Incorporating Risk Attitude and Reputation into Infinitely Repeated Games and an Analysis on the Iterated Prisoner's Dilemma

Abstract

Many real life situations can be modeled as Prisoner's Dilemma. There are various strategies in the literature. However, few of which match the design objectives of an intelligent agent -being reactive and pro-active. In this paper, we incorporate risk attitude and reputation into infinitely repeated games. In this way, we find that the original game matrix can be transformed to a new matrix, which has a kind of cooperative equilibrium. We use the proposed concepts to analyze the Iterated Prisoner's Dilemma. Simulation also shows that agents, which consider risk attitude and reputation in the decision-making process, have improved performance and are reactive as well as pro-active.

A Three-party Repeated Game Model for Data Privacy in Mobile Edge Crowdsensing of IoT

“…At present, many real-world application scenarios can be simulated as prisoners' dilemma, and the relevant research literature also provides a variety of strategies; however, it rarely conforms to the design objectives of the intelligent agent: reactivity and initiative. In [11], the risk attitude and reputation factors are combined into infinite repeated games, and the original game theory matrix is transformed into a new matrix with cooperative equilibrium. By analyzing the repeated prisoner's dilemma and the results of simulation experiments, it is verified that the performance of agents considering the above two factors in the decision-making process,in both active and passive manner is improved.…”

“…[9] provides an example of a scheme combining game theory and cryptography to solve the problem of privacy protection in MCS paradigm. The repeated prisoner's dilemma game under multiple factors is considered in [11]. [38] combined the AI algorithm on the basis of game theory and cryptography, provided an effective solution to the problem of privacy leakage risk in MECS paradigm, without considering the impact of repeated interaction between entities over a period of time.…”

Risk and Prisoner's Dilemma: A Reinterpretation of Coombs' Re‐parameterization

“…Their empirical results supported the major prediction that cooperation was a risk‐averse option; however, results regarding the difference between the gain domain and the loss domain were mixed. In another formulation of risk attitudes in an iterated PD game, Lam and Leung (, ) suggested that risk is associated with reputations. They reasoned that risk‐averse people are more concerned about the reputation of themselves and their opponent, that is, how cooperative they appear to their opponent and how cooperative the opponent appears to them.…”

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