scholarly journals Inspection—Corruption Game of Illegal Logging and Other Violations: Generalized Evolutionary Approach

Mathematics ◽  
2021 ◽  
Vol 9 (14) ◽  
pp. 1619
Author(s):  
Vassili N. Kolokoltsov
Keyword(s):  
Tax Evasion ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Efficient Frontier ◽  
Point Of View ◽  
Quadratic Growth ◽  
Illegal Logging ◽  
Major Player ◽  
Game Theoretic ◽  
Evolutionary Point

Games of inspection and corruption are well developed in the game-theoretic literature. However, there are only a few publications that approach these problems from the evolutionary point of view. In previous papers of this author, a generalization of the replicator dynamics of the evolutionary game theory was suggested for inspection modeling, namely the pressure and resistance framework, where a large pool of small players plays against a distinguished major player and evolves according to certain myopic rules. In this paper, we develop this approach further in a setting of the two-level hierarchy, where a local inspector can be corrupted and is further controlled by the higher authority (thus combining the modeling of inspection and corruption in a unifying setting). Mathematical novelty arising in this investigation involves the analysis of the generalized replicator dynamics (or kinetic equation) with switching, which occurs on the “efficient frontier of corruption”. We try to avoid parameters that are difficult to observe or measure, leading to some clear practical consequences. We prove a result that can be called the “principle of quadratic fines”: We show that if the fine for violations (both for criminal businesses and corrupted inspectors) is proportional to the level of violations, the stable rest points of the dynamics support the maximal possible level of both corruption and violation. The situation changes if a convex fine is introduced. In particular, starting from the quadratic growth of the fine function, one can effectively control the level of violations. Concrete settings that we have in mind are illegal logging, the sales of products with substandard quality, and tax evasion.

scholarly journals eGAP: An Evolutionary Game Theoretic Approach to Random Forest Pruning

2020 ◽  
Vol 4 (4) ◽  
pp. 37
Author(s):  
Khaled Fawagreh ◽  
Mohamed Medhat Gaber
Keyword(s):  
Random Forest ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Theoretic Approach ◽  
Healthcare Applications ◽  
Healthcare Data ◽  
Smart Healthcare ◽  
Game Theoretic ◽  
Game Theoretic Approach

To make healthcare available and easily accessible, the Internet of Things (IoT), which paved the way to the construction of smart cities, marked the birth of many smart applications in numerous areas, including healthcare. As a result, smart healthcare applications have been and are being developed to provide, using mobile and electronic technology, higher diagnosis quality of the diseases, better treatment of the patients, and improved quality of lives. Since smart healthcare applications that are mainly concerned with the prediction of healthcare data (like diseases for example) rely on predictive healthcare data analytics, it is imperative for such predictive healthcare data analytics to be as accurate as possible. In this paper, we will exploit supervised machine learning methods in classification and regression to improve the performance of the traditional Random Forest on healthcare datasets, both in terms of accuracy and classification/regression speed, in order to produce an effective and efficient smart healthcare application, which we have termed eGAP. eGAP uses the evolutionary game theoretic approach replicator dynamics to evolve a Random Forest ensemble. Trees of high resemblance in an initial Random Forest are clustered, and then clusters grow and shrink by adding and removing trees using replicator dynamics, according to the predictive accuracy of each subforest represented by a cluster of trees. All clusters have an initial number of trees that is equal to the number of trees in the smallest cluster. Cluster growth is performed using trees that are not initially sampled. The speed and accuracy of the proposed method have been demonstrated by an experimental study on 10 classification and 10 regression medical datasets.

scholarly journals An oscillating tragedy of the commons in replicator dynamics with game-environment feedback

2016 ◽  
Vol 113 (47) ◽  
pp. E7518-E7525 ◽  
Author(s):  
Joshua S. Weitz ◽  
Ceyhun Eksin ◽  
Keith Paarporn ◽  
Sam P. Brown ◽  
William C. Ratcliff
Keyword(s):  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Tragedy Of The Commons ◽  
Individual Behavior ◽  
Global Maximum ◽  
Rational Choices ◽  
The Commons ◽  
Game Theoretic ◽  
Individual Actions ◽  
Game Environment

A tragedy of the commons occurs when individuals take actions to maximize their payoffs even as their combined payoff is less than the global maximum had the players coordinated. The originating example is that of overgrazing of common pasture lands. In game-theoretic treatments of this example, there is rarely consideration of how individual behavior subsequently modifies the commons and associated payoffs. Here, we generalize evolutionary game theory by proposing a class of replicator dynamics with feedback-evolving games in which environment-dependent payoffs and strategies coevolve. We initially apply our formulation to a system in which the payoffs favor unilateral defection and cooperation, given replete and depleted environments, respectively. Using this approach, we identify and characterize a class of dynamics: an oscillatory tragedy of the commons in which the system cycles between deplete and replete environmental states and cooperation and defection behavior states. We generalize the approach to consider outcomes given all possible rational choices of individual behavior in the depleted state when defection is favored in the replete state. In so doing, we find that incentivizing cooperation when others defect in the depleted state is necessary to avert the tragedy of the commons. In closing, we propose directions for the study of control and influence in games in which individual actions exert a substantive effect on the environmental state.

Generalized Replicator Dynamics as a Model of Specialization and Diversity in Societies

1998 ◽  
Vol 01 (04) ◽  
pp. 325-359 ◽  
Author(s):  
Vivek S. Borkar ◽  
Sanjay Jain ◽  
Govindan Rangarajan
Keyword(s):  
Mixed Strategy ◽  
Replicator Dynamics ◽  
Pure Strategy ◽  
Evolutionary Game ◽  
Payoff Matrix ◽  
Theoretic Model ◽  
Final States ◽  
Game Theoretic ◽  
Game Theoretic Model ◽  
Pure Strategies

We consider a generalization of replicator dynamics as a non-cooperative evolutionary game-theoretic model of a community of N agents. All agents update their individual mixed strategy profiles to increase their total payoff from the rest of the community. The properties of attractors in this dynamics are studied. Evidence is presented that under certain conditions the typical attractors of the system are corners of state space where each agent has specialized to a pure strategy, and/or the community exhibits diversity, i.e., all strategies are represented in the final states. The model suggests that new pure strategies whose payoff matrix elements satisfy suitable inequalities with respect to the existing ones can destabilize existing attractors if N is sufficiently large, and be regarded as innovations that enhance the diversity of the community.

scholarly journals An oscillating tragedy of the commons in replicator dynamics with game-environment feedback

2016 ◽  
Author(s):  
Joshua S. Weitz ◽  
Ceyhun Eksin ◽  
Keith Paarporn ◽  
Sam P. Brown ◽  
William C. Ratcliff
Keyword(s):  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Tragedy Of The Commons ◽  
Individual Behavior ◽  
Global Maximum ◽  
New Class ◽  
Rational Choices ◽  
The Commons ◽  
Game Theoretic ◽  
Game Environment

A tragedy of the commons occurs when individuals take actions to maximize their payoffs even as their combined payoff is less than the global maximum had the players coordinated. The originating example is that of over-grazing of common pasture lands. In game theoretic treatments of this example there is rarely consideration of how individual behavior subsequently modifies the commons and associated payoffs. Here, we generalize evolutionary game theory by proposing a class of replicator dynamics with feedback-evolving games in which environment-dependent payoffs and strategies coevolve. We initially apply our formulation to a system in which the payoffs favor unilateral defection and cooperation, given replete and depleted environments respectively. Using this approach we identify and characterize a new class of dynamics: an oscillatory tragedy of the commons in which the system cycles between deplete and replete environmental states and cooperation and defection behavior states. We generalize the approach to consider outcomes given all possible rational choices of individual behavior in the depleted state when defection is favored in the replete state. In so doing we find that incentivizing cooperation when others defect in the depleted state is necessary to avert the tragedy of the commons. In closing, we propose new directions for the study of control and influence in games in which individual actions exert a substantive effect on the environmental state.

On the Strategic Complementarity of Skilled Workers and Technological Innovation: Which Determines Which?

2021 ◽  
pp. 232102222110243
Author(s):  
Elvio Accinelli ◽  
Armando García ◽  
Edgar J. Sánchez Carrera ◽  
Jorge Zazueta
Keyword(s):  
Dynamical System ◽  
Initial Conditions ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Point Of View ◽  
Skilled Workers ◽  
Strategic Complementarity ◽  
Long Run ◽  
Short Run ◽  
The Government

In this document, we analyse the strategic complementarity between technological investment and investment in training by workers. We show that, beyond the importance of the answer to the question about which factor determines which, initial minimal conditions in both factors are required to start a long-run social development process. If these minimums are not met, the economy can become a self-satisfied economy, with a social mediocre performance but, at least in the short run, successful from the individual point of view. We consider that either manager of firms as workers are rational agents who make decisions about their future behaviour, considering the current state of the economy, understanding for such, the percentage of innovative and non-innovative firms in the market and the percentage of skilled and unskilled workers in the labour market. While managers decide the best way to invest, workers decide whether to invest or not in the upgrade or in the development of their skills to face the new challenges posed by technological change. The evolution of the economy is summarized in a complex dynamical system represented by a coupled dynamical system very close to the replicator dynamics considered in evolutionary game theory. In this way, we show that the initial conditions play a crucial role to understand the possibilities of future performance of the economy in each country, and, on the other hand, we analyse the conditions that make possible or necessary the intervention of the government in the economy. JEL Codes: C72, C73, O11, O55, K42

Evolutionary game analysis of information sharing by institutional investors

2021 ◽  
pp. 1-9
Author(s):  
Hua Li ◽  
Qingqing Lou ◽  
Qiubai Sun ◽  
Bowen Li
Keyword(s):  
Information Sharing ◽  
Institutional Investors ◽  
Information Exchange ◽  
Evolutionary Game ◽  
Stable State ◽  
Point Of View ◽  
Game Model ◽  
Game Analysis ◽  
Relationship Network ◽  
The Relationship

In order to solve the conflict of interests of institutional investors, this paper uses evolutionary game model. From the point of view of information sharing, this paper discusses four different situations. Only when the sum of risk and cost is less than the penalty of free riding, the evolution of institutional investors will eventually incline to the stable state of information sharing. That is, the phenomenon of hugging. The research shows that the institutional investors are not independent of each other, but the relationship network of institutional investors for the purpose of information exchange. The content of this paper enriches the research on information sharing of institutional investors.

scholarly journals System Dynamics Model for the Evolutionary Behaviour of Government Enterprises and Consumers in China’s New Energy Vehicle Market

2020 ◽  
Vol 12 (4) ◽  
pp. 1578 ◽  
Author(s):  
Hongxia Sun ◽  
Yao Wan ◽  
Huirong Lv
Keyword(s):  
System Dynamics ◽  
Motor Vehicle ◽  
Replicator Dynamics ◽  
Evolutionary Game ◽  
Practical Significance ◽  
Subsidy Policy ◽  
New Energy ◽  
New Energy Vehicle ◽  
The Impact ◽  
Vehicle Market

Exhaust pollution and energy crises are worsening worldwide. China has become the largest motor vehicle producer; thus, promoting the use of new energy vehicles (NEVs) in China has important practical significance. In this paper, considering the limited rationality of governments, NEV enterprises and consumers, we study the subsidy policy of the China NEV market using the evolutionary game and system dynamics (SD) methods. First, a tripartite evolutionary game model is developed and the replicator dynamics equations and Jacobian matrix are obtained. A SD simulation of the model was conducted to further clarify the impact of the initial market proportion and three variables used in the model. The results show that the initial market proportion affects the evolution speed but does not affect the evolution result when the three group players all choose a mixed strategy. For governments, they should not hastily cancel price subsidies provided to consumers; rather, they should dynamically adjust the rate of the subsidy decrease and increase the consumers’ extra cost for purchasing fuel vehicles (FVs). NEV enterprises should appropriately increase their investments in the research and development (R&D) of NEVs.

scholarly journals “Information”—from an Evolutionary Point of View

Information ◽  
2014 ◽  
Vol 5 (2) ◽  
pp. 272-284 ◽  
Author(s):  
Walter Kofler
Keyword(s):  
Point Of View ◽  
Evolutionary Point
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