Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem

The cooperative game of global temperature lacks automaticity and emotional jamming. To solve this issue, an agent-based modelling method is developed based on Milinski’s noncooperative game experiments. In addition, genetic algorithm is used to improve the investment strategy of each agent. Simulat...

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Veröffentlicht in:Mathematical Problems in Engineering Jg. 2012; H. 2012; S. 1204 - 1217-476
Hauptverfasser: Wang, Zheng, Zhang, Jingling
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Limiteds 01.01.2012
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Schlagworte:
Agent-based models
Climate change
Climate models
Economic models
Environmental protection
Game theory
Games
Genetic algorithms
Investment strategy
Jamming
Mathematical problems
Reagents
Simulation
Studies
ISSN:1024-123X, 1563-5147
Online-Zugang:Volltext
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Zusammenfassung:The cooperative game of global temperature lacks automaticity and emotional jamming. To solve this issue, an agent-based modelling method is developed based on Milinski’s noncooperative game experiments. In addition, genetic algorithm is used to improve the investment strategy of each agent. Simulations are carried out by designing different coding schemes, mutation schemes, and fitness functions. It is demonstrated that the method can achieve maximum benefits under the premise of the agent non-cooperative game through encouraging optimal individuals. The results provide a sound basis for developing tools and methods to support the simulation of climate game strategy that involves multiple stakeholders.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:1024-123X
1563-5147
DOI:10.1155/2012/709473