• Title/Summary/Keyword: evolutionary game theory

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The game of safety behaviors among different departments of the nuclear power plants

  • Yuan, Da;Wang, Hanqing;Wu, Jian
    • Nuclear Engineering and Technology
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    • v.54 no.3
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    • pp.909-916
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    • 2022
  • To study the developments and variations of unsafe behaviors in nuclear power plants thus reduce the possibility of human-related accidents, this paper, based on the Game Theory, focused on the changes in benefits of the Department of Management, Operational and Emergency in a nuclear power plant, and established the expected revenue functions of these departments. Additionally, the preventive measures of unsafe behaviors in nuclear power plants were also presented in terms of these 3 departments. Results showed that the violations of the Operation Department (OD) and the Emergency Department (ED) were not only relevant with the factors such as their own risks, costs, and the responsibility-sharing due to accidents, but also affected by the safety investments from the Management Department (MD). Furthermore, results also showed that the accident-induced responsibility-sharing of both the OD and the ED would rise, if the MD increased the investments in safety. As a result, the probability of violation behaviors of these 3 departments would be attenuated consciously, which would reduce the unsafe behaviors in the nuclear power plants significantly.

Analysis on Iterated Prisoner's Dilemma Game using Binary Particle Swarm Optimization (이진 입자 군집 최적화를 이용한 반복 죄수 딜레마 게임 분석)

  • Lee, Sangwook
    • The Journal of the Korea Contents Association
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    • v.20 no.12
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    • pp.278-286
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    • 2020
  • The prisoner's dilemma game which is a representative example of game theory is being studied with interest by many economists, social scientists, and computer scientists. In recent years, many researches on computational approaches that apply evolutionary computation techniques such as genetic algorithms and particle swarm optimization have been actively conducted to analyze prisoner dilemma games. In this study, we intend to evolve a strategy for a iterated prisoner dilemma game participating two or more players using three different binary particle swarm optimization techniques. As a result of experimenting by applying three kinds of binary particle swarm optimization to the iterated prisoner's dilemma game, it was confirmed that mutual cooperation can be established even among selfish participants to maximize their own gains. However, it was also confirmed that the more participants, the more difficult to establish a mutual cooperation relationship.