14 research outputs found
The Stability of Two-Community Replicator Dynamics with Discrete Multi-Delays
This article investigates the stability of evolutionarily stable strategy in replicator dynamics of two-community with multi-delays. In the real environment, players interact simultaneously while the return of their choices may not be observed immediately, which implies one or more time-delays exists. In addition to using the method of classic characteristic equations, we also apply linear matrix inequality (i.e., LMI) to discuss the stability of the mixed evolutionarily stable strategy in replicator dynamics of two-community with multi-delays. We derive a delay-dependent stability and a delay-independent stability sufficient conditions of the evolutionarily stable strategy in the two-community replicator dynamics with two delays, and manage to extend the sufficient condition to n time delays. Lastly, numerical trials of the Hawk–Dove game are given to verify the effectiveness of the theoretical consequences
Evolutionary dynamics of cooperation in <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline" id="d1e646" altimg="si253.svg"><mml:mi>N</mml:mi></mml:math>-person snowdrift games with peer punishment and individual disguise
Evolutionary Games and Dynamics in Public Goods Supply with Repetitive Actions
Based on a tripartite game model among suppliers of public goods, consumers, and the government, a tripartite repeated game model is constructed to analyze the evolution mechanism of which suppliers supply at low prices, consumers purchase, and the government provides incentives, and to establish the dynamics system of a repeated game. The equilibrium points of the evolutionary game are solved, and among them, the equilibrium points are found to satisfy the parameter conditions of ESS. The numerical simulation is employed to verify the impact of penalty coefficients and discount factors on the stability of strategies, which are adopted by the three players in a tripartite repeated game on public goods, and scenario analyses are conducted. The research results of this paper could provide a reference for the government, suppliers, and consumers to make rapid decisions, who are in the supply chain of public goods, especially quasi-public goods, such as coal, water, electricity, and gas, and help them to obtain stable incomes and then ensure the stable operation of the market.</jats:p
Research on Repeated Quantum Games with Public Goods under Strong Reciprocity
We developed a repeated quantum game of public goods by using quantum entanglement and strong reciprocity mechanisms. Utilizing the framework of quantum game analysis, a comparative investigation incorporating both entangled and non-entangled states reveals that the player will choose a fully cooperative strategy when the expected cooperation strategy of the competitor exceeds a certain threshold. When the entanglement of states is not considered, the prisoner’s dilemma still exists, and the cooperating party must bear the cost of defactoring the quantum strategy themselves; when considering the entanglement of states, the benefits of both parties in the game are closely related, forming a community of benefits. By signing a strong reciprocity contract, the degree of cooperation between the game parties can be considered using the strong reciprocity entanglement contract mechanism. The party striving to cooperate does not have to bear the risk of the other party’s defector, and to some extent, it can solve the prisoner’s dilemma problem. Finally, taking the public goods green planting industry project as an example, by jointly entrusting a third party to determine and sign a strong reciprocity entanglement contract, both parties can ensure a complete quantum strategy to maximize cooperation and achieve Pareto optimality, ultimately enabling the long-term and stable development of the public goods industry project
Evolutionary Games and Dynamics in Public Goods Supply with Repetitive Actions
Based on a tripartite game model among suppliers of public goods, consumers, and the government, a tripartite repeated game model is constructed to analyze the evolution mechanism of which suppliers supply at low prices, consumers purchase, and the government provides incentives, and to establish the dynamics system of a repeated game. The equilibrium points of the evolutionary game are solved, and among them, the equilibrium points are found to satisfy the parameter conditions of ESS. The numerical simulation is employed to verify the impact of penalty coefficients and discount factors on the stability of strategies, which are adopted by the three players in a tripartite repeated game on public goods, and scenario analyses are conducted. The research results of this paper could provide a reference for the government, suppliers, and consumers to make rapid decisions, who are in the supply chain of public goods, especially quasi-public goods, such as coal, water, electricity, and gas, and help them to obtain stable incomes and then ensure the stable operation of the market
Network virus propagation and security situation awareness based on Hidden Markov Model
The security situation of the network is determined by the observation state and hidden state of a complex virus system. To analyze the relationship between the two states and evaluate the trends in the security situation of the system, we construct a new model for security situation awareness based on Hidden Markov Model (HMM). Firstly, the paper examines the impact of virus propagation on network security and proposes a new SIR (Susceptible–Infected–Recovered) virus propagation model on scale-free networks. Secondly, we construct a Hidden Markov Model for network security, and this model designs and utilizes the Forward Algorithm and Viterbi Algorithm to assess the security status of epidemic networks. Finally, we ascertain the effectiveness of the model and algorithms through model examples and simulation experiments. The results show that the proposed algorithm is highly efficient in analyzing the security of virus systems and has great application value in predicting the security trends of networks
