scholarly journals Modelling on Infectious Disease with Voluntary Vaccination Behavior on Social Networks by Evolutionary Game Theory and Multi-Agent Simulation

2014 ◽  
Vol 28 (3) ◽  
pp. 280-287
Author(s):  
Jun TANIMOTO
Keyword(s):  
Infectious Disease ◽  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Vaccination Behavior ◽  
Agent Simulation ◽  
Multi Agent ◽  
Voluntary Vaccination

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks

2014 ◽  
Vol 68 ◽  
pp. 1-9 ◽  
Author(s):  
Eriko Fukuda ◽  
Satoshi Kokubo ◽  
Jun Tanimoto ◽  
Zhen Wang ◽  
Aya Hagishima ◽  
...  
Keyword(s):  
Infectious Disease ◽  
Risk Assessment ◽  
Social Networks ◽  
Vaccination Behavior ◽  
Voluntary Vaccination

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

scholarly journals Dynamic Model of Collaboration in Multi-Agent System Based on Evolutionary Game Theory

Games ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 75
Author(s):  
Zhuozhuo Gou ◽  
Yansong Deng
Keyword(s):  
Game Theory ◽  
Evolutionary Game Theory ◽  
Evolutionary Game ◽  
Multi Agent Systems ◽  
Exchange Of Information ◽  
Message Communication ◽  
Stable Conditions ◽  
Agent Collaboration ◽  
Multi Agent ◽  
Reducing Costs

Multi-agent collaboration is greatly important in order to reduce the frequency of errors in message communication and enhance the consistency of exchanging information. This study explores the process of evolutionary decision and stable strategies among multi-agent systems, including followers, leaders, and loners, involved in collaboration based on evolutionary game theory (EGT). The main elements that affected the strategies are discussed, and a 3D evolution model is established. The evolutionary stability strategy (ESS) and stable conditions were analyzed subsequently. Numerical simulation results were obtained through MATLAB simulation, and they manifested that leaders play an important role in exchanging information with other agents, accepting agents’ state information, and sending messages to agents. Then, with the positivity of receiving and feeding back messages for followers, implementing message communication is profitable for the system, and the high positivity can accelerate the exchange of information. At the behavior level, reducing costs can strengthen the punishment of impeding the exchange of information and improve the positivity of collaboration to facilitate the evolutionary convergence toward the ideal state. Finally, the EGT results revealed that the possibility of collaboration between loners and others is improved, and the rewards are increased, thereby promoting the implementation of message communication that encourages leaders to send all messages, improve the feedback positivity of followers, and reduce the hindering degree of loners.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 317-331
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of pl ion propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

PATENTING OR SECRET? THE INTERACTION BETWEEN LEADING FIRMS AND FOLLOWING FIRMS BASED ON EVOLUTIONARY GAME THEORY AND MULTI-AGENT SIMULATION

2019 ◽  
Vol 23 (07) ◽  
pp. 1950068 ◽  
Author(s):  
XIAOYANG ZHAO
Keyword(s):  
Game Theory ◽  
Bounded Rationality ◽  
Evolutionary Game Theory ◽  
Patent Protection ◽  
Evolutionary Game ◽  
Equilibrium Solutions ◽  
Strategic Choices ◽  
Trade Off ◽  
Multi Agent ◽  
Imitation Strategy

Firms who want to appropriate innovation often need to make decision facing the trade-off between patenting and secret. This paper explores how leading firms make trade-off between patenting and secret through the view of the interaction between leading firms and following firms who have the option of imitation or substitution, based on the evolutionary game theory. Then, a simulation model is built combining the evolutionary game model and agent-based modelling method, which allows us to implement bounded rationality and interactivities. The simulation is run with different gain parameters and the results are checked by cross-validation. It is found that leading firms are more likely to adopt patenting strategy with well developed patent protection regime. While depending on variations on patent protection effectiveness, technological characteristics, and leading firms’ investment in patent portfolio development, following firms may choose imitation strategy or substitution strategy. Considering bounded rationality, firms could choose sub-optional strategies and leads to scenarios other than evolutionary equilibrium solutions, which provide deeper insights of strategic choices of leading firms and following firms. This paper makes contributions to theory by using the perspective of multi-agent view and integrating bounded rationality in the simulation. Finally, this paper draws conclusion and puts forward some suggestions.

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