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"Game Protection"
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Multiplayer Repeated Game of Environmental Protection between Government and Enterprises
An important source of environmental pollution in our country is industrial enterprises, which have caused great damage to the ecological environment. The government continues to pay more attention to environmental protection, while enterprises aim to maximize their own interests, to the detriment of the overall social interests. We propose a probability game with economic incentive mechanism between government and polluting enterprises. In the game, each enterprise decides whether to invest in environmental protection. Considering the benefits of selfish enterprises, local governments, as managers, adopt a zero determinant (ZD) strategy for enterprises. This strategy has played an important role in minimizing social costs. It has introduced the entire society's environmental protection investment into the game. We simulate the game model to evaluate the performance of the ZD strategy numerically.
Journal Article
Heartwood : a novel
\"In the heart of the Maine woods, an experienced Appalachian Trail hiker goes missing. She is forty-two-year-old Valerie Gillis, who has vanished 200 miles from her final destination. Alone in the wilderness, Valerie pours her thoughts into fractured, poetic letters to her mother as she battles the elements and struggles to keep hoping. At the heart of the investigation is Beverly, the determined Maine State Game Warden tasked with finding Valerie, who leads the search on the ground. Meanwhile, Lena, a seventy-six-year-old birdwatcher in a Connecticut retirement community, becomes an unexpected armchair detective. Roving between these compelling narratives, a puzzle emerges, intensifying the frantic search, as Valerie's disappearance may not be accidental.\"--Provided by publisher.
BOOK
Challenges in understanding and communicating the risk of zoonotic disease spillover from wild animal meat
Discussions around managing hunting and the consumption of wild animal meat increasingly emphasizes public health concerns and the risk of zoonotic spillover. In this article, we explore factors that may lead to under- or overestimating health risks from wild meat and break down key terminology for a multidisciplinary audience. We outline key principles of disease ecology and epidemiology that are often overlooked when quantifying spillover risk, and reflect on the importance of contextualizing health risks relative to food-health systems more broadly. We discuss how misrepresenting risks, intentionally or unintentionally, to justify conservation practices can have unintended negative conservation and public health consequences—despite the importance of conservation in protecting human health more broadly. We stress the importance of considering individual and local health outcomes (food security, neglected tropical diseases, etc.), not only those impacting global health (i.e. pandemic prevention). Finally, we advocate for evidence-informed, context-appropriate strategies for wild meat management.
Journal Article
An Extended Chemical Plant Environmental Protection Game on Addressing Uncertainties of Human Adversaries
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.
Journal Article
Strategically Patrolling in a Chemical Cluster Addressing Gas Pollutants’ Releases through a Game-Theoretic Model
Chemical production activities in chemical clusters, if not well managed, will pose great threats to the surrounding air environment and impose great burden on emergency handling. Therefore, it is urgent and substantial in a chemical cluster to develop proper and suitable pollution controlling strategies for an inspection agency to monitor chemical production processes. Apart from the static monitoring resources (e.g., monitoring stations and gas sensor modules), patrolling by mobile vehicle resources is arranged for better detecting the illegal releasing behaviors of emission spots in different chemical plants. However, it has been proven that the commonly used patrolling strategies (i.e., the fixed route strategy and the purely randomized route strategy) are non-optimal and fail to interact with intelligent chemical plants. Therefore, we proposed the Chemical Cluster Environmental Protection Patrolling (CCEPP) game to tackle the problem in this paper. Through combining the source estimation process, the game is modeled to detect the illegal releasing behaviors of chemical plants by randomly and strategically arranging the patrolling routes and intensities in different chemical sites. In this game-theoretic model, players (patroller and chemical sites), strategies, payoffs, and game solvers are modeled in sequence. More importantly, this game model also considers traffic delays or bounded cognition of patrollers on patrolling plans. Therefore, a discrete Markov decision process was used to model this stochastic process. Further, the model is illustrated by a case study. Results imply that the patrolling strategy suggested by the CCEPP game outperforms both the fixed route strategy and the purely randomized route strategy.
Journal Article