scholarly journals On a continuous mixed strategies model for evolutionary game theory

2011 ◽  
Vol 4 (1) ◽  
pp. 187-213 ◽  
Author(s):  
Astridh Boccabella ◽  
◽  
Roberto Natalini ◽  
Lorenzo Pareschi ◽  
◽  
...  
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Mixed Strategies

Game theory and the evolution of behaviour

1984 ◽  
Vol 7 (1) ◽  
pp. 95-101 ◽  
Author(s):  
J. Maynard Smith
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Mixed Strategies ◽  
Learning Behaviour ◽  
Prior Residence ◽  
The Asymmetry

AbstractEvolutionary game theory is a method of analysing the evolution of phenotypes (including types of behaviour) when the fitness of a particular phenotype depends onits frequency in the population. It was first applied to pairwise contests between animals. Such contests usually have some associated asymmetry, in size, prior residence, or age or sex status; the theory predicts that the asymmetry will be used as a cue to settlethe contest, and this is found to be the case. The theory can also be applied when individuals are competing against the population as a whole, or some part of it. In such cases, the evolution of variable behaviour - so-called mixed strategies - is predicted; actual examples of this are given. Game theory can be applied to the evolution of cooperative as well as of antagonistic behaviour. An analysis of the evolution of learning leads to testable predictions about learning behaviour.

scholarly journals A Study of Taxi Service Mode Choice Based on Evolutionary Game Theory

2019 ◽  
Vol 2019 ◽  
pp. 1-17
Author(s):  
Zhu Bai ◽  
Mingxia Huang ◽  
Shuai Bian ◽  
Huandong Wu
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Mode Choice ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Game Model ◽  
Stable States ◽  
Taxi Service ◽  
Service Mode ◽  
The Impact

The emergence of online car-hailing service provides an innovative approach to vehicle booking but has negatively influenced the taxi industry in China. This paper modeled taxi service mode choice based on evolutionary game theory (EGT). The modes included the dispatching and online car-hailing modes. We constructed an EGT framework, including determining the strategies and the payoff matrix. We introduced different behaviors, including taxi company management, driver operation, and passenger choice. This allowed us to model the impact of these behaviors on the evolving process of service mode choice. The results show that adjustments in taxi company, driver, and passenger behaviors impact the evolutionary path and convergence speed of our evolutionary game model. However, it also reveals that, regardless of adjustments, the stable states in the game model remain unchanged. The conclusion provides a basis for studying taxi system operation and management.

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