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Games
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Evolutionary Games and Statistical Physics of Social Networks
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Evolutionary Games and Statistical Physics of Social Networks

A special issue of Games (ISSN 2073-4336).

Deadline for manuscript submissions: closed (30 November 2016) | Viewed by 67937

Special Issue Editor

Prof. Dr. Attila Szolnoki

E-Mail Website
Guest Editor
Institute of Technical Physics and Materials Science, Centre for Energy Research, Hungarian Academy of Sciences, P.O. Box 49, H-1525 Budapest, Hungary
Interests: evolutionary game theory; statistical physics; Monte Carlo simulations; phase transitions; social and economic systems

Special Issue Information

Dear Colleagues,

The scientific approach of evolutionary game theory is proved to be prosperous in a broad variety of fields and systems, ranging from the smallest, such as viruses and bacteria, to the largest ones, which are formed by human societies. Importantly, these seemingly very different areas not only employ the original tools founded by mathematicians, but they also provide stimulating ideas to the main theory. In particular, one of our recent understandings was to realize that solutions in spatially structured populations could be significantly different from those we expect based on our experience with random systems. In other words, emerging patterns provide very specific environment for competing strategies, which could alter the final outcome relevantly. This Special Issue is intended to provide examples when network science and applied mathematics meet the concepts of statistical physics to the benefit of the original theory. Interested authors are invited to participate in this thrilling venture.

Prof. Dr. Attila Szolnoki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Games is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cooperation
  • social dilemmas
  • punishment
  • reward
  • cyclic dominance
  • pattern formation
  • networks

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Published Papers (8 papers)

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Research

3495 KiB  
Article
Topological Aspects of the Multi-Language Phases of the Naming Game on Community-Based Networks
by Filippo Palombi and Simona Toti
Games 2017, 8(1), 12; https://doi.org/10.3390/g8010012 - 9 Feb 2017
Cited by 2 | Viewed by 7657
Abstract
The Naming Game is an agent-based model where individuals communicate to name an initially unnamed object. On a large class of networks continual pairwise interactions lead the system to an ultimate consensus state, in which agents onverge on a globally shared name. Soon [...] Read more.
The Naming Game is an agent-based model where individuals communicate to name an initially unnamed object. On a large class of networks continual pairwise interactions lead the system to an ultimate consensus state, in which agents onverge on a globally shared name. Soon after the introduction of the model, it was observed in literature that on community-based networks the path to consensus passes through metastable multi-language states. Subsequently, it was proposed to use this feature as a mean to discover communities in a given network. In this paper we show that metastable states correspond to genuine multi-language phases, emerging in the thermodynamic limit when the fraction of links connecting communities drops below critical thresholds. In particular, we study the transition to multi-language states in the stochastic block model and on networks with community overlap. We also xamine the scaling of critical thresholds under variations of topological properties of the network, such as the number and relative size of communities and the structure of intra-/inter-community links. Our results provide a theoretical justification for the proposed use of the model as a community-detection algorithm. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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3692 KiB  
Article
Cyclic Competition and Percolation in Grouping Predator-Prey Populations
by Alessandra F. Lütz, Annette Cazaubiel and Jeferson J. Arenzon
Games 2017, 8(1), 10; https://doi.org/10.3390/g8010010 - 2 Feb 2017
Cited by 15 | Viewed by 7356
Abstract
We study, within the framework of game theory, the properties of a spatially distributed population of both predators and preys that may hunt or defend themselves either isolatedly or in group. Specifically, we show that the properties of the spatial Lett-Auger-Gaillard model, when [...] Read more.
We study, within the framework of game theory, the properties of a spatially distributed population of both predators and preys that may hunt or defend themselves either isolatedly or in group. Specifically, we show that the properties of the spatial Lett-Auger-Gaillard model, when different strategies coexist, can be understood through the geometric behavior of clusters involving four effective strategies competing cyclically,without neutral states. Moreover, the existence of strong finite-size effects, a form of the survival of the weakest effect, is related to a percolation crossover. These results may be generic and of relevance to other bimatrix games. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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5732 KiB  
Article
The Evolution of Reputation-Based Cooperation in Regular Networks
by Tatsuya Sasaki, Hitoshi Yamamoto, Isamu Okada and Satoshi Uchida
Games 2017, 8(1), 8; https://doi.org/10.3390/g8010008 - 21 Jan 2017
Cited by 20 | Viewed by 10350
Abstract
Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study [...] Read more.
Despite recent advances in reputation technologies, it is not clear how reputation systems can affect human cooperation in social networks. Although it is known that two of the major mechanisms in the evolution of cooperation are spatial selection and reputation-based reciprocity, theoretical study of the interplay between both mechanisms remains almost uncharted. Here, we present a new individual-based model for the evolution of reciprocal cooperation between reputation and networks. We comparatively analyze four of the leading moral assessment rules—shunning, image scoring, stern judging, and simple standing—and base the model on the giving game in regular networks for Cooperators, Defectors, and Discriminators. Discriminators rely on a proper moral assessment rule. By using individual-based models, we show that the four assessment rules are differently characterized in terms of how cooperation evolves, depending on the benefit-to-cost ratio, the network-node degree, and the observation and error conditions. Our findings show that the most tolerant rule—simple standing—is the most robust among the four assessment rules in promoting cooperation in regular networks. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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615 KiB  
Article
Social Pressure and Environmental Effects on Networks: A Path to Cooperation
by María Pereda and Daniele Vilone
Games 2017, 8(1), 7; https://doi.org/10.3390/g8010007 - 14 Jan 2017
Cited by 1 | Viewed by 7088
Abstract
In this paper, we study how the pro-social impact due to the vigilance by other individuals is conditioned by both environmental and evolutionary effects. To this aim, we consider a known model where agents play a Prisoner’s Dilemma Game (PDG) among themselves and [...] Read more.
In this paper, we study how the pro-social impact due to the vigilance by other individuals is conditioned by both environmental and evolutionary effects. To this aim, we consider a known model where agents play a Prisoner’s Dilemma Game (PDG) among themselves and the pay-off matrix of an individual changes according to the number of neighbors that are “vigilant”, i.e., how many neighbors watch out for her behavior. In particular, the temptation to defect decreases linearly with the number of vigilant neighbors. This model proved to support cooperation in specific conditions, and here we check its robustness with different topologies, microscopical update rules and initial conditions. By means of many numerical simulations and few theoretical considerations, we find in which situations the vigilance by the others is more effective in favoring cooperative behaviors and when its influence is weaker. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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1793 KiB  
Article
Cognitive Hierarchy Theory and Two-Person Games
by Carlos Gracia-Lázaro, Luis Mario Floría and Yamir Moreno
Games 2017, 8(1), 1; https://doi.org/10.3390/g8010001 - 3 Jan 2017
Cited by 4 | Viewed by 9553
Abstract
The outcome of many social and economic interactions, such as stock-market transactions, is strongly determined by the predictions that agents make about the behavior of other individuals. Cognitive hierarchy theory provides a framework to model the consequences of forecasting accuracy that has proven [...] Read more.
The outcome of many social and economic interactions, such as stock-market transactions, is strongly determined by the predictions that agents make about the behavior of other individuals. Cognitive hierarchy theory provides a framework to model the consequences of forecasting accuracy that has proven to fit data from certain types of game theory experiments, such as Keynesian beauty contests and entry games. Here, we focus on symmetric two-player-two-action games and establish an algorithm to find the players’ strategies according to the cognitive hierarchy approach. We show that the snowdrift game exhibits a pattern of behavior whose complexity grows as the cognitive levels of players increases. In addition to finding the solutions up to the third cognitive level, we demonstrate, in this theoretical frame, two new properties of snowdrift games: (i) any snowdrift game can be characterized by only a parameter, its class; (ii) they are anti-symmetric with respect to the diagonal of the pay-off’s space. Finally, we propose a model based on an evolutionary dynamics that captures the main features of the cognitive hierarchy theory. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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454 KiB  
Article
Modeling Poker Challenges by Evolutionary Game Theory
by Marco Alberto Javarone
Games 2016, 7(4), 39; https://doi.org/10.3390/g7040039 - 7 Dec 2016
Cited by 2 | Viewed by 8754
Abstract
We introduce a model for studying the evolutionary dynamics of Poker. Notably, despite its wide diffusion and the raised scientific interest around it, Poker still represents an open challenge. Recent attempts for uncovering its real nature, based on statistical physics, showed that Poker [...] Read more.
We introduce a model for studying the evolutionary dynamics of Poker. Notably, despite its wide diffusion and the raised scientific interest around it, Poker still represents an open challenge. Recent attempts for uncovering its real nature, based on statistical physics, showed that Poker in some conditions can be considered as a skill game. In addition, preliminary investigations reported a neat difference between tournaments and ‘cash game’ challenges, i.e., between the two main configurations for playing Poker. Notably, these previous models analyzed populations composed of rational and irrational agents, identifying in the former those that play Poker by using a mathematical strategy, while in the latter those playing randomly. Remarkably, tournaments require very few rational agents to make Poker a skill game, while ‘cash game’ may require several rational agents for not being classified as gambling. In addition, when the agent interactions are based on the ‘cash game’ configuration, the population shows an interesting bistable behavior that deserves further attention. In the proposed model, we aim to study the evolutionary dynamics of Poker by using the framework of Evolutionary Game Theory, in order to get further insights on its nature, and for better clarifying those points that remained open in the previous works (as the mentioned bistable behavior). In particular, we analyze the dynamics of an agent population composed of rational and irrational agents, that modify their behavior driven by two possible mechanisms: self-evaluation of the gained payoff, and social imitation. Results allow to identify a relation between the mechanisms for updating the agents’ behavior and the final equilibrium of the population. Moreover, the proposed model provides further details on the bistable behavior observed in the ‘cash game’ configuration. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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697 KiB  
Article
Coevolution of Cooperation and Layer Selection Strategy in Multiplex Networks
by Katsuki Hayashi, Reiji Suzuki and Takaya Arita
Games 2016, 7(4), 34; https://doi.org/10.3390/g7040034 - 1 Nov 2016
Cited by 4 | Viewed by 7574
Abstract
Recently, the emergent dynamics in multiplex networks, composed of layers of multiple networks, has been discussed extensively in network sciences. However, little is still known about whether and how the evolution of strategy for selecting a layer to participate in can contribute to [...] Read more.
Recently, the emergent dynamics in multiplex networks, composed of layers of multiple networks, has been discussed extensively in network sciences. However, little is still known about whether and how the evolution of strategy for selecting a layer to participate in can contribute to the emergence of cooperative behaviors in multiplex networks of social interactions. To investigate these issues, we constructed a coevolutionary model of cooperation and layer selection strategies in which each an individual selects one layer from multiple layers of social networks and plays the Prisoner’s Dilemma with neighbors in the selected layer. We found that the proportion of cooperative strategies increased with increasing the number of layers regardless of the degree of dilemma, and this increase occurred due to a cyclic coevolution process of game strategies and layer selection strategies. We also showed that the heterogeneity of links among layers is a key factor for multiplex networks to facilitate the evolution of cooperation, and such positive effects on cooperation were observed regardless of the difference in the stochastic properties of network topologies. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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946 KiB  
Article
The Influence of Mobility Rate on Spiral Waves in Spatial Rock-Paper-Scissors Games
by Mauro Mobilia, Alastair M. Rucklidge and Bartosz Szczesny
Games 2016, 7(3), 24; https://doi.org/10.3390/g7030024 - 9 Sep 2016
Cited by 34 | Viewed by 8642
Abstract
We consider a two-dimensional model of three species in rock-paper-scissors competition and study the self-organisation of the population into fascinating spiraling patterns. Within our individual-based metapopulation formulation, the population composition changes due to cyclic dominance (dominance-removal and dominance-replacement), mutations, and pair-exchange of neighboring [...] Read more.
We consider a two-dimensional model of three species in rock-paper-scissors competition and study the self-organisation of the population into fascinating spiraling patterns. Within our individual-based metapopulation formulation, the population composition changes due to cyclic dominance (dominance-removal and dominance-replacement), mutations, and pair-exchange of neighboring individuals. Here, we study the influence of mobility on the emerging patterns and investigate when the pair-exchange rate is responsible for spiral waves to become elusive in stochastic lattice simulations. In particular, we show that the spiral waves predicted by the system’s deterministic partial equations are found in lattice simulations only within a finite range of the mobility rate. We also report that in the absence of mutations and dominance-replacement, the resulting spiraling patterns are subject to convective instability and far-field breakup at low mobility rate. Possible applications of these resolution and far-field breakup phenomena are discussed. Full article
(This article belongs to the Special Issue Evolutionary Games and Statistical Physics of Social Networks)
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