Genetic algorithms (GAs) have been used widely in evolving game-playing strategies since the mid-1980's. This paper looks at a particular game | the iterated prisoner's dilemma game, which is of interest to many economists, social scientists, evolutionary computation researchers and computer scientists. The paper describes a computational approach which uses a GA to evolve strategies for the 2 ...

Evolutionary game theory describes systems where individual success is based on the interaction with others. We consider a system in which players unconditionally imitate more successful strategies but sometimes also explore the available strategies at random. Most research has focused on how strategies spread via genetic reproduction or cultural imitation, but random exploration of the availab...

Evolutionary game dynamics of two players with two strategies has been studied in great detail. These games have been used to model many biologically relevant scenarios, ranging from social dilemmas in mammals to microbial diversity. Some of these games may, in fact, take place between a number of individuals and not just between two. Here we address one-shot games with multiple players. As lon...

We examine dynamic models of evolutionary selection processes on asymmetric two-player games. Conditions are established under which dynamic selection processes will yield outcomes that respect iterated strict dominance. The addition of a stability requirement ensures that outcomes will be Nash equilibria. However, we find that stable outcomes need not respect weak dominance, and hence need not...

In plants, investment in height improves access to light, but incurs costs in construction and maintenance of the stem. Because the benefits of plant height depend on which other height strategies are present, competition for light can usefully be framed as a game-theoretic problem. The vertical structure of the world’s vegetation, which is inefficient for plant growth, can then be understood a...

Symmetric evolutionary games, i.e., evolutionary games with symmetric fitness matrices, have important applications in population genetics, where they can be used to model for example the selection and evolution of the genotypes of a given population. In this paper, we review the theory for obtaining optimal and stable strategies for symmetric evolutionary games, and provide some new proofs and...

Matrix games, defined by a set of strategies and a corresponding matrix of payoffs, are commonly used to model animal populations because they are both simple and generate meaningful results. It is generally assumed that payoffs are independent of time. However, the timing of contests in real populations may have a marked effect on the value of rewards. We consider matrix games where the payoff...

Evolutionary Game Theory is the study of strategic interactions among large populations of agents who base their decisions on simple, myopic rules. A major goal of the theory is to determine broad classes of decision procedures which both provide plausible descriptions of selfish behaviour and include appealing forms of aggregate behaviour. For example, properties such as the correlation betwee...

This is an introduction to the special issue titled ‘‘Collective behavior and evolutionary games’’ that is in the making at Chaos, Solitons & Fractals. The term collective behavior covers many different phenomena in nature and society. From bird flocks and fish swarms to social movements and herding effects [1–5], it is the lack of a central planner that makes the spontaneous emergence of somet...