Search Results (110)

The concept of Nash equilibria in pure strategies for quantum extensions of the general form of the Prisoner’s Dilemma game is investigated. The process of quantization involves incorporating two additional unitary strategies, which effectively expand the classical game. We consider five classes of such quantum games, which remain invariant under isomorphic transformations of the classical game. The resulting Nash equilibria are found to be more closely aligned with Pareto-optimal solutions than those of the conventional Nash equilibrium outcome of the classical game. Our results demonstrate the complexity and diversity of strategic behavior in the quantum setting, providing new insights into the dynamics of classical decision-making dilemmas. In particular, we provide a detailed characterization of strategy profiles and their corresponding Nash equilibria, thereby extending the understanding of quantum strategies’ impact on traditional game-theoretical problems. Full article

In this work, we study n-agent Bayesian games with m-dimensional vector types and linear payoffs, also called linear multidimensional Bayesian games. This class of games is equivalent with n-agent, m-game uniform multigames. We distinguish between games that have a discrete type space and those with a continuous type space. More specifically, we are interested in the existence of pure Bayesian Nash equilibriums for such games and efficient algorithms to find them. For continuous priors, we suggest a methodology to perform Nash equilibrium searches in simple cases. For discrete priors, we present algorithms that can handle two-action and two-player games efficiently. We introduce the core concept of threshold strategy and, under some mild conditions, we show that these games have at least one pure Bayesian Nash equilibrium. We illustrate our results with several examples like the double-game prisoner’s dilemma (DGPD), the game of chicken, and the sustainable adoption decision problem (SADP). Full article

Background: Decision-making under risk is a crucial process for undertaking health behaviors. Although the influence of individual differences on decision-making under risk has been widely examined, there is no clear consensus yet as to how to explain this process considering both young and older adults. The main aim of this preliminary study was to examine age differences in decision-making under risk, risk propensity, sensation-seeking, and self-conscious emotions between younger and older adults. Methods: A total of 40 subjects (20 young adults and 20 older adults) participated in the present study. The young adults were aged 18–35 years (M = 23.25, SD = 2.59). The older adults were aged 65–70 years (M = 68.50, SD = 4.01). Participants completed the Risk Propensity Scale, the Sensation-Seeking Scale, the Test of Self-Conscious Affect, and the Prisoner’s Dilemma Game. Results: The results indicated that the groups showed different behaviors in sensation-seeking (p < 0.001, pη2 = 0.14). The older group showed a larger propensity to seek recreational activities and unconventional behaviors than the younger group (p < 0.0001, d = 0.78; p = 0.001, d = 0.75). Also, the older adults demonstrated a greater inclination toward pride (p < 0.01, d = 0.78), whereas younger adults exhibited a stronger tendency towards shame (p < 0.01, d = 0.76). Conclusions: These data suggest a shift in risk preferences as individuals age, potentially influenced by a variety of psychological, social, and experiential factors. The applications of this study can support psychological well-being, productivity, and quality of life in later adulthood. Full article

This study introduces a simple model, which can be used to examine the influence of reputation on expected income achieved within the Iterated Prisoner’s Dilemma (IPD) game framework. The research explores how different reputation distributions among society members impact overall outcomes by modeling a society of agents, each characterized by a reputation score that dictates their likelihood of cooperation. Due to the simplicity of the model, we can analytically determine the expected incomes based on the distribution of agents’ reputations and model parameters. The results show that a higher reputation generally leads to greater expected income, thereby promoting cooperation over defection. However, in some cases, where there are more defecting individuals, the expected income reaches the maximum for agents with an average reputation, and then decreases for individuals who cooperate more. Various scenarios, including uniform, increasing, and decreasing reputation distributions, are analyzed to understand their effects on the promoted interaction strategy. Finally, we outline future extensions of the model and potential research directions, including the exploration of alternative reputation distributions, variable interaction parameters, and different payoff structures in the dilemma games. Full article

Human cooperation is ubiquitous and instinctive. We are among the most cooperative species on Earth. Still, research mostly focuses on why we cooperate, instead of understanding why some of us do not do so. The public goods game can be used to map human cooperation as well as to study free riding. We acquired data through an online, unincentivized questionnaire which prompted respondents to choose how much of an initial endowment to contribute to a common pool. The respondents contributed, on average, 54% of their initial endowment to the common pool. The usual categorization scheme of the elicited conditional contribution pattern discerns unconditional free riders who do not contribute irrespective of the contributions of others and calls everyone a conditional cooperator who correlates their contribution with that of the others. However, someone consistently offering less than the others should not be called a cooperator. Consequently, based on the conditional contribution patterns among our respondents, we suggest a recategorization of contribution patterns into the following categories: unconditional cooperator (1.5%), unconditional free rider (10.6%), perfect conditional cooperator (42.6%), hump-shaped contributor (0.7%), V-shaped contributor (0.4%), conditional cooperator (16.6%), conditional free rider (13.6%), conditional contributor (6.4%), negative conditional contributor (0%), and others (7.6%). We only call someone a cooperator if the respondent at least matches others’ contribution, and call everyone consistently offering less a free rider. Furthermore, we found no difference between the contributions of women and men. No correlation of contribution with age, educational attainment, and size of the residential settlement was found. Students’ contributions were not different from non-students’ contributions. We found a significant correlation of the contribution to the common pool with hypercompetitive orientation (negative correlation) and the self-assessed willingness to take risks in general (positive correlation). Full article

Individuals can learn about others from sources far from them, and conformity can operate not only on a local scale but also on a global scale. This study aimed to investigate the influence of conformity and global learning on social systems of cooperation using agent-based models of the spatial prisoner’s dilemma game. Three agent-based models incorporating differing types of global conformity were built and analyzed. The results suggested that global learning was generally unfavorable for cooperation. However, in some cases, it enabled resistance to the dominance of defection. Moreover, referring to more diverse sources was less harmful to cooperation than referring to a larger number of similar sources. Evolutionary dynamics were generated according to how competing forces of cooperative and defective agents were balanced. Random drifts toward either the cooperation- or defection-dominant state occurred under some parameter conditions. Whether the drifts were equally or unequally probable toward either state differed according to the parameter conditions. This study highlights the importance of individuals’ psychological biases in the evolution of cooperation. It also shows that differing practices of those biases can generate different dynamics, resulting in the system having different states. Full article

In the context of green economy, Closed-Loop Supply Chain (CLSC) competition is intensifying. This study aims to help companies operating in green supply chains determine optimal remanufacturing strategies when competing with other firms. We examine the decision-making problem of CLSCs in competitive environments facing multiple remanufacturing mode options. The research constructs a Prisoner’s dilemma model for dual CLSCs, where each chain has three strategic choices: independent remanufacturing, outsourced remanufacturing, and authorized remanufacturing. Employing Stackelberg game models, Nash equilibrium analysis, and numerical simulations, this study explores how remanufactured product unit saving costs affect remanufacturing mode decisions concerning competitive intensity and discount policies. The study then draws the following conclusions: (1) CLSCs prefer outsourced and authorized remanufacturing in competitive scenarios; (2) Remanufactured product discounting significantly influences CLSC remanufacturing decisions; (3) Competitors typically adopt conservative strategies by aligning decisions with rivals. These results provide practical guidance for CLSCs selecting remanufacturing approaches when facing substitute competition, contributing to more sustainable and competitive supply chain operations. Full article

Forecast risk management is central to the financial management process. This study aims to apply Monte Carlo simulation to solve three classic probabilistic paradoxes and discuss their implementation in corporate financial management. The article presents Monte Carlo simulation as an advanced tool for risk management in financial management processes. This method allows for a comprehensive risk analysis of financial forecasts, making it possible to assess potential errors in cash flow forecasts and predict the value of corporate treasury growth under various future scenarios. In the investment decision-making process, Monte Carlo simulation supports the evaluation of the effectiveness of financial projects by calculating the expected net value and identifying the risks associated with investments, allowing more informed decisions to be made in project implementation. The method is used in reducing cash flow volatility, which contributes to lowering the cost of capital and increasing the value of a company. Simulation also enables more accurate liquidity planning, including forecasting cash availability and determining appropriate financial reserves based on probability distributions. Monte Carlo also supports the management of credit and interest rate risk, enabling the simulation of the impact of various economic scenarios on a company’s financial obligations. In the context of strategic planning, the method is an extension of decision tree analysis, where subsequent decisions are made based on the results of earlier ones. Creating probabilistic models based on Monte Carlo simulations makes it possible to take into account random variables and their impact on key financial management indicators, such as free cash flow (FCF). Compared to traditional methods, Monte Carlo simulation offers a more detailed and precise approach to risk analysis and decision-making, providing companies with vital information for financial management under uncertainty. This article emphasizes that the use of Monte Carlo simulation in financial management not only enhances the effectiveness of risk management, but also supports the long-term growth of corporate value. The entire process of financial management is able to move into the future based on predicting future free cash flows discounted at the cost of capital. We used both numerical and analytical methods to solve veridical paradoxes. Veridical paradoxes are a type of paradox in which the result of the analysis is counterintuitive, but turns out to be true after careful examination. This means that although the initial reasoning may lead to a wrong conclusion, a correct mathematical or logical analysis confirms the correctness of the results. An example is Monty Hall’s problem, where the intuitive answer suggests an equal probability of success, while probabilistic analysis shows that changing the decision increases the chances of winning. We used Monte Carlo simulation as the numerical method. The following analytical methods were used: conditional probability, Bayes’ rule and Bayes’ rule with multiple conditions. We solved truth-type paradoxes and discovered why the Monty Hall problem was so widely discussed in the 1990s. We differentiated Monty Hall problems using different numbers of doors and prizes. Full article

This paper studies biased-manager hiring in a market with network externalities and product compatibility. We show that the aggressivity of a biased manager has a non-linear relationship with product compatibility; however, since both owners want to hire aggressive managers, product compatibility is irrelevant to the type of manager the owner hires. In Cournot competition, product compatibility is crucial in alleviating the “prisoner’s dilemma” due to the net network effect of network externalities with product compatibility. In Bertrand competition, the “prisoner’s dilemma” is resolved when the augmented net network effect of product compatibility is large. Full article

In this paper, we focus on developing self-organizing algorithms aimed at solving, in a distributed way, the coverage problem in Wireless Sensor Networks (WSNs). For this purpose, we apply a game-theoretical framework based on an application of a variant of the Spatial Prisoner’s Dilemma game. The framework is used to build a multi-agent system, where agent-players in the process of iterated games tend to achieve a Nash equilibrium, providing them the possible maximal values of payoffs. A reached equilibrium corresponds to a global solution for the coverage problem represented by the following two objectives: coverage and the corresponding number of sensors that need to be turned on. A multi-agent system using the game-theoretic framework assumes the creation of a graph model of WSNs and the further interpretation of nodes of the WSN graph as agents participating in iterated games. We use the following two types of reinforcement learning machines as agents: Learning Automata (LA) and Cellular Automata (CA). The main novelty of the paper is the development of a specialized reinforcement learning machine based on the application of ($ϵ,h$)-learning automata. As the second model of an agent, we use the adaptive CA that we recently proposed. While both agent models operate in discrete time, they differ in the way they store and use available information. LA-based agents store in their memories the current information obtained in the last h-time steps and only use this information to make a decision in the next time step. CA-based agents only retain information from the last time step. To make a decision in the next time step, they participate in local evolutionary competitions that determine their subsequent actions. We show that agent-players reaching the Nash equilibria corresponds to the system achieving a global optimization criterion related to the coverage problem, in a fully distributed way, without the agents’ knowledge of the global optimization criterion and without any central coordinator. We perform an extensive experimental study of both models and show that the proposed learning automata-based model significantly outperforms the cellular automata-based model. Full article

To explore the coupling relationship between information propagation behaviors and evolution dynamics in swarm systems, this paper establishes the SEBAR model based on mean field theory with a macroscopic view of information dissemination. Then, the balance points and basic reproduction number are calculated and a proof of equilibrium stability from the point of view of system stability is given. In addition, the influence of model parameters on propagation behaviors is also analyzed. To stimulate the emergence of cooperative behaviors in a swarm system, a repeated “prisoner’s dilemma” game based on controllable individuals is proposed under the framework of bionic “soft control”. The combination of information propagation and game strategies is used to realize information regulation. The simulation results show that the proposed models and methods can reflect the information communication patterns and evolution characteristics. It also illustrates the viability and effectiveness of regulating information through the evolutionary game. Full article

Living organisms expend energy to sustain survival, a process which is reliant on consuming resources—termed here as the “cost of survival”. In the Prisoner’s Dilemma (PD), a classic model of social interaction, individual payoffs depend on choices to either provide benefits to others at a personal cost (cooperate) or exploit others to maximize personal gain (defect). We demonstrate that in an iterated Prisoner’s Dilemma (IPD), a simple “Always Cooperate” (ALLC) strategy evolves and remains evolutionarily stable when the cost of survival is sufficiently high, meaning exploited cooperators have a low probability of survival. We derive a rule for the evolutionary stability of cooperation, x/z >T/R, where x represents the duration of mutual cooperation, z the duration of exploitation, T the defector’s free-riding payoff, and R the payoff for mutual cooperation. This finding suggests that higher survival costs can enhance social welfare by selecting for cooperative strategies. Full article

In recent years, with rapid economic development, the importance of environmental governance has gradually been overlooked. The increasing pollution caused by rural sewage discharge has posed a significant threat to the local ecological environment. In this context, this paper treats the local governments, village enterprises, and farmers as the game subjects, integrating them with prisoner’s dilemma theory to construct a tripartite game model. By analyzing the equilibrium points and stability of the model, as well as the effects of the parameters in the dynamic equations, this paper reveals the evolution of strategic choices made by different participants. The results indicate that the optimal strategy for local governments is strict regulation, and village enterprises tend to adopt purification measures, while farmers weigh the costs and benefits and exhibit a negative attitude toward participating in governance. Finally, from a practical perspective, this paper offers suggestions for improving rural ecological environmental protection by engaging local governments, village enterprises, and farmers, aiming to promote the sustainable development of the ecological environment. Full article

Dissocial personality is understood as a personality that does not ideologize most social norms and is characterized by a lack of empathy. Precise criteria for diagnosing dissocial personality are included in the ICD-10 classification, which is still in force in Poland. This classification is widely available in both Polish and English. In Poland, there is a fairly wide range of assistance available for people with personality disorders in day care units and 24-h wards for the treatment of personality disorders. Unfortunately, due to some antisocial behaviors that violate the criminal law in force in Poland, people with dissocial personality are placed in prisons. The development of dissocial personality depends on both genetic factors and the demoralizing influence of the social environment. The mutual interactions of genetic and environmental factors in the pathogenesis of dissocial personality can be analyzed both using statistical methods for large groups and by analyzing a case study, which is a qualitative study and is underestimated in modern medicine. Due to the complex pathogenesis of dissocial personality, various ethical dilemmas arise, and the extent of the guilt for the committed, prohibited act depends on genetic factors and brain structure and to some extent on environmental factors. The apparent ability of people with dissocial personality to look into their own actions leaves doctors always with the question of how sick or bad the person is. In this study, we used the method of qualitative analysis of case studies of two patients treated in a 24-h personality disorder treatment unit of the Department of Neuroses, Personality Disorders and Eating Disorders of the Second Psychiatric Clinic of the Institute of Psychiatry and Neurology in Warsaw. Full article

When a landslide occurs, the person who discovers it will likely report the disaster; however, a person who receives this report will likely need someone on site to check, since the reporter may have misread the information. This allows third parties to make use of the confirmed information. Facilitating such mechanisms for reporting, confirming, and utilizing disaster information is considered to be necessary for sharing details about one. In this paper, we proposed and analyzed an agent-based model that incorporates disaster behavior into the model of Toriumi et al. The reporting of a disaster refers to submitting articles, the confirmation of the information by another person refers to commenting on the articles, and utilizing the information refers to comments responding to the aforementioned comment using the framework of meta-reward games, based on the prisoner’s dilemma game. We then analyze the costs and rewards to encourage cooperation in several social networks. It is found that reducing the cost of commenting (conforming) encourages the submission of information. The properties of the results do not depend on network structure, which is novel and unexpected, and it is expected that the properties of real social networks will be predictable. Full article