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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Main Authors:	Zheng Wang, Jingling Zhang
Format:	Article
Language:	English
Published:	Hindawi Limited 2012-01-01
Series:	Mathematical Problems in Engineering
Online Access:	http://dx.doi.org/10.1155/2012/709473

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spelling	doaj-bd11f2760dbc4d509cffeb1c7fecdfb12020-11-24T20:41:20ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472012-01-01201210.1155/2012/709473709473Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game ProblemZheng Wang0Jingling Zhang1The College Computer Engineering, Zhejiang Institute of Mechanical and Electrical Engineering, Hangzhou 310053, ChinaComputer Science and Technology College, Zhejiang University of Technology, Hangzhou 310014, ChinaThe 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.http://dx.doi.org/10.1155/2012/709473
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Zheng Wang Jingling Zhang
spellingShingle	Zheng Wang Jingling Zhang Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem Mathematical Problems in Engineering
author_facet	Zheng Wang Jingling Zhang
author_sort	Zheng Wang
title	Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
title_short	Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
title_full	Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
title_fullStr	Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
title_full_unstemmed	Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem
title_sort	agent-based modeling and genetic algorithm simulation for the climate game problem
publisher	Hindawi Limited
series	Mathematical Problems in Engineering
issn	1024-123X 1563-5147
publishDate	2012-01-01
description	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.
url	http://dx.doi.org/10.1155/2012/709473
work_keys_str_mv	AT zhengwang agentbasedmodelingandgeneticalgorithmsimulationfortheclimategameproblem AT jinglingzhang agentbasedmodelingandgeneticalgorithmsimulationfortheclimategameproblem
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Agent-Based Modeling and Genetic Algorithm Simulation for the Climate Game Problem

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