Game Approach Research Articles

Overgamified? An Exploratory Study on Gamification and Crowdsourcing for Fake Accounts Detection in Social Networks

In this exploratory research, a gamification approach for crowdsourcing fake account detection in social networks has been proposed and evaluated for the first time. Gamification usually tries to satisfy the users’ psychological needs. However, motivation could also be based on human physiological needs. Among these needs are health, shelter, and clothes. In the gamification world, we can translate them into monetary or cash rewards. We have investigated the effects of both these rewards on users’ motivations in participating and detecting fake accounts by conducting two in-the-wild exploratory experiments and two surveys. The experimental results showed that users prefer physiological rewards over psychological rewards, and an increase in the reward (0.75 euro in this study) resulted in a 365% increase in user participation and a 28.88% decrease in number of accurate reports in the first experiment. Similarly, in the second experiment, we observed that higher monetary rewards resulted in higher user acquisition and higher user engagement, but the quality of the reports was 10% lower than the low monetary rewards. This indicates that physiological rewards can potentially make users over-motivated or, in other words, overgamified. To tackle this problem, we proposed a gamification approach that benefits from both psychological and physiological rewards and gradually increases them. The evaluation results showed a 15% increase in the quality of the reports, a 26% increase in interaction time using the proposed method, and a 19% increase in user acquisition to lower monetary rewards. It also showed a 57% increase in commitment to participating in the survey compared with other groups. Both survey results show that around 40% of the users prefer to receive between 0.50 and 1 euro for their services. Also, women showed more quality responses and commitment in completing the participation than men.

Improving Older Adults’ Technology Adoption on Mobile Map: A Gamification Approach

In the era of digitalization, it is critical to improve older adults’ digital literacy and inclusion by enhancing their technology adoption to create a more accessible and inclusive social environment. However, older adults always exhibit lower levels of technology usage, and there is insufficient support available to meet their specific needs. Gamification, with its potential to motivate people, presents a great opportunity to address the issue of technology adoption among older adults. Despite gamification being predominantly applied to younger generations, this study offers a unique contribution by examining the impact of gamification on supporting older adults’ technology adoption. A case study of tailor-made gamification for Google Maps was constructed based on the game-based learning model and game mechanics. The effectiveness of the proposed gamification strategy has been assessed through interviews and observation. The results revealed a significant positive effect of gamification on enhancing older adults’ technology knowledge and adoption intentions.

Grandfathering or benchmarking? The impact of carbon quota allocation rule on the joint emission reduction supply chain

The choice of carbon quota allocation rule (CQA rule) is crucial for the efficient operation of cap-and-trade policy. This paper analyses the impact of grandfathering (GF) rule and benchmarking (BM) rule on the joint emission reduction (JER) supply chain by using a differential game approach. In the proposed model, the upstream manufacturer achieves its emission reduction target through green technology and recycling, and the downstream retailer promotes these products. Our results show that compared with the benchmark case, both CQA rules do not always encourage the manufacturer to increase emission reduction investments. Moreover, the environmental and economic performance of different CQA rules is time-varying. For low-emission products, both CQA rules may yield higher total carbon emissions. For medium and high-emission products, the BM rule has a better short-term environmental performance, while the GF rule always has the best long-term environmental performance. As such, the government should prioritise the inclusion of medium and high-emission manufacturers in the carbon trading market and adopt the BM rule at the initial stage, and then transition to the GF rule. We also provide practical insights on the timing of transition, setting free carbon quotas, balancing economic and environmental performance, and dealing with uncertain market changes.

Efforts To Improve Shooting Accuracy Through The Target Situations Game Approach In Petanque Sports

Efforts To Improve Shooting Accuracy Through The Target Situations Game Approach In Petanque Sports

European Perspectives on Public Benefit in Relation to Food: Insights from a Serious Game Approach

There is limited understanding of what constitutes public benefit from the perspective of the public, and none that we are aware of related to food consumer science. The purpose of this study is to contribute towards a better understanding of public benefit as a whole and its connection to food choice, essential to driving progress towards responsible consumption and healthier diets. Public benefit, associated trade-offs and responsible actors were investigated via written questions, and food choice was explored during group discussions using the PlayDecide methodology. Adults (n = 105) were recruited in six European countries (Denmark, Germany, Italy, Slovakia, Spain and the UK) and stratified by attained education. Our findings indicate that assumptions should not be made that there is general consensus about what constitutes public benefit, especially with regard to consumer food choice. Group discussions around food-related freedom of choice, education, agency and responsibility suggested that private and public benefit are neither mutually exclusive nor automatically complementary. The serious game approach employed affected a change in participants’ public benefit perceptions, demonstrating its potential to better evaluate the connections between private interests and the common good through meaningful public deliberation.

Distributed filtering with time-varying topology: A temporal-difference learning approach in dual games

This study aims to develop a dual games (DGs) mechanism and implement a temporal difference learning (TDL) approach to address distributed filter design while considering network-induced time-varying topology from individual optimality and global equilibrium perspectives. In a detailed analysis, each filtering node (FN) treats its individual filtering action and exogenous disturbance as opposing elements, striving to determine the optimal policy while accounting for the worst-case scenario. This competition between FN and the disturbance culminates in a zero-sum game. Simultaneously, FN collaborates effectively with its neighbors to achieve consensus estimation, giving rise to a non-zero-sum game. Notably, an error-based filtering action is built to solve challenges posed by DGs. Ultimately, each FN attains its estimation at a minimum cost, and the entire distributed filtering network achieves the consensus estimation at a Nash equilibrium. Moreover, the transition probability correlation matrices (TPCMs) of the time-varying topology are obtained through direct observation of multi-episodes of topological transition trajectories. It has been proved that with a sufficiently ample number of episodes, TPCMs converge to their optimal values when TPs are known as apriori. Finally, a numerical example and an aero-engine system are presented to illustrate the effectiveness and practical potential of the proposed method.

Barrier-critic-disturbance approximate optimal control of nonzero-sum differential games for modular robot manipulators

In this paper, for addressing the safe control problem of modular robot manipulators (MRMs) system with uncertain disturbances, an approximate optimal control scheme of nonzero-sum (NZS) differential games is proposed based on the control barrier function (CBF). The dynamic model of the manipulator system integrates joint subsystems through the utilization of joint torque feedback (JTF) technique, incorporating interconnected dynamic coupling (IDC) effects. By integrating the cost functions relevant to each player with the CBF, the evolution of system states is ensured to remain within the safe region. Subsequently, the optimal tracking control problem for the MRM system is reformulated as an NZS game involving multiple joint subsystems. Based on the adaptive dynamic programming (ADP) algorithm, a cost function approximator for solving Hamilton–Jacobi (HJ) equation using only critic neural networks (NN) is established, which promotes the feasible derivation of the approximate optimal control strategy. The Lyapunov theory is utilized to demonstrate that the tracking error is uniformly ultimately bounded (UUB). Utilizing the CBF’s state constraint mechanism prevents the robot from deviating from the safe region, and the application of the NZS game approach ensures that the subsystems of the MRM reach a Nash equilibrium. The proposed control method effectively addresses the problem of safe and approximate optimal control of MRM system under uncertain disturbances. Finally, the effectiveness and superiority of the proposed method are verified through simulations and experiments.

Optimizing Traveler Behavior Between MADINA and JEDDA Using UPPAAL Stratego: A Stochastic Priced Timed Games Approach

This study looks at how travelers move between MADINA and JEDDA, using the UPPAAL Stratego tool to tackle the complexities of urban mobility. As cities grow, effective transportation planning becomes more challenging. Travelers have three options: car, bus, and train. The choices for car and bus travel are impacted by traffic conditions, which can vary between heavy and light, affecting both travel time and cost. We propose a detailed mathematical model that captures all possible scenarios related to these travel options, incorporating the uncertainties of real life. This allows us to simulate different traffic situations. By using UPPAAL Stratego, we evaluate three strategies: the Safe Strategy, which minimizes risk; the Fast Strategy, which aims to reduce travel time; and the Fast and Safe Strategy, which seeks a balance between speed and safety. This paper starts with an introduction to the Stochastic Priced Timed Games approach, highlighting its relevance in modeling dynamic travel environments. We then provide an overview of UPPAAL Stratego, showcasing its abilities in generating, optimizing, and comparing strategies. Next, we outline our mathematical model, explaining the assumptions, parameters, and data sources we used. Our simulation results illustrate how each strategy performs under different conditions, shedding light on traveler preferences and behaviors. The findings underscore the significance of accounting for traffic variability in travel planning and offer important insights for urban transportation policies aimed at improving the traveler experience and optimizing resource use. Additionally, we emphasize the theoretical contributions of our model by demonstrating its applicability to real-world scenarios and its potential to inform future research in urban mobility optimization. Ultimately, this research adds to the growing knowledge of smart transportation systems, demonstrating how formal mathematical modeling can address complex real-world challenges and inform future urban mobility strategies.

Assessment of gamified mixed reality environments for upper limb robotic rehabilitation: pilot study on healthy adults

Exoskeletons for rehabilitation have the potential to aid movement and promote intensive, task-oriented, and personalized motor training. However, robotic-assisted training and user experience could be further improve by including Mixed Reality Environments (MREs) and using a gamification approach. This paper presents the design and evaluation of a MR solution based on Microsoft Hololens 2 for robot-assisted bilateral shoulder training. It is based on gamified MREs designed to guide and encourage bilateral synchronous and asynchronous movements of the upper extremities while a 6 Degrees of Freedom (DOF) exoskeleton (FLOAT) provides motor assistance only to the impared limb. The robotic-assisted bimanual tasks involve the use of rehabilitative tools (such as a dowel rod), as a means to interact with the virtual world and to enable the intact limb guide and control the motions of the disable limb. The gamified MR training solution generates meaningful performance metrics from the kinematic analysis of hands movement, captured by Hololens. The subjective evaluation of the gamified MR solution focused on usability, cognitive load, and user experience. Meanwhile, the objective evaluation encompassed the analysis of the robot-assisted movements with and without gamified MREs, a comparative analysis between metrics obtained from Hololens and Vicon data, and the collection of reference data and trajectories. There were twenty-one healthy adults involved in the evaluation of the system. The results with the gamified MREs highlight excellent system usability, low cognitive load, and high user experience. Additionally, integrating gamified MREs into robot-assisted movements enhances shoulder movements. Data collection with Hololens demonstrated to be reliable and consistent. Furthermore, the normal reference values, paths, and velocity profiles obtained from healthy individuals offer a foundation for assessing the performance of individuals with disabilities. In summary, the introduction of gamified MREs for robot-assisted bilateral shoulder movements marks a significant and promising advancement in rehabilitation technology.

Dynamic Operational Planning in Warfare: A Stochastic Game Approach to Military Campaigns

ABSTRACTWe study a two‐player discounted zero‐sum stochastic game model for dynamic operational planning in military campaigns. At each stage, the players manage multiple commanders who order military actions on objectives that have an open line of control. When a battle over the control of an objective occurs, its stochastic outcome depends on the actions and the enabling support provided by the control of other objectives. Each player aims to maximize the cumulative number of objectives they control, weighted by their criticality. To solve this large‐scale stochastic game, we derive properties of its Markov perfect equilibria by leveraging the logistics and military operational command and control structure. We show the consequential isotonicity of the optimal value function with respect to the partially ordered state space, which in turn leads to a significant reduction of the state and action spaces. We also accelerate Shapley's value iteration algorithm by eliminating dominated actions and investigating pure equilibria of the matrix game solved at each iteration. We demonstrate the computational value of our equilibrium results on a case study that reflects representative operational‐level military campaigns with geopolitical implications. Our analysis reveals a complex interplay between the game's parameters and dynamics in equilibrium, resulting in new military insights for campaign analysts.

Quiet Pandemic Amid COVID-19: A literature review on gamification for mental health

Background: COVID-19 affects individuals both physically and mentally. The key is to address emerging needs with a modest technique that helps boost the positive approach in individuals. Gamification offers attempts to engage users with the non-game approach, and its growing popularity in other fields, such as finance and retail, is evident. Objective: This research aims to study the available literature that analyzes and understands using the Gamification approach for mental health in the pandemic. Methods: The author performed a systematic literature review using the PRISMA technique among the selected articles published until Jul 2023, focusing on Gamification, mental health, and COVID in highly reputed record databases, which were peer-reviewed studies. Therefore, the studies using the standard international language of English were eligible for this Study. Results: The Study identified elevated articles exploring Gamification through mobile application software, web-based platforms, and other tools since COVID-19 limited in-person social contact for individual safety during peak time. Conclusion: There are limited studies of Gamification in mental health, and the existing studies suggest that Gamification supports the betterment of mental health. Future studies can explore the different areas of mental health with gamification-based applications or gamified approaches.

Optimization of Organic Rankine Cycle for Hot Dry Rock Power System: A Stackelberg Game Approach

Due to its simple structure and stable operation, the Organic Rankine Cycle (ORC) has gained significant attention as a primary solution for low-grade thermal power generation. However, the economic challenges associated with development difficulties in hot dry rock (HDR) geothermal power systems have necessitated a better balance between performance and cost effectiveness within ORC systems. This paper establishes a game pattern of the Organic Rankine Cycle with performance as the master layer and economy as the slave layer, based on the Stackelberg game theory. The optimal working fluid for the ORC is identified as R600. At the R600 mass flow rate of 50 kg/s, the net system cycle work is 4186 kW, the generation efficiency is 14.52%, and the levelized cost of energy is 0.0176 USD/kWh. The research establishes an optimization method for the Organic Rankine Cycle based on the Stackelberg game framework, where the network of the system is the primary optimization objective, and the heat transfer areas of the evaporator and condenser serve as the secondary optimization objective. An iterative solving method is utilized to achieve equilibrium between the performance and economy of the ORC system. The proposed method is validated through a case study utilizing hot dry rock data from Qinghai Gonghe, allowing for a thorough analysis of the working fluid and system parameters. The findings indicate that the proposed approach effectively balances ORC performance with economic considerations, thereby enhancing the overall revenue of the HDR power system.

Offshore grid planning considering restricted areas: An evolution game approach

In this paper, offshore wind farm cluster transmission network planning is examined in depth, based on the finite rational evolutionary game method. In the actual project, the game scenarios of offshore wind farm developers and transmission system operators and their respective interests are considered, while cable laying exclusion zones owing to the submarine environment are fully taken into account. Through simulation experiments, the significant effect of the proposed method in improving grid adaptability and interference immunity is verified. The results demonstrate that the proposed finite rational evolutionary game method increases the return on investment by 1.83 % compared to the traditional method, while the payoff ratio of the game participants is 12.81 % lower. In addition, the method excels in ensuring the feasibility of project implementation by successfully balancing the interests between the OWF developer and the power transmission system operator. This offers a new perspective for efficient planning of transmission networks for offshore wind farms that can better cope with complex engineering environments and balance the interests of all parties.

Brand livestream mode options: AI vs KOL livestream in the platform supply chain

PurposeDriven by the rapid expansion of online retail and the surge in livestream commerce, the impact of different livestream mode on brand and platform performance has become a critical issue. This paper analyzes the impact of artificial intelligence (AI) and key opinion leader (KOL) livestream on the profitability of brands and the platform, incorporating the effects of horizontal interactions to identify the optimal livestream mode.Design/methodology/approachThis paper develops a model of a platform supply chain involving two brands and a platform, where each brand independently decides whether to utilize KOL or AI livestream. Applying Stackelberg game approach, the study derives equilibria for various livestream scenarios, identifying the optimal livestream mode for both parties. Additionally, the model is extended to incorporate asymmetric market potential and network externality to evaluate their impact on a brand’s choice of livestream mode.FindingsSeveral interesting and important results are derived in this paper. Firstly, it is found that AI livestream enables brands to leverage network externality and mitigate the market disadvantage, thereby gaining a competitive advantage. Secondly, while KOL livestream promotes trust, the medium KOL commission rates could cause brands to be trapped in a prisoner’s dilemma, and excessively high commission rates may render them less profitable. Thirdly, the KOL commission rate, network externality intensity, horizontal interactions and market disadvantage are critical determinants influencing a brand’s choice of livestream mode.Originality/valueThis study is the first to investigate the effects of horizontal interactions, asymmetric market potential and asymmetric network externality on livestream mode selection by brands within a platform supply chain. The research provides valuable insights into optimizing livestream strategies to enhance brand profitability.

Optimizing integrated energy systems at park level: A cooperative game approach with exergy economics

This study presents a comprehensive framework for optimizing energy systems by integrating exergy analysis, energy economics, and game theory. The concept of exergy, which quantifies the usable energy within a system, is employed to evaluate energy efficiency and losses across various energy sources, including thermal, cooling, chemical, and electrical systems. Stoichiometric coefficients, denoted by the factor λ, are utilized to simplify exergy calculations for different energy types and processes. The economic evaluation of energy flows is conducted through energy economics principles, incorporating cost allocation and balance equations. The integration of game theory into the optimization model ensures strategic interactions among energy components, leading to a Nash equilibrium that balances economic performance, efficiency, and environmental sustainability. The model also accounts for emissions and the required proportion of renewable energy. To solve the complex optimization problem, a modified Particle Swarm Optimization (PSO) algorithm is employed, featuring adaptive mechanisms for velocity and inertia updates, enhancing the search process for the optimal solution. The proposed framework is designed to optimize the Integrated Energy System (IES) efficiently, ensuring sustainable and economically viable energy management. The analysis of optimization strategies highlights a trade-off between cost and efficiency. Strategy 1, focused on minimizing cost, achieves the lowest cost at 4069.37 CNY, 25.79 % less than Strategy 2, but with a reduced exergy efficiency of 59.82 %, which is 10.14 % lower than Strategy 2′s 68.47 %. Strategy 3 offers a balanced approach, with a cost of 4970.89 CNY, 9.43 % higher than Strategy 1 but 9.43 % lower than Strategy 2. It achieves an exergy efficiency of 67.87 %, only 0.60 % lower than Strategy 2, thus providing a practical compromise between economic performance and efficiency.

The Open Data Newsroom: A Game Approach for Developing Open Data Competencies in Elementary School

Open Data refers to digital data that is made available to anyone with the legal and technical conditions to be freely used, reused, and redistributed. Although it has emerged as a new common with the potential to increase citizen participation and transparency, current literature suggests the lack of skills for managing data and participating in Open Data processes, as one of the main barriers to achieve these benefits. Integrating Open Data in school education has been recognized as key to fostering a larger community able to participate in Open Data ecosystems. This study showcases the design of a role-playing game grounded in authentic learning principles for the development of Open Data competencies in elementary school. The Open Data Newsroom is a game approach that immerses students in solving a mystery with data. In the game, students play Open Data Journalists engaging in a three-phase authentic process to get, understand and deliver data. The learning goal in the game is that students build open data competencies: data literacy and real-world problem solving. A design-based research methodological approach is applied to develop theory based and practically grounded educational designs. Two interventions in Danish schools have been conducted, each one with the participation of seventeen students in 7th to 9th grade and three teachers. Interventions are aimed at iteratively designing and testing the game. The discussion section elaborates on opportunities for redesigning and systematically developing the game as a learning design for Open Data competencies.

When Games get in the way: Gamification Approach for Teaching Maths – A Case Study With Undergraduate Tourism Students

Planning more dynamic and motivating lessons for students is the goal of any teacher, especially maths teachers, a subject where the lack of interest and motivation to learn is so evident and a major concern. Several studies highlight the positive impact of the adoption of gamification strategies in teaching/learning, both in student motivation and in the development of soft skills (teamwork, creativity, decision-making, leadership, communication, and critical thinking). Game-based learning thus promotes students' interest and involves them in this process. In this sense, one of the authors of this study chose to use several (non-digital) games to support the teaching-learning process in her classes. The games used were developed by the authors and have been thoroughly designed to address specific maths topics. The games took various forms, including card games, board games and other hands-on activities. The participants in the study are first-year undergraduate students from a Portuguese higher education institution and encompassed the course of “Quantitative Methods”. The aim of the study is to investigate students’ perceptions of the use of gamification in the maths teaching-learning process. To gather information about students’ insights on the use of games in math classes a quantitative survey was conducted. Similar studies have shown that higher education students are usually receptive to the use of games, finding it useful to increase their motivation and consider game-based learning can positively impact learning. Our findings are in line with those studies.

Incentive Mechanism for Redactable Blockchain Governance: An Evolutionary Game Approach

Incentive Mechanism for Redactable Blockchain Governance: An Evolutionary Game Approach

Control Allocation of Spacecraft Revisited: A Stackelberg Differential Game Approach

Control Allocation of Spacecraft Revisited: A Stackelberg Differential Game Approach

DEVELOPMENT OF AN INTERACTIVE WEBSITE WITH DIDACTIC GAMES TO ENHANCE VOCABULARY IN YOUNG STUDENTS WITH INTELLECTUAL DISABILITIES

The article investigates the development of a website that includes interactive didactic games designed to improve the vocabulary of primary schoolchildren with intellectual disabilities. It describes the importance of developing vocabulary in children with intellectual disabilities and shows how the game approach can be an effective tool for teaching and developing speech in this category of children. The process of developing a website with didactic games is considered, which includes the selection of appropriate software, interface design, development of interactive tasks and games, as well as testing and improvement of the website. In particular, the article discusses methods and approaches to creating games aimed at developing lexical skills, expanding vocabulary and improving communication skills in children with intellectual disabilities. The advantages of using interactive didactic games in the educational process of junior schoolchildren with intellectual disabilities are highlighted. They stimulate children's interest in learning words and expanding their vocabulary, develop cognitive and speech skills, improve memory and concentration, and increase motivation and enjoyment of learning. A game-based approach can keep children interested, motivated, and effective, helping them to develop their language skills and achieve greater academic success. The website was created on the wix platform. The collection of didactic games was developed on the LearningApps platform. There are various types of tasks, for example quizzes, puzzles, crosswords, matching exercises, etc. Images for didactic games were generated by playground.ai artificial intelligence, which opens up new opportunities for creating visually appealing games and tasks. The importance of developing website with interactive didactic games for the development of vocabulary of younger students with intellectual disabilities is emphasized, they can become an effective tool for teaching and developing speech in children of this category, contributing to their success in learning and overall development.