Habit or Utility: A Key Choice Point in Promoting the Adoption of Telehealth in China

Telehealth, as an indispensable means of technical support in the Healthy China Strategy, currently has less than 20 percent adoption rate in China despite a great deal of government policies and investments. In the current study, to analyse the influencing factors behind doctors’ and patients’ adoption of telehealth, an asymmetric dynamic evolutionary game model of doctor-patient behaviour selection was established. Based on the model solution, the evolutionarily stable strategies that emerge in different situations were analysed. The results show that it is difficult for the adoption of telehealth in China to keep pace with coverage due to the “dual low” nature of telehealth: both doctors’ utility from telehealth and patients’ telehealth cost threshold are too low to incentivize adoption. The strategy to promote the adoption of telehealth in China should include providing adequate training for doctors and patients on the use of telehealth technology, rewarding doctors who provide telehealth services and raising the threshold cost of patient’s telehealth adoption.

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Research on Optimization of Array Honeypot Defense Strategies Based on Evolutionary Game Theory

Mathematics ◽

10.3390/math9080805 ◽

2021 ◽

Vol 9 (8) ◽

pp. 805

Author(s):

Leyi Shi ◽

Xiran Wang ◽

Huiwen Hou

Keyword(s):

Replicator Dynamics ◽

Evolutionarily Stable Strategy ◽

Evolutionary Game ◽

Game Model ◽

Evolutionarily Stable Strategies ◽

Defense Strategies ◽

Active Defense ◽

Defense Technology ◽

The Stability ◽

Evolutionarily Stable

Honeypot has been regarded as an active defense technology that can deceive attackers by simulating real systems. However, honeypot is actually a static network trap with fixed disposition, which is easily identified by anti-honeypot technology. Thus, honeypot is a “passive” active defense technology. Dynamic honeypot makes up for the shortcomings of honeypot, which dynamically adjusts defense strategies with the attack of hackers. Therefore, the confrontation between defenders and attackers is a strategic game. This paper focuses on the non-cooperative evolutionary game mechanism of bounded rationality, aiming to improve the security of the array honeypot system through the evolutionarily stable strategies derived from the evolutionary game model. First, we construct a three-party evolutionary game model of array honeypot, which is composed of defenders, attackers and legitimate users. Secondly, we formally describe the strategies and revenues of players in the game, and build the three-party game payoff matrices. Then the evolutionarily stable strategy is obtained by analyzing the Replicator Dynamics of various parties. In addition, we discuss the equilibrium condition to get the influence of the number of servers N on the stability of strategy evolution. MATLAB and Gambit simulation experiment results show that deduced evolutionarily stable strategies are valid in resisting attackers.

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Sustainable tourism modeling: Pricing decisions and evolutionarily stable strategies for competitive tour operators

Tourism Economics ◽

10.1177/1354816618806729 ◽

2018 ◽

Vol 25 (5) ◽

pp. 779-799 ◽

Cited By ~ 7

Author(s):

Yong He ◽

Peng He ◽

Feifei Xu ◽

Chunming (Victor) Shi

Keyword(s):

Sustainable Tourism ◽

Evolutionary Game ◽

Innovation Strategy ◽

Cost Advantage ◽

Evolutionarily Stable Strategies ◽

Environment Friendly ◽

Pricing Decisions ◽

Green Tourism ◽

The Government ◽

Evolutionarily Stable

In this article, we investigate two competitive tour operators (TOs) who choose between traditional tourism strategy (strategy T) and green tourism innovation strategy (strategy G). Our article attempts to address the following important issues using evolutionary game models: when would TOs facing environment-friendly tourists adopt the strategy G? How do TOs set product prices under different strategy combinations? How can the government effectively motivate TOs to pursue green tourism? Our research results show that a green tourism innovation pioneer could monopolize the market under certain conditions. Furthermore, when the environmental preference of tourists is sufficiently low, no TOs would adopt the strategy G; when it is moderate, only the TO with cost advantage (stronger TO) would adopt the strategy G; when it is sufficiently high, both TOs would select the strategy G. Our research also demonstrates that the stronger TO implements the strategy G mostly independent of the rival’s decisions, but the opposite is true for the TO with cost disadvantage (weaker TO). We further investigate potential government subsidies that can motivate TOs to carry out green tourism simultaneously. Our results suggest that to be more effective, the government first offer the green subsidy to highly competitive tourism locations and/or more innovative TOs.

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Evolutionary Game Theory: A Generalization of the ESS Definition

International Game Theory Review ◽

10.1142/s0219198919500051 ◽

2019 ◽

Vol 21 (04) ◽

pp. 1950005

Author(s):

Elvio Accinelli ◽

Filipe Martins ◽

Jorge Oviedo

Keyword(s):

Game Theory ◽

Strategic Planning ◽

Evolutionary Game Theory ◽

Replicator Dynamics ◽

Evolutionary Game ◽

Previous Literature ◽

Evolutionarily Stable Strategies ◽

Symmetric Games ◽

Two Populations ◽

Evolutionarily Stable

In this paper, we study the concept of Evolutionarily Stable Strategies (ESSs) for symmetric games with [Formula: see text] players. The main properties of these games and strategies are analyzed and several examples are provided. We relate the concept of ESS with previous literature and provide a proof of finiteness of ESS in the context of symmetric games with [Formula: see text] players. We show that unlike the case of [Formula: see text], when there are more than two populations an ESS does not have a uniform invasion barrier, or equivalently, it is not equivalent to the strategy performing better against all strategies in a neighborhood. We also construct the extended replicator dynamics for these games and we study an application to a model of strategic planning of investment.

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Seasonality in the production of male larvae: a game model for parasitic barnacles (Cirripedia: Rhizocephala)

Journal of Crustacean Biology ◽

10.1093/jcbiol/ruaa021 ◽

2020 ◽

Vol 40 (6) ◽

pp. 833-838 ◽

Cited By ~ 1

Author(s):

Sachi Yamaguchi ◽

Yoh Iwasa

Keyword(s):

Reproductive Success ◽

Seasonal Pattern ◽

Evolutionary Game ◽

Continuous Distribution ◽

Game Model ◽

Male Production ◽

Limited Ability ◽

Emergence Pattern ◽

Production Pattern ◽

Evolutionarily Stable

Abstract The male larvae of many parasitic barnacles are planktonic and are seasonally released. To achieve reproductive success, a male must be accepted by a receptive female that has successfully infected a host. To understand the seasonality of the breeding biology of parasitic barnacles, we developed an evolutionary game theoretical model for the seasonal pattern in the production of male larvae. Assumptions are that female parasitic barnacles become receptive following a given seasonal pattern. The parental females (mothers) choose the timing of producing their own male larvae to achieve maximum reproductive success. In the evolutionarily stable seasonal pattern, the production of male larvae often shows a sharp peak on a single day, indicating strongly synchronized production of male larvae, even when the supply of receptive females is distributed over the breeding season. When the total number of male larvae is large, the evolutionarily stable male production pattern may include multiple peaks, but it never shows a continuous distribution. This is very different from the game model previously developed for the emergence pattern of butterflies, where evolutionarily stable male emergence is always continuously distributed over a fraction of the mating season. As planktonic larvae, male parasitic barnacles have a naturally limited ability to find receptive females, and females may stay receptive for many days, whereas in butterflies, newly emerged females are mated within a day of their emergence.

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Packet Forwarding Strategies in Multiagent Systems: An Evolutionary Game Approach

Wireless Communications and Mobile Computing ◽

10.1155/2018/4965343 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14

Author(s):

Yuanjie Li ◽

Xiaojun Wu

Keyword(s):

Multiagent Systems ◽

Replicator Dynamics ◽

Evolutionary Game ◽

Game Model ◽

Packet Forwarding ◽

Evolutionarily Stable Strategies ◽

Incentive Mechanisms ◽

Average Probability ◽

Save Energy ◽

Stable Points

In multiagent systems (MASs), agents need to forward packets to each other to accomplish a target task. In this paper, we study packet forwarding among agents using evolutionary game theory under the mechanisms of Carrier Sense Multiple Access/Collision Avoidance (CSMA/CA). Packet forwarding among agents plays a key role to stabilize the whole MAS. We study the transfer probability of packet forwarding of agents at the idle state or the busy state and computer the probability of the packet forwarding for a MAS. When agents make their decisions to select Forward or No-Forward strategy, a packet forwarding evolutionary game model is built to reflect the utilities of different packet forwarding strategies. Two incentive mechanisms are introduced into the game model. One is to motivate agents to strengthen cooperation; the other is to encourage agents to select the No-Forward strategy to save energy while they are in the busy state. The parameter value that encourages an agent to select the No-Forward strategy is inversely proportional to the average probability of the packet forwarding. The replicator dynamics of agent packet forwarding strategy evolution are given. We propose and prove the theorems indicating that evolutionarily stable strategies (ESSs) can be attained. The results of simulation experiments verify the correctness of the proposed theorems and the effects of the two incentive mechanisms and the probability of packet forwarding, which assures the robustness of evolutionary stable points among agents in MASs.

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Resource Allocation as an Evolving Strategy

Evolutionary Computation ◽

10.1162/evco.1996.4.1.33 ◽

1996 ◽

Vol 4 (1) ◽

pp. 33-55 ◽

Cited By ~ 6

Author(s):

Sverrir Olafsson

Keyword(s):

Network Management ◽

Evolutionary Game Theory ◽

Evolutionary Game ◽

Evolutionary Games ◽

Network Services ◽

Efficient Utilization ◽

Evolutionarily Stable Strategies ◽

Network Utilization ◽

Function Network ◽

Evolutionarily Stable

The efficient utilization of resources is an issue of essential importance in modern network management. The emergence of increasingly complicated and continuously changing network services requires softer and fuzzier methods in network management. In this paper we demonstrate how evolutionary game theory can be used for an efficient allocation of service requirements onto an ensemble of heterogeneous network components. By incorporating differentiated pricing structures into a system utility function, network agents are encouraged to increase their usage of those components that are presently badly utilized. It is demonstrated how this approach can enhance network utilization significantly. Some new results regarding evolutionarily stable strategies in nonlinear evolutionary games are also reported.

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The distribution of evolutionarily stable strategies

Journal of Applied Probability ◽

10.2307/3214432 ◽

1988 ◽

Vol 25 (2) ◽

pp. 233-246 ◽

Cited By ~ 10

Author(s):

John Haigh

Keyword(s):

Evolutionary Game ◽

Random Variables ◽

Complete Picture ◽

Evolutionarily Stable Strategies ◽

Underlying Distribution ◽

Evolutionarily Stable ◽

Independent Identically Distributed

Suppose the n × n matrix A gives the payoffs for some evolutionary game, and its entries are the values of independent, identically distributed, continuous random variables. The distribution of the pattern of evolutionarily stable strategies for A will depend, if n ≧ 3, on this underlying distribution. A fairly complete picture for n = 3 is found, and some results are obtained for n ≧ 4.

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Evolutionary Game Theoretic Analysis of Low Carbon Investment in Supply Chains under Governmental Subsidies

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph15112465 ◽

2018 ◽

Vol 15 (11) ◽

pp. 2465 ◽

Cited By ~ 7

Author(s):

Guang Zhu ◽

Gaozhi Pan ◽

Weiwei Zhang

Keyword(s):

Supply Chains ◽

Incentive Mechanism ◽

Rapid Development ◽

Evolutionary Game ◽

Investment Strategy ◽

Free Riding ◽

Low Carbon ◽

Evolutionarily Stable Strategies ◽

Evolutionarily Stable ◽

Profit Growth

With the rapid development of global industry and economy, excessive carbon dioxide emission has emerged as a critical issue in both developed and developing countries. Using an evolutionary game framework in which game players can adjust their strategies constantly, this paper investigates how to optimize the strategy of low carbon investment for suppliers and manufacturers in supply chains, and discuss the impacts of various factors on evolutionarily stable strategies. Additionally, we examine an incentive mechanism based on governmental subsidies to eliminate free riding and motivate co-investment. Furthermore, a case study and numerical examples are provided for illustration and simulation purposes, leading to several countermeasures and suggestions. Our analytical results show that the strategic choice of low carbon investment is correlated with profit growth coefficients, investment costs and profits from free riding. Investment costs have more significant impacts than other factors on evolutionarily stable strategies, while profit growth coefficients are more important at initial stages in the evolutionary process. The incentive mechanism based on governmental subsidies is an effective solution to motivate co-investment, and governments should take some measures to improve the assess accuracy and supervisory efficiency of investment strategy.

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