Search Results (41)

Classical epidemic models treat vaccine uptake as an exogenous parameter, yet real-world coverage emerges from strategic choices made by individuals facing uncertain risks. During the last two decades, vaccination games, which combine epidemic dynamics with game theory, behavioural economics, and network science, have become a very important tool for analysing this problem. Here, we synthesise more than 80 theoretical, computational, and empirical studies to clarify how population structure, psychological perception, pathogen complexity, and policy incentives interact to determine vaccination equilibria and epidemic outcomes. Papers are organised along five methodological axes: (i) population topology (well-mixed, static and evolving networks, multilayer systems); (ii) decision heuristics (risk assessment, imitation, prospect theory, memory); (iii) additional processes (information diffusion, non-pharmacological interventions, treatment, quarantine); (iv) policy levers (subsidies, penalties, mandates, communication); and (v) pathogen complexity (multi-strain, zoonotic reservoirs). Common findings across these studies are that voluntary vaccination is almost always sub-optimal; feedback between incidence and behaviour can generate oscillatory outbreaks; local network correlations amplify free-riding but enable cost-effective targeted mandates; psychological distortions such as probability weighting and omission bias materially shift equilibria; and mixed interventions (e.g., quarantine + vaccination) create dual dilemmas that may offset one another. Moreover, empirical work surveys, laboratory games, and field data confirm peer influence and prosocial motives, yet comprehensive model validation remains rare. Bridging the gap between stylised theory and operational policy will require data-driven calibration, scalable multilayer solvers, and explicit modelling of economic and psychological heterogeneity. This review offers a structured roadmap for future research on adaptive vaccination strategies in an increasingly connected and information-rich world. Full article

This study investigated the social and behavioural impacts of employing a card game designed to support the teaching of business metrics through active peer-to-peer engagement, contrasting with traditional passive lectures. Grounded in Bandura’s Social Learning Theory (SLT), the study used a multiple-methods approach including student feedback, a focus group, and an interview. A novel card game, Metrics Masters©, was played by 390 students across a range of educational levels and settings. The research found that the game effectively introduced and reinforced their understanding of key business metrics, while simultaneously enhancing social interaction, teamwork, and problem-solving among Millennial and Generation Z students. The findings underline the efficacy of game-based learning and its close alignment with the SLT principles of observation, imitation, and social interaction. The theoretical contribution of this paper lies in its explicit application and extension of SLT within the context of business education, illustrating empirically how social interactions facilitated by game-based activities significantly enhance learning outcomes. Furthermore, this paper contributes to educational practice by providing robust evidence that game-based learning methods can effectively address educational challenges heightened by the COVID-19 pandemic, offering actionable strategies for educators aiming to foster both academic and social development among students. Full article

This study employs an evolutionary game theory framework to analyze the interactive learning, imitation, and strategic evolution among multiple actors within China’s aquatic product traceability system. It focuses on four types of strategic interactions: between fishers and the government, fishers and consumers, fishers who adopt the traceability system and those who do not, and between consumers who purchase traceable aquatic products and those who do not. The evolutionarily stable strategies and equilibrium outcomes in each game depend on the net benefits obtained and the various costs borne by each party. Among these factors, transaction costs within the traceability system play a particularly critical role in shaping stakeholder behavior. The lower the transaction costs, the more likely stakeholders are to adopt strategies that support or enhance the functioning of the system. Therefore, reducing the operational and transaction costs of the traceability system should be a key policy focus for the government. This includes efforts in policy and regulatory development, platform and infrastructure construction, and the improvement of information exchange mechanisms to foster sustainable development in aquaculture. Full article

In recent years, rapid progress in autonomous driving has been achieved through advances in sensing, control, and earning. However, as the complexity of traffic scenarios increases, ensuring safe interaction among vehicles remains a formidable challenge. Recent works combining artificial potential fields (APFs) with game-theoretic methods have shown promise in modeling vehicle interactions and avoiding collisions. However, these approaches often suffer from overly conservative decisions or fail to capture the nonlinear dynamics of real-world driving. To address these imitations, we propose a novel framework that integrates mean field game (MFG) theory with model predictive control (MPC) and quadratic programming (QP). Our approach everages the aggregate behavior of surrounding vehicles to predict interactive effects and embeds these predictions into an MPC-QP scheme for real-time control. Simulation results in complex driving scenarios demonstrate that our method achieves multiple autonomous driving tasks while ensuring collision-free operation. Furthermore, the proposed framework outperforms popular game-based benchmarks in terms of achieving driving tasks and producing fewer collisions. Full article

The patent openness decisions of frontier enterprises and the consequent investment tendencies of laggard enterprises play a significant role in their profitability. Despite the benefits resulting from directly using open patents, in order to capture market share and surpass frontier enterprises, laggard enterprises must decide whether they are going to invest in R&D or expansion. In this context, based on evolutionary game theory and the operational behaviors of both frontier and laggard enterprises, this study constructed a model of enterprise revenue under asymmetric competition, exploring the impact of patent openness with and without government subsidies on enterprise revenue. This study discovered that: (1) when the industry scale is small, frontier enterprises gain significant social effects through patent openness, while laggard enterprises invest in expansion; (2) as the industry scale gradually expands, frontier enterprises tend to prefer not to open their patents, and laggard enterprises gradually shift from imitation to independent innovation when the return on R&D investment increases more than that on expansion investment; and (3) when the R&D costs of laggard enterprises are high, frontier enterprises usually choose not to open their patents, forcing laggard enterprises to turn to investment in expansion. This allows frontier enterprises to reduce the losses from patent openness while enjoying the benefits of reduced industry production costs. This study provides new perspectives on patent openness and investment tendencies with the help of an evolutionary game mechanism and offers managerial policy recommendations. Full article

Manufacturers and consumers are boundedly rational and ultimately seek evolutionarily stable strategies through trial and error, imitation, and learning. It is important to study the pricing strategies of manufacturers and the purchasing channel decisions of consumers in the context of increasingly fierce competition in online channels, in addition to consumers’ loss aversion due to increasingly confusing promotional strategies; accordingly, in this paper, an evolutionary game including both parties is constructed, and the loss aversion factor from prospect theory is introduced. Based on data from Chinese media reports on the cosmetics industry, simulation and sensitivity analyses were conducted using Matlab R2024a. The results indicate that—in addition to channel services affecting the evolutionarily stable strategy for purchasing channel selection—a decrease in consumer loss aversion will help consumers reach the evolutionarily stable strategy faster. For manufacturers, channel services do not affect their evolution to a unified pricing strategy; however, when consumer loss aversion increases, manufacturers’ evolutionarily stable strategy will shift from a unified pricing strategy to a differentiated pricing strategy. Full article

We start from the fundamental premise that any physical interaction can be interpreted as a game. To demonstrate this, we draw upon the free energy principle and the theory of quantum reference frames. In this way, we place the game-theoretic Nash Equilibrium in a new light in so far as the incompleteness and undecidability of the concept, as well as the nature of strategies in general, can be seen as the consequences of certain no-go theorems. We show that games of the generic imitation type follow a circularity of idealization that includes the good regulator theorem, generalized synchrony, and undecidability of the Turing test. We discuss Bayesian games in the light of Bell non-locality and establish the basics of quantum games, which we relate to local operations and classical communication protocols. In this light, we also review the rationality of gaming strategies from the players’ point of view. Full article

We investigate the role and performance of imitative behavior in a class of quantity-setting, Cournot games. Within a framework of evolutionary competition between rational, myopic best-response and imitation heuristics with differential heuristics’ costs, we found that the equilibrium stability depends on the sign of the cost differential between the unstable heuristic (Cournot best-response) and the stable one (imitation) and on the intensity of the evolutionary pressure. When this cost differential is positive (i.e., imitation is relatively cheaper vis a vis Cournot), most firms use this heuristic and the Cournot equilibrium is stabilized for market sizes for which it was unstable under Cournot homogeneous learning. However, as the number of firms increases $(n=7)$, instability eventually sets in. When the cost differential is negative (imitation is more expensive than Cournot), complicated quantity fluctuations, along with the co-existence of heuristics, arise already for the triopoly game. Full article

Lying and truth-telling are conflicting behavioral strategies that pervade much of the lives of social animals and, as such, have always been topics of interest to both biology and philosophy. This age-old conflict is linked to one of the most serious threats facing society today, viz., the collapse of trustworthy sources of information. Here, we revisit this problem in the context of the two-choice sender–receiver game: the sender tosses a coin and reports the supposed outcome to the receiver, who must guess the true outcome of the toss. For the sender, the options are to lie or tell the truth, while for the receiver, the options are to believe or disbelieve the sender’s account. We assume that social learning determines the strategy used by players and, in particular, that players tend to imitate successful individuals and thus change their strategies. Using the replicator equation formulation for infinite populations and stochastic simulations for finite populations, we find that when the sender benefits from the receiver’s failure, the outcome of the game dynamics depends strongly on the choice of initial strategies. This sensitivity to the initial conditions may reflect the unpredictability of social systems whose members have antagonistic interests. Full article

The richest assemblage of the Triassic Diptera has been described from the famous Konservat-Lagerstätte Grès à Voltzia (Upper Buntsandstein) in the northern Vosges Mountains in France, dated as Early Anisian. A re-examination of the holotypes and additional material from the type locality allows for the establishment of Vogerhyphus gen. nov. and erection of the Vogerhyphinae subfam. nov. for Vymrhyphus blagoderovi Krzemiński and Krzemińska, 2003 and Vogerhyphus krzeminskorum sp. nov. (Protorhyphidae), and a new monotypic family Galliidae fam. nov. for Gallia alsatica Krzemiński and Krzemińska, 2003, originally described as Rhagionidae based on its wing venation. Galliidae fam. nov. is characterized by its closed cua cell and long moniliform antenna with 14-segmented flagellum and is hypothesized to belong to the stem-group Brachycera, along with the Late Triassic Prosechamyiidae. The process of brachycerization in the Diptera evolution is briefly discussed. Full article

In unmanned systems, remote sensing is an approach that collects and analyzes data such as visual images, infrared thermal images, and LiDAR sensor data from a distance using a system that operates without human intervention. Recent advancements in deep learning enable the direct mapping of input images in remote sensing to desired outputs, making it possible to learn through imitation learning and for unmanned systems to learn by collecting and analyzing those images. In the case of autonomous cars, raw high-dimensional data are collected using sensors, which are mapped to the values of steering and throttle through a deep learning network to train imitation learning. Therefore, by imitation learning, the unmanned systems observe expert demonstrations and learn expert policies, even in complex environments. However, in imitation learning, collecting and analyzing a large number of images from the game environment incurs time and costs. Training with a limited dataset leads to a lack of understanding of the environment. There are some augmentation approaches that have the limitation of increasing the dataset because of considering only the locations of objects visited and estimated. Therefore, it is required to consider the diverse kinds of the location of objects not visited to solve the limitation. This paper proposes an enhanced model to augment the number of training images comprising a Preprocessor, an enhanced Swin Transformer model, and an Action model. Using the original network structure of the Swin Transformer model for image augmentation in imitation learning is challenging. Therefore, the internal structure of the Swin Transformer model is enhanced, and the Preprocessor and Action model are combined to augment training images. The proposed method was verified through an experimental process by learning from expert demonstrations and augmented images, which reduced the total loss from 1.24068 to 0.41616. Compared to expert demonstrations, the accuracy was approximately 86.4%, and the proposed method achieved 920 points and 1200 points more than the comparison model to verify generalization. Full article

UNESCO’s Sustainable Development Goal 4 and new curricula around the world call for a better quality of education. Among the main challenges of improving quality is increasing the integration between disciplines and improving the preparation of students for the personal and work requirements of a smarter and rapidly changing society. For that purpose, we need to design new and effective didactic strategies. However, current classrooms are isolated. They practically never connect. This hinders the exchange of ideas. It inhibits imitation and recombination, the basic blocks of cultural evolution and innovation. In this paper, we analyze four online interclass tournaments that we have implemented in the last decade. This long-term view is crucial for estimating the sustainability of new teaching strategies. These tournaments are very uncommon lessons, where entire elementary or middle school classes interconnect synchronously and play an educational game. This increased interconnectedness is only possible thanks to digital communication technology. We found that these interclass tournaments are feasible to implement in schools; that they are a promising mechanism for teaching with an increased integration of disciplines; and that they facilitate imitation, recombination, and innovation of teaching strategies. Thus, interclass tournaments could be a feasible strategy to help innovate and improve the quality of education. Full article

Research on the application of artificial intelligence (AI) in games has recently gained momentum. Most commercial games still use AI based on a finite state machine (FSM) due to complexity and cost considerations. However, FSM-based AI decreases user satisfaction given that it performs the same patterns of consecutive actions in the same situations. This necessitates a new AI approach that applies domain-specific expertise to existing reinforcement learning algorithms. We propose a behavioral-cloning-based advantage actor-critic (A2C) that improves learning performance by applying a behavioral cloning algorithm to an A2C algorithm in basketball games. The state normalization, reward function, and episode classification approaches are used with the behavioral-cloning-based A2C. The results of the comparative experiments with the traditional A2C algorithms validated the proposed method. Our proposed method using existing approaches solved the difficulty of learning in basketball games. Full article

In biological evolution, organisms that are more adapted to the environment tend to survive better, which can be explained in part by evolutionary game theory. In this paper, we propose an improved spatial prisoner’s dilemma game model, which allows the focal player to access the strategy of other agents beyond their nearest neighbors with a specified probability. During the strategy update, a focal player usually picks up a randomly chosen neighbor according to a Fermi-like rule. However, in our model, unlike the traditional strategy imitation, a focal agent will decide to update their strategy through the modified rule with a specific probability q. In this case, the focal agent accesses n other individuals who have the same strategy as the imitated neighbor, where the information accessing cost needs to be paid, and then compares their discounted payoff with the average payoff of those $n+1$ agents to make the decision of strategy adoption; otherwise, they only refer to their own payoff and their neighbor’s payoff to decide whether the strategy spread happens. Numerical simulations indicate that a moderate value of n can foster the evolution of cooperation very well, and increase in q will also improve the dilemma of cooperators. In addition, there exists an optimal product of $n\times c$ to cause the emergence of cooperation under the specific simulation setup. Taken together, the current results are conducive to understanding the evolution of cooperation within a structured population. Full article

Inefficiencies in the construction and demolition waste (CDW) recycling supply chain constrain green innovation in the construction industry. However, existing studies have not analyzed the innovation behavior of recyclers in CDW recycling public-private partnership (PPP) projects from the perspective of innovation diffusion theory. To reveal the mechanism of recyclers’ innovation behavior in CDW recycling PPP projects in which recyclers and remanufacturers jointly participate in the operation stage, this study uses a Stackelberg game to analyze the optimal innovation strategy choice and total profit of the CDW recycling supply chain among the two innovation paths of green independent innovation and green imitation innovation under the combined effects of technology spillover, consumer green sensitivity, and government price subsidies to consumers. The main conclusions are as follows. (1) Remanufacturers and recyclers can improve their own innovation level and profit through technology spillover. (2) The total profit of the CDW recycling supply chain changes dynamically with the level of spillover. (3) The government price subsidy to consumers does not always improve the total profit of the CDW recycling supply chain. (4) The effect of consumers’ green sensitivity on the total profit of the CDW recycling supply chain shows heterogeneity with the innovation path of recyclers and the level of technological spillover. This study not only enriches the theoretical study of the green supply chain but also provides a basis for decision-making for recyclers and governments in practice. Full article