scholarly journals Evolutionary games on cycles

2006 ◽  
Vol 273 (1598) ◽  
pp. 2249-2256 ◽  
Author(s):  
Hisashi Ohtsuki ◽  
Martin A Nowak
Keyword(s):  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Weak Selection ◽  
Stochastic Effects ◽  
Frequency Dependent Selection ◽  
Game Dynamics ◽  
Case Selection ◽  
Mixed Populations ◽  
Update Rules

Traditional evolutionary game theory explores frequency-dependent selection in well-mixed populations without spatial or stochastic effects. But recently there has been much interest in studying the evolutionary game dynamics in spatial settings, on lattices and other graphs. Here, we present an analytic approach for the stochastic evolutionary game dynamics on the simplest possible graph, the cycle. For three different update rules, called ‘birth–death’ (BD), ‘death–birth’ (DB) and ‘imitation’ (IM), we derive exact conditions for natural selection to favour one strategy over another. As specific examples, we consider a coordination game and Prisoner's Dilemma. In the latter case, selection can favour cooperators over defectors for DB and IM updating. We also study the case where the replacement graph of evolutionary updating remains a cycle, but the interaction graph for playing the game is a complete graph. In this setting, all three update rules lead to identical conditions in the limit of weak selection, where we find the ‘1/3-law’ of well-mixed populations.

scholarly journals Aspiration dynamics of multi-player games in finite populations

2014 ◽  
Vol 11 (94) ◽  
pp. 20140077 ◽  
Author(s):  
Jinming Du ◽  
Bin Wu ◽  
Philipp M. Altrock ◽  
Long Wang
Keyword(s):  
Evolutionary Game ◽  
Pairwise Comparison ◽  
Evolutionary Games ◽  
Structured Populations ◽  
Weak Selection ◽  
Additional Information ◽  
Average Abundance ◽  
Imperfect Rationality ◽  
Update Rules ◽  
Limiting Case

On studying strategy update rules in the framework of evolutionary game theory, one can differentiate between imitation processes and aspiration-driven dynamics. In the former case, individuals imitate the strategy of a more successful peer. In the latter case, individuals adjust their strategies based on a comparison of their pay-offs from the evolutionary game to a value they aspire, called the level of aspiration. Unlike imitation processes of pairwise comparison, aspiration-driven updates do not require additional information about the strategic environment and can thus be interpreted as being more spontaneous. Recent work has mainly focused on understanding how aspiration dynamics alter the evolutionary outcome in structured populations. However, the baseline case for understanding strategy selection is the well-mixed population case, which is still lacking sufficient understanding. We explore how aspiration-driven strategy-update dynamics under imperfect rationality influence the average abundance of a strategy in multi-player evolutionary games with two strategies. We analytically derive a condition under which a strategy is more abundant than the other in the weak selection limiting case. This approach has a long-standing history in evolutionary games and is mostly applied for its mathematical approachability. Hence, we also explore strong selection numerically, which shows that our weak selection condition is a robust predictor of the average abundance of a strategy. The condition turns out to differ from that of a wide class of imitation dynamics, as long as the game is not dyadic. Therefore, a strategy favoured under imitation dynamics can be disfavoured under aspiration dynamics. This does not require any population structure, and thus highlights the intrinsic difference between imitation and aspiration dynamics.

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Evolutionary game dynamics of combining the payoff-driven and conformity-driven update rules

2020 ◽  
Vol 140 ◽  
pp. 110146
Author(s):  
Jingyan Lin ◽  
Changwei Huang ◽  
Qionglin Dai ◽  
Junzhong Yang
Keyword(s):  
Evolutionary Game ◽  
Game Dynamics ◽  
Update Rules

Evolutionary game dynamics of combining the imitation and aspiration-driven update rules

2019 ◽  
Vol 100 (2) ◽  
Author(s):  
Xianjia Wang ◽  
Cuiling Gu ◽  
Jinhua Zhao ◽  
Ji Quan
Keyword(s):  
Evolutionary Game ◽  
Game Dynamics ◽  
Update Rules

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Evolutionary Game Theory

2021 ◽  
Vol 1 (2) ◽  
pp. 20-28
Author(s):  
Arij Michel
Keyword(s):  
Game Theory ◽  
Institutional Change ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Future Research ◽  
Theory Analysis ◽  
Game Analysis ◽  
Advantages And Disadvantages ◽  
Development Direction

The article uses evolutionary game theory analysis as the research object, which is the most commonly used research method of institutional change, and summarizes some methods in the research of institutional change, and points out the advantages and disadvantages of evolutionary game analysis in the research of institutional change and through the comparison of cutting-edge methods and evolutionary games to see the development direction of future research institutional changes.

Evolutionary game dynamics of death-birth process with interval payoffs on graphs

2021 ◽  
pp. 1-12
Author(s):  
Bichuan Jiang ◽  
Lan Shu
Keyword(s):  
Natural Selection ◽  
Dynamic Equation ◽  
Prisoner's Dilemma ◽  
Evolutionary Game ◽  
Prisoner’S Dilemma ◽  
Fixation Probability ◽  
Weak Selection ◽  
Birth Process ◽  
Prisoner’S Dilemma Game ◽  
Game Dynamics

In this paper, we study the evolutionary game dynamics of the death-birth process with interval payoffs on graphs. First of all, we derive the interval replication dynamic equation. Secondly, we derive the fixation probability of the B-C prisoner’s dilemma game based on the death-birth process under the condition of weak selection, analyze the condition of the strategy fixed in the population, that is the condition of strategy A being dominant is analyzed. So we can judge whether natural selection is beneficial to strategy A in the game process through this condition. Finally, the feasibility of this method is verified by several examples.

Evolutionary Games and Local Dynamics

2015 ◽  
Vol 17 (02) ◽  
pp. 1540016 ◽  
Author(s):  
Philippe Uyttendaele ◽  
Frank Thuijsman
Keyword(s):  
Game Theory ◽  
Population Dynamics ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Global Dynamics ◽  
Local Interactions ◽  
Local Dynamics

In this paper, we examine several options for modeling local interactions within the framework of evolutionary game theory. Several examples show that there is a major difference between population dynamics using local dynamics versus global dynamics. Moreover, different modeling choices may lead to very diverse results.

Resource Allocation as an Evolving Strategy

1996 ◽  
Vol 4 (1) ◽  
pp. 33-55 ◽  
Author(s):  
Sverrir Olafsson
Keyword(s):  
Network Management ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Network Services ◽  
Efficient Utilization ◽  
Evolutionarily Stable Strategies ◽  
Network Utilization ◽  
Function Network ◽  
Evolutionarily Stable

The efficient utilization of resources is an issue of essential importance in modern network management. The emergence of increasingly complicated and continuously changing network services requires softer and fuzzier methods in network management. In this paper we demonstrate how evolutionary game theory can be used for an efficient allocation of service requirements onto an ensemble of heterogeneous network components. By incorporating differentiated pricing structures into a system utility function, network agents are encouraged to increase their usage of those components that are presently badly utilized. It is demonstrated how this approach can enhance network utilization significantly. Some new results regarding evolutionarily stable strategies in nonlinear evolutionary games are also reported.

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