. Next we summarize the most important aspects of Evolutionary Game Theory. Finally, we discuss the state-of-the-art of Multi-Agent Reinforcement Learning and the mathematical connection with Evolutionary Game Theory.

The evolution in animals of a first possession convention, in which individuals retain what they are the first to acquire, has often been taken as a foundation for the evolution of human ownership institutions. However, among humans, individuals actually only seldom retain an item they have acquired from the environment, instead typically transferring what they possess to other members of the community, to those in command, or to those who hold a contractual title. This paper presents a novel game-theoretic model of the evolution of ownership institutions as rules governing resource transfers. Integrating existing findings, the model contributes a new perspective on the emergence of communal transfers among hominin large game hunters around 200,000 years ago, of command ownership among sedentary humans in the millennia prior to the transition to agriculture, and of titled property ownership around 5,500 years ago. Since today’s property institutions motivate transfers through the promise of future returns, the analysis presented here suggests that these institutions may be placed under considerable pressure should resources become significantly constrained.

Preface (stream-split proportions and stock-recruitment relation) and economic factors (harvest costs and benefits) incorporate Markovian stochastic elements. The implications of alternative knowledge-structures are explored, through dynamic programming and simulation. Haurie, Moresino and Viguier propose a two-level hierarchical differential game to represent the possible negotiations of GHG emissions quotas between different nations in a post-Kyoto era. The players are countries with growing economies. The quotas are determined non-cooperatively but are globally constrained to satisfy a long term limit on the discounted cumulative emissions. Once the quotas are determined an international emissions trading system permits the country to realize the abatement program at the least global cost. The set of normalized equilibria is proposed as the solution concept that could be used to drive the negotiations in such a context. These equilibrium solutions are characterized.

Psychological game theory encompasses formal theories designed to remedy game-theoretic indeterminacy and to predict strategic interaction more accurately. Its theoretical plurality entails second-order indeterminacy, but this seems unavoidable. Orthodox game theory cannot solve payoff-dominance problems, and remedies based on interval-valued beliefs or payoff transformations are inadequate. Evolutionary game theory applies only to repeated interactions, and behavioral ecology is powerless to explain cooperation between genetically unrelated strangers in isolated interactions. Punishment of defectors elucidates cooperation in social dilemmas but leaves punishing behavior unexplained. Team reasoning solves problems of coordination and cooperation, but aggregation of individual preferences is problematic.

One of the major puzzles in evolutionary theory is how communication and information transfer are possible when the interests of those involved conflict.  Simply put, communication is possible if there are substantial costs associated with sending a signal or, alternatively, if signals themselves are difficult, if not impossible, to fake (such signals are often known as indices).  In this second case, perfect information transfer seems inevitable if there are physical constraints, which limit the signal repertoire of an individual, effectively making bluffing an impossibility.  This, I shall argue, is incorrect.  Indices by no means guarantee information transfer.  I demonstrate the existence of a so-called pooling equilibrium and discuss why the traditional argument for perfect information transfer (Frank's full disclosure principle) does not hold in all cases.  Finally, I attempt to outline under what conditions signaling constraints will evolve.

Social punishment has been suggested as a key approach to ensuring high levels of cooperation and norm compliance in one-shot interactions. However, it has been shown that it only works when punishment is highly cost-efficient. On the other hand, signalling retribution hearkens back to medieval sovereignty, insofar as the very word for gallows in French stems from the Latin word for power and serves as a grim symbol of the ruthlessness of high justice. Here we introduce the mechanism of signalling an act of punishment and a special type of defector emerges, one who can recognise this signal and avoid punishment by way of fear. We perform extensive agent-based simulations so as to confirm and expand our understanding of the external factors that influence the success of social punishment. We show that our suggested mechanism serves as a catalyst for cooperation, even when signalling and punishment are very costly. We observe the preventive nature of advertising retributive acts and w...

We give a mechanism fully implementing envy-free divisions such that: strategy spaces are symmetric, the set of Nash equilibria is a global attractor for the best-reply dynamics. As a byproduct, undesired mixed-strategy equilibria are weeded out by the adjustment process.

Evolutionary games have considerable unrealized potential for modeling substantive economic issues. They promise richer predictions than orthodox game models but often require more extensive speci®cations. This paper exposits the speci®cation of evolutionary game models and classi®es the possible asymptotic behavior for one and two dimensional models.

We explore how evolutionary game dynamics have to be modi"ed to accomodate a mathematical framework for the evolution of language. In particular, we are interested in the evolution of vocabulary, that is associations between signals and objects. We assume that successful communication contributes to biological "tness: individuals who communicate well leave more o!spring. Children inherit from their parents a strategy for language learning (a language acquisition device). We consider three mechanisms whereby language is passed from one generation to the next: (i) parental learning: children learn the language of their parents; (ii) role model learning: children learn the language of individuals with a high payo!; and (iii) random learning: children learn the language of randomly chosen individuals. We show that parental and role model learning outperform random learning. Then we introduce mistakes in language learning and study how this process changes language over time. Mistakes increase the overall e$cacy of parental and role model learning: in a world with errors evolutionary adaptation is more e$cient. Our model also provides a simple explanation why homonomy is common while synonymy is rare. 1999 Academic Press 148 M. A. NOWAK E¹ A¸.

I probe the judgments of the agreeable that we make about food and drink. I first separate different concerns that we might have with food and drink. After that, I address expressive language by first sketching an evolutionary language-game-theoretic approach for referential language. I then try to extend it to expressive language, showing how expressive signaling might be likely to evolve. Given an account of expressive prediction, and its point, I turn to the Frege-Geach problem for the agreeable. I show how a proper understanding of what expression is, in the evolutionary language-game-theoretic framework, allows us to side-step a central aspect the problem.