An analysis of population dynamics with migration by evolutionary game theory

Teoh,, Shian Li (2013) An analysis of population dynamics with migration by evolutionary game theory. [Final Year Project Report] (Unpublished)

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Abstract

All of life is a game and migration lured by the prospect of receiving higher payoff is no exception. Games have players, strategies and payoffs. In evolutionary game theory, which is an extension of classical game theory, the strategies of players are determined genetically. The population dynamics can be modeled using the concept of evolutionary game theory in the form of replicator equations to describe the local details of the interactions between each individual and how the individual's behavior can be influenced by the payoff received by other individuals playing same strategies within the same population and across different populations. In this project, we address the independence of individuals' behavior by using replicator dynamics equations in two subpopulations without and with migration. The system of replicator equations is simulated in Simulink. A Graphical User Interface is constructed to provide a user friendly platform for understanding the individuals' behaviors for three different types of game, namely Prisoner's Dilemma, Stag-Hunt, and Hawk-Dove, representing social dilemma, cooperative, and anti-coordination among individuals. The evolution of population dynamics in two populations is the combination process of its intrinsic replication and also migration.

Item Type: Final Year Project Report
Additional Information: Project Report (B.Sc.) -- Universiti Malaysia Sarawak, 2013.
Uncontrolled Keywords: Evolutionary Game Theory, Graphical User Interface
Subjects: N Fine Arts > N Visual arts (General) For photography, see TR
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Unai
Date Deposited: 23 Aug 2022 02:21
Last Modified: 23 Aug 2022 02:21
URI: http://ir.unimas.my/id/eprint/39280

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