Evolution and the Theory of Games

Smith, John Maynard

doi:10.1017/cbo9780511806292

Cited by 5,474 publications

(1,759 citation statements)

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“…[1][2][3][4]. The development of macroscopic complexity seems to spring very naturally even in the case of very simple cyclic predator-prey models with a low number of species, as in the case of the classic rock-paper-scissor (RPS) game [5][6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Interfaces with internal structures in generalized rock-paper-scissors models

et al. 2014

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In this work we investigate the development of stable dynamical structures along interfaces separating domains belonging to enemy partnerships, in the context of cyclic predator-prey models with an even number of species N ≥ 8. We use both stochastic and field theory simulations in one and two spatial dimensions, as well as analytical arguments, to describe the association at the interfaces of mutually neutral individuals belonging to enemy partnerships and to probe their role in the development of the dynamical structures at the interfaces. We identify an interesting behaviour associated to the symmetric or asymmetric evolution of the interface profiles depending on whether N/2 is odd or even, respectively. We also show that the macroscopic evolution of the interface network is not very sensitive internal structure of the interfaces. Although this work focus on cyclic predator prey-models with an even number of species, we argue that the results are expected to be quite generic in the context of spatial stochastic May-Leonard models.

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Section: Introductionmentioning

confidence: 99%

Interfaces with internal structures in generalized rock-paper-scissors models

et al. 2014

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“…Another notable omission is evolutionary game theory [9]. Traditionally, game theory attempts to model strategic decisions of a number of interacting individual players, where the game and the players are concepts that can be interpreted quite broadly.…”

Section: Topics Coveredmentioning

confidence: 99%

A taxonomy of biologically inspired research in computer networking

2010

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a b s t r a c tThe natural world is enormous, dynamic, incredibly diverse, and highly complex. Despite the inherent challenges of surviving in such a world, biological organisms evolve, self-organize, self-repair, navigate, and flourish. Generally, they do so with only local knowledge and without any centralized control. Our computer networks are increasingly facing similar challenges as they grow larger in size, but are yet to be able to achieve the same level of robustness and adaptability. Many research efforts have recognized these parallels, and wondered if there are some lessons to be learned from biological systems. As a result, biologically inspired research in computer networking is a quickly growing field. This article begins by exploring why biology and computer network research are such a natural match. We then present a broad overview of biologically inspired research, grouped by topic, and classified in two ways: by the biological field that inspired each topic, and by the area of networking in which the topic lies. In each case, we elucidate how biological concepts have been most successfully applied. In aggregate, we conclude that research efforts are most successful when they separate biological design from biological implementation -that is to say, when they extract the pertinent principles from the former without imposing the limitations of the latter.

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“…The dynamics of games can have different driving mechanisms. In "evolutionary game theory" [5], devised by John Maynard Smith in 1973, agents (living organisms) whose strategies are effective against competitors survive and reproduce more rapidly. This replicates their genes, and strategies they encode, in higher concentration in future generations.…”

Section: Introductionmentioning

confidence: 99%

Limit cycles and the benefits of a short memory in rock-paper-scissors games

Burridge

2015

Phys. Rev. E

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When playing games in groups, it is an advantage for individuals to have accurate statistical information on the strategies of their opponents. Such information may be obtained by remembering previous interactions. We consider a rock-scissors-paper game in which agents are able to recall their last m interactions, used to estimate the behaviour of their opponents. At critical memory length, a Hopf bifurcation leads to the formation of stable limit cycles. In a mixed population, agents with longer memories have an advantage, provided the system has a stable fixed point, and there is some asymmetry in the payoffs of the pure strategies. However, at a critical concentration of long memory agents, the appearance of limit cycles destroys their advantage. By introducing population dynamics that favours successful agents, we show that the system evolves toward the bifurcation point.

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Evolution and the Theory of Games

Cited by 5,474 publications

References 1 publication

Interfaces with internal structures in generalized rock-paper-scissors models

Interfaces with internal structures in generalized rock-paper-scissors models

A taxonomy of biologically inspired research in computer networking

Limit cycles and the benefits of a short memory in rock-paper-scissors games

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