Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2012, Issue 2012 (31 Dec. 2012), pp.1-14, 14 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2012-11-28
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Abstract EN
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.
American Psychological Association (APA)
Wang, Zheng& Zhang, Jingling. 2012. Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem. Mathematical Problems in Engineering،Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1001848
Modern Language Association (MLA)
Wang, Zheng& Zhang, Jingling. Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem. Mathematical Problems in Engineering No. 2012 (2012), pp.1-14.
https://search.emarefa.net/detail/BIM-1001848
American Medical Association (AMA)
Wang, Zheng& Zhang, Jingling. Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem. Mathematical Problems in Engineering. 2012. Vol. 2012, no. 2012, pp.1-14.
https://search.emarefa.net/detail/BIM-1001848
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1001848