Trust Game Model Research Articles

Evolution of trust in N-player trust games with loss assessment.

Trust plays a crucial role in social and economic interactions, serving as the foundation for social stability and human cooperation. Previous studies have explored the evolution of trust between investors and trustees by constructing trust game models, incorporating factors such as network structure, reputation, and incentives. However, these studies often assume that investors consistently maintain their investment behavior, neglecting the potential influence of the investment environment on investment behavior. To address this gap, we introduce a loss assessment mechanism and construct a trust game model. Specifically, investors first allocate their investment amount to an assessment agency, which divides the amount into two parts according to a certain allocation ratio. One part is used for investment assessment, and the results are fed back to the investors. If the payoff from this portion exceeds the investors' expected value, the remaining amount is invested; otherwise, it is returned to the investors. The results indicate that investors with moderate expectations are more likely to form alliances with trustworthy trustees, thereby effectively promoting the evolution of trust. Conversely, lower or higher expectations yield opposite results. Additionally, we find that as investors' expected values increase, the corresponding allocation ratio should also increase to achieve higher payoffs.

Evolution of trust in the N-player trust game with the margin system

Investigations into trust behavior between investors and trustees using trust games have gained significant attention in recent years. However, understanding the process of trust evolution remains challenging. The margin system, widely employed in the financial industry as an economic and behavioral incentive mechanism, aims to maintain order in financial markets and protect participants' rights and interests. Despite its extensive use, the precise influence of the margin system on trust evolution dynamics remains unclear. To address this gap, we propose an N-player trust game model that incorporates a margin system within an infinite well-mixed population. In our model, a third-party institution collects a proportionate amount of margin from trustees, which is returned upon fulfilling their obligations but forfeited otherwise. By utilizing replicated dynamic equations, we find that implementing the margin system can establish a stable coexistence state between investors and trustworthy trustees, representing a significant advancement in trust evolution. Additionally, an intriguing finding arises from our observation of an inverted U-shaped relationship between the magnitude of the attraction domain for coexistence and the coefficient of the margin. This suggests that excessively high margin proportions can discourage trustees' participation, while excessively low proportions may fail to effectively deter dishonest behavior. Optimal margin proportions can effectively promote trust evolution.

Evolution of trust in a hierarchical population with different investors based on investment behavioral theory

The study of trust behavior between investors and trustees through trust games has been a hot topic recently. In previous research, the standard N−player trust game model has been used to reveal some aspects of trust evolution, but does not consider the risk perception of investors. According to behavioral investment theory, investors have different sensitivities to investment risk due to their individual environments and characteristics. Here, we construct an N-player trust game model where we divide investors into two categories, namely, venture investors and conservative investors. Conservative investors are willing to pay an information cost upfront to avoid investment risk, while venture investors are not. By analyzing replicator equations, we find that the system has an asymptotically stable internal equilibrium point when the group size is large, while when the group size is small, the system becomes a Hamiltonian system with a stable periodic solution. Our result shows that a lower information cost leads to a higher proportion of trustworthy trustees and thus reduces the portion of untrustworthy trustees.

Evolutionary dynamics in networked trust games with diverse investment patterns

Most previous works study the evolution of trust by commonly assuming that investors adopt a deterministic investment strategy. In this work, we propose a mechanism of diverse investment in the trust game model on social networks, where each investor adopts a probabilistic strategy by considering the trustworthiness level in the local group to decide whether to invest or not. Extensive simulation results suggest that the proposed mechanism inhibits the untrustworthy behavior and limits its spread, thus stabilizing the cooperative cluster of investors and trustworthy trustees. Therefore, the trust level and global wealth are greatly enhanced comparing to the traditional setup with homogeneous investment pattern. The strong investment diversity can even eliminate untrustworthiness completely despite the fact that the severe temptation condition is disadvantageous to the evolution of trust. We also investigate the impact of investment diversity on trust game model embedding in different network structures with different initial conditions, where we observe similarly positive evolutionary outcomes. We hope these observations can provide valuable insights into further exploring the improvement of trust in real life.

The Effect of Dishonest Sellers on E-commerce: An Agent-Based Modeling Approach

Abstract This paper studies dishonest sellers in the e-commerce market, specifically their impact on the market under different conditions. We consider the role of consumers’ social and individual learning and social network branches on the market. We rely on a quality uncertainty market model (Izquierdo et al., 2007) and a trust game model (Wierzbicki et al., 2014) to establish an agent-based model. Our approach considers the proportion of honest and dishonest sellers, the reputation of sellers, and the expectation of quality among consumers after purchasing the goods. The results of the study reveal that when dishonest sellers appear in a market with a high degree of quality uncertainty, there is a negative impact on the market, including a decline in consumer expected quality of products in the market, a decrease in commodity transaction volume and market price, and a decrease in seller income. The impact is more pronounced in markets with a higher proportion of dishonest sellers. JEL classification numbers: C15, C63, D21, B82, B83. Keywords: Agent-Based modeling, E-commerce market, Dishonest sellers, Trust game, Reputation of sellers.

A Trust Game Model of Service Cooperation in Cloud Computing

With the development of cloud services, many network fraudulent incidents have damaged the interests of transaction subjects and brought a great crisis to online service. To analyze and solve the key conditions for different participants to achieve mutual trust and win-win situations in the cloud computing, we propose a trust prediction game model composed of the supervisor, cloud service provider (CSP), and user. Firstly, we use the Bayesian formula to predict the behavior trust attribute and propose the trust service map function and weight algorithm by the principle of maximum dispersion. Secondly, based on the perspective of the user, we establish a two-party dynamic game model and discuss the existence possibility of game equilibrium. Thirdly, based on the perspective of CSP, we establish a tripartite game model, analyze several possible equilibria, and obtain the equilibrium strategy from a mixed perspective. Finally, the experimental results show that the supervision has a significant impact on the strategy selection of the players, verify the correctness and effectiveness of various game parameters, exhibition the better advantage than several articles under some different standards, and make a useful exploration for building a secure and trusted cloud service environment.

Dynamic trust game model between venture capitalists and entrepreneurs based on reinforcement learning theory

It has been extensively demonstrated that the trust between venture capitalists and entrepreneurs plays an important role in improving the success rate of entrepreneurship. However, little research has been performed concerning the dynamic nature of the trust between venture capitalists and entrepreneurs. Therefore, we attempt to reveal the motivations and process of trust between VCs and entrepreneurs from the perspective of dynamics. First, the theoretical model of dynamic trust was proposed. Second, reinforcement learning was introduced to design the multi-stage game model of dynamic trust, and the algorithm was illustrated. Reinforcement learning theory can reveal the reasons for dynamic changes in trust from a psychological perspective. Finally, the action strategies of venture capitalists and entrepreneurs were simulated. We observe that the dynamic characteristics of trust between venture capitalists and entrepreneurs are determined by entrepreneurs’ efforts. Venture capitalists can prevent investment risks and maintain trust stability when fewer funds are invested in the early stage and when more funds are invested in the later stage. Since the dynamic process of trust is also the process of learning about the other, the dynamic process of trust is non-linear, and the relationship is adaptive.

A Trust Game Model and Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

The existence of malicious secondary users will bring damage to the performance of cooperative spectrum sensing and spectrum access in cognitive radio networks, so effectively curbing malicious behavior of secondary users become the key to success for cooperative spectrum sensing mechanism. Inspired by economics of repeated game theory, a trust game model and algorithm of distributed cooperative spectrum sensing oriented to malicious secondary users named FRTrust is proposed. In FRTrust, the reputation status is used to describe the performance of a secondary user in cooperative spectrum sensing process. It encourages secondary users to choose positive and honest behavior strategies for greater and long term benefits. Simultaneously, a ‘differentiation’ punishment mechanism is presented to respond malicious behaviors of secondary users. By this way, the ‘first offender’ secondary users and the ‘recidivist' secondary users can be distinguished effectively. If a secondary user departs from the normal times in its life period, it will be punished superimposed. Simulation results show that the FRTrust algorithm can encourage secondary users to participate in spectrum sensing in a cooperative attitude, improve the transaction success ratio of cooperative spectrum sensing, and guarantee the fairness and spectrum access performance for cognitive radio networks.

A Trust Game Model and Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

A Trust Game Model and Algorithm for Cooperative Spectrum Sensing in Cognitive Radio Networks

Analysis on Electricity-Coal Quality Problems Based on Trust Game Model

The quality of the electricity-coal affected the economic benefit of the thermal power plant and brought hidden risks to the safe operation of unit. Firstly, we analyze the impacts of thermal power plants test accuracy on electricity-coal suppliers decision-making. Secondly, we present the trust game model and studied the long-term cooperative relationship in electricity-coal suppliers decision-making. Finally, we make a calculation example about the game between the electricity-coal suppliers and the thermal power plant, and it shows that if both sides cooperate to establish a reasonable benefit-sharing mechanism, information asymmetry will be made up, and the quality of the electricity-coal can be ensured fundamentally.

A Study on Trust Construction in University Research Team

University research team, as a special form of organizations in university, is a characteristic feature of contemporaneity science.it has a rapid development in recent years. But the trust is playing a very important role in research team’s development. The paper analyzes the trust construction of research team by establish one-shot and repeated trust game models, and based on this, establishes the trust game model with university intervention. The conclusion shows that the trust mechanism will not be constructed by one-shot game. While it can be constructed by repeated game, but its trust mechanism is not stable. With the university intervation, the team members will change their behavior and increase the trust probability, and it will be easily construct trust in university research team. According to the above analysis, the paper presents some countermeasures and suggestions to promote trust construction in university research team.