An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries

Zhengqiu Zhu, Bin Chen, Sihang Qiu, Rongxiao Wang, Feiran Chen, Yiping Wang and Xiaogang Qiu
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Zhengqiu Zhu: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
Bin Chen: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
Sihang Qiu: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
Rongxiao Wang: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
Feiran Chen: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China
Yiping Wang: The Naval 902 Factory, Shanghai 200083, China
Xiaogang Qiu: College of System Engineering, National University of Defense Technology, 109 Deya Road, Changsha 410073, China

IJERPH, 2018, vol. 15, issue 4, 1-20

Abstract: Chemical production activities in industrial districts pose great threats to the surrounding atmospheric environment and human health. Therefore, developing appropriate and intelligent pollution controlling strategies for the management team to monitor chemical production processes is significantly essential in a chemical industrial district. The literature shows that playing a chemical plant environmental protection (CPEP) game can force the chemical plants to be more compliant with environmental protection authorities and reduce the potential risks of hazardous gas dispersion accidents. However, results of the current literature strictly rely on several perfect assumptions which rarely hold in real-world domains, especially when dealing with human adversaries. To address bounded rationality and limited observability in human cognition, the CPEP game is extended to generate robust schedules of inspection resources for inspection agencies. The present paper is innovative on the following contributions: (i) The CPEP model is extended by taking observation frequency and observation cost of adversaries into account, and thus better reflects the industrial reality; (ii) Uncertainties such as attackers with bounded rationality, attackers with limited observation and incomplete information (i.e., the attacker’s parameters) are integrated into the extended CPEP model; (iii) Learning curve theory is employed to determine the attacker’s observability in the game solver. Results in the case study imply that this work improves the decision-making process for environmental protection authorities in practical fields by bringing more rewards to the inspection agencies and by acquiring more compliance from chemical plants.

Keywords: chemical plant environmental protection game; human cognition; bounded rationality; limited observation; learning curves (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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