Multiple Games Research Articles

Individual Differences in Cognitive Abilities and Personality Traits Predict Car-Soccer Video Game Performance

Associations with player performance in traditional field-based sports and video games have been observed with specific cognitive abilities and personality traits. The present study investigated whether such connections can be used to predict performance in hybrid genre video games that include game mechanics from multiple traditional games. The focus of the present was on the hybrid genre car-soccer game, Rocket League. The gameplay shares some aspects of traditional soccer and video games along with unique mechanics. Psychological traits that have been observed to correlate with performance in these traditional games were hypothesized to be associated with better Rocket League performance. In the present study, participants greater in mental rotation ability and number processing tended to have higher performance. Evidence from detailed match metrics indicated that they more effectively navigated and maneuvered around the car-soccer arena. Connections with personality traits suggested that player openness and neuroticism affected offensive–defensive metrics, likely via team dynamics. Variations in associations with match metrics indicated that different car-soccer gameplay actions relied upon different psychological abilities. This research suggests that psychological predictors of performance in traditional sports may predict performance in hybrid video games that share game mechanics.

A study on the application of game theory modeling in the analysis of pharmaceutical price elasticity

Abstract Setting reasonable drug prices is the fundamental goal of drug price elasticity analysis, and the game theory method can play a role in drug pricing by analyzing the behaviors of multiple game subjects to give a plan that meets the best interests of all parties. The optimal pricing strategies under different threshold conditions are summarized by establishing four model assumptions and solving them based on the basic model of game theory and the bidding process. Accordingly, the drug pricing of Pharmaceutical Company F was analyzed, and it was found that its optimal pricing was 21.3yuan, at which time the profit was 132.74% higher than the original pricing profit. After applying this pricing, it was found that the implementation of the new pricing increased the mean score of the company’s profitability by 0.16738 to 0.19504 as compared to before the optimized drug pricing strategy, indicating that the pricing strategy improved by the game theory model is able to provide the company’s level of profitability and is feasible.

Decreased Concussion Incidence Following the Implementation of the Targeting Rules: An Updated Epidemiology of National Football League Concussions From 2017 to 2022.

The incidence of concussions in football, and the ensuing media attention, has garnered scientific investigation, prompted technological advances in protective gear, and altered the rules of the game, including the National Football League's (NFL) "Targeting" rule, which began in 2018, but the impact of these changes is unclear. This study aims to describe the epidemiology of concussions that occurred in five NFL seasons from the 2017-2018 season through the 2021-2022 season and characterize positional differences in rate and games missed. There was a significant decrease (p = 0.02) in total concussions between the 2017-2018 season (102 concussions) and the remaining four seasons (average of 73.80 concussions per year), accounting for a 38% decrease. Offensive and defensive units had decreased concussion rates and average games missed per concussion. Defensive backs (10.46 per 1,000 athlete exposures (AEs)) and tight ends (10.69 per 1,000 AEs) had the highest concussion rates, and the defensive line had the highest average games missed per concussion at 3.97. The introduction of the "Targeting" rule and other rule changes in the NFL in 2018 correlated with a decrease in total concussions per year, total games missed due to concussion, and average games missed per concussion. Offense and defense experienced similar reductions in concussion incidence and severity. Overall, the updated epidemiology of NFL concussions suggests that the incidence of concussions has decreased; however, players continue to experience concussions that require them to miss multiple games.

Reinforcement learning-based formation-surrounding control for multiple quadrotor UAVs pursuit-evasion games

This paper proposes a reinforcement learning-based formation-surrounding control method for multiple quadrotor unmanned aerial vehicles (UAVs) pursuit-evasion (MPE) games system subject to external disturbances. In the framework of the MPE games, the pursuers aim to equally surround the evaders which try to avoid being surrounded when forming the desired formation. By constructing position and attitude tracking error subsystems of quadrotor UAV, this paper proposes two control strategies which combines the feedforward control technique and reinforcement learning (RL) method. First, two novel cost functions are presented for the quadrotor UAV with external disturbances. Then, two control schemes based on RL have been developed to guarantee the stability of the tracking error subsystem. Subsequently, two critic-only neural networks (NN) weight update laws that only satisfy finite excitation conditions are proposed to estimate the optimal cost function. Furthermore, Nash equilibrium for multiple quadrotor UAVs is achieved by means of RL strategy to solve the Hamilton-Jacobi-Isaacs (HJI) equations. And the property of equally surrounding is proved for the first time by utilizing Euler's formula in this paper. Finally, the numerical simulation results are given to show the effectiveness and superior performance of the proposed control method.

Cooperative decision-making of multiple autonomous vehicles in a connected mixed traffic environment: A coalition game-based model

Advances in vehicle-networking technologies have enabled vehicles to cooperate in mixed traffic. However, realizing the cooperative decision-making of multiple connected autonomous vehicles (CAVs) when influenced by the presence of connected manual vehicles (CMVs) is a challenging area in current research. In this study, we propose a coalition game-based (CG-based) model for multi-CAV cooperative decision-making in a connected mixed traffic environment. First, the model integrates the perceived risk field theory, quantifying the driving risk from the perspective of different CMVs; this risk is used to determine the uncertainty of the motion state of CMVs. Second, the model can identify the conflicts caused by multiple lane-changing vehicles and decouple the conflict problem into multiple two-vehicle lane-changing games, including a cooperative game between two CAVs and a non-cooperative game between a CAV and a CMV. To test the proposed model, four scenarios that blocked the passage of multiple CAVs were set up; in these scenarios, the average speed of the CG-based model was 21.05, 16.76, 23.17, and 12.55% higher than that of the LC2013 model. The simulation results showed that the CG-based model could improve the efficiency of multiple CAVs while ensuring safety in a mixed traffic flow.

A Mathematical Connection Between Single-Elimination Sports Tournaments and Evolutionary Trees

Summary How many ways are there to arrange the sequence of games in a single-elimination sports tournament? We consider the connection between this enumeration problem and the enumeration of “labeled histories,” or sequences of asynchronous branching events, in mathematical phylogenetics. The possibility of playing multiple games simultaneously in different arenas suggests an extension of the enumeration of labeled histories to scenarios in which multiple branching events occur simultaneously. We provide a recursive result enumerating game sequences and labeled histories in which simultaneity is allowed. For a March Madness basketball tournament of 68 labeled teams, the number of possible sequences of games is ∼ 1.91 × 10 78 if arbitrarily many arenas are available, but only ∼ 3.60 × 10 68 if all games must be played sequentially in the same arena.

Entropy as a Measure of Puzzle Difficulty

Evaluating and ranking the difficulty and enjoyment of puzzles is important in game design. Typically, such rankings are constructed manually for each specific game, which can be time consuming, subject to designer bias, and requires extensive play testing. An approach to ranking that generalizes across multiple puzzle games is even more challenging because of their variation in factors like rules and goals. This paper introduces two general approaches to compute puzzle entropy, and uses them to evaluate puzzles that players enjoy. The resulting uncertainty score is equivalent to the number of bits of data necessary to communicate the solution of a puzzle to a player of a given skill level. We apply our new approaches to puzzles from the 2016 game, The Witness. The computed entropy scores largely reproduce the order of a set of puzzles that introduce a new mechanic in the game. The scores are also positively correlated with the user ratings of user-created Witness puzzles, providing evidence that our approach captures notions of puzzle difficulty and enjoyment. Our approach is designed to exploit game-specific knowledge in a general way and thus can extended to provide automatic rankings or curricula in a variety of applications.

Understanding Human-AI Teaming Dynamics through Gaming Environments

With the goal of better understanding Human-machine Teaming (HMT) dynamics and how team competencies that are transportable across contexts can lead to different teaming behaviors and team performances, I propose a series of three studies to explore communication, coordination and adaptation in HMT paradigms. I implement and integrate multiple AI agents and use collaborative games as testing environments to evaluate teaming effects. My work can provide findings to two higher level research questions that are widely studied in HMT: 1) the bidirectional behaviors that human and AI agents may develop when working as a team and, 2) how different types of AI agents can impact the teaming efficiency in human-AI teaming. Besides, my work can also contribute to Human-Computer Interaction and Game AI scholarship with insights into teaming dynamics in Human-AI teaming.

Creating Diverse Play-Style-Centric Agents through Behavioural Cloning

Developing diverse and realistic agents in terms of behaviour and skill is crucial for game developers to enhance player satisfaction and immersion. Traditional game design approaches involve hand-crafted solutions, while learning game-playing agents often focuses on optimizing for a single objective, or play-style. These processes typically lack intuitiveness, fail to resemble realistic behaviour, and do not encompass a diverse spectrum of play-styles at varying levels of skill. To this end, our goal is to learn a set of policies that exhibit diverse behaviours or styles while also demonstrating diversity in skill level. In this paper, we propose a novel pipeline, called PCPG (Play-style-Centric Policy Generation), which combines unsupervised play-style identification and policy learning techniques to generate a diverse set of play-style-centric agents. The agents generated by the pipeline can effectively capture the richness and diversity of gameplay experiences in multiple video game domains, showcasing identifiable and diverse play-styles at varying levels of proficiency.

A multiple access channel game with users implementing throughput and latency metrics

A multiple access channel game with users implementing throughput and latency metrics

Video Game Interface Design Patterns to Facilitate Human-Agent Teaming

User interface design patterns that document Human-Agent Team (HAT) interface best practices were developed by analyzing team video games with different types of agents, ranging from virtual players in sports games to advisors contributing to strategy and planning in combat games. One factor that may contribute to the enormous success of some games is the cohesive team interactions between humans and agents. A design pattern collection was developed by identifying 25 design patterns under interface themes most relevant to HATs. The design patterns describe how multiple successful game interfaces handle challenging aspects of HAT interaction, addressing contexts including planning, spatial orientation, task management, communication, and more. Based on the complex and well-tested interface solutions in video games, these design patterns can provide HAT user interface developers practical guidance for interface development and a starting point for developing a HAT design pattern language.

Emotions and online gaming experiences: An examination of MMORPG gamers from India and the United States

Massively multiplayer online role-playing games (MMORPGs) constitute a genre of online games that has enjoyed phenomenal market success due to in-game purchases and push advertising. Despite the genre's popularity, little is known about players' experiences with these games. Using an Indian panel of 319 players and a U.S. panel of 425 players, we examined multiple game experiences and the impacts of each on players' satisfaction and replay intentions. Study 1 explored Indian players' positive and negative feelings; findings showed that positive feelings positively influenced flow, immersive, and social experiences, whereas negative feelings had no significant effects on other game experiences. Study 2 addressed U.S. players' game experiences as well as their satisfaction and replay intentions. While positive feelings and flow experiences positively affected players' satisfaction and replay intentions, immersive experience did not. Social experiences played a positive role in players' satisfaction but did not influence their replay intentions. Results highlight the importance of positive game experiences and carry managerial implications for game marketers and designers.

Employing Metaverse Marketing Through Gaming And Its Impact On Customer Experience: Evidence From Multiple Online Gaming Platforms

Employing Metaverse Marketing Through Gaming And Its Impact On Customer Experience: Evidence From Multiple Online Gaming Platforms

Soft-Safe: Software Defined Safety-as-a-Service for Intelligent Transportation System

In this work, we propose Soft-Safe, a Software Defined Safety-as-a-Service (Safe-aaS) model for provisioning safety-related decisions to the registered end-users. In Safe-aaS, the end-users register to the infrastructure, provide their initial and destination location, select certain decision parameters, and make payment through a Web portal. As the safety-related decisions are time-critical in nature, therefore timely delivery of these decisions is essential. Considering these facts and road transportation as the application scenario of Safe-aaS, we address the problem of efficient decision delivery to the end-users in two stages. In the first stage, we propose a Software Defined Safe-aaS platform to address the problems of heterogeneity among the SDN switches present in the edge layer. Further, based on the utility of each of the SDN switches present within the vicinity of the end-users, we optimally select a suitable SDN switch among the available ones, for delivering them decisions in the second stage. To obtain the maximum utility for delivering decisions to the end-users, we map the interactions between the SDN controller and SDN switches as a Non-cooperative Single Leader Multiple Follower game. Then, we estimate the optimal delay incurred by an SDN switch applying the Lagrangian function and Karush-Kuhn-Tucker (KKT) conditions. Exhaustive simulation results illustrate that the energy consumed and delay incurred using our proposed scheme, Soft-Safe, is reduced compared to the existing schemes, Traditional Safe-aaS and MoRule.

Transformative live-action roleplay and Dagorhir costumes: Regulation, consumption and power dynamics, 1977 to the present

Dagorhir is one of the largest and oldest documented live-action roleplay groups. Dagorhir organizers have published multiple game regulations via handbooks with much emphasis on costumes since the 1970s. Dagorhir facilitates community building, identity negotiation and creative storytelling that expands beyond the game through transformative play. In our research, we examine how these costume regulations have influenced fantasy character and real-world identities, how the regulations have influenced perceived costume authenticity over time and how the handbook regulations have engaged with power dynamics related to intersectional identities. We analysed costume-related content in the three handbooks while drawing upon content analysis and historical methods. We found that as the regulations evolved since the 1970s, the rules increasingly centred costumes, indicating the prominence of costume in this escapist community. However, while these spaces centred on the costumed body, Dagorhir regulations reinforced oppressive intersectional norms. Our work has implications for society and business, that is, our findings can help individuals understand why people participate in live-action roleplay, which may reduce stigma surrounding this activity. Additionally, costume producers and retailers can make informed business decisions based upon our findings. Last, live-action roleplay communities can utilize our findings to reject oppressive written and unwritten regulations.

Optimal scheduling of data centers based on multiple games

With the increasing dominance of electricity retailers in the electricity market, it has become a new trend for the data center (DC) to participate in sales-side transactions. However, data center electricity retailers (DCERs) and DCs that purchase electricity by DCERs, as different stakeholders, will inevitably face conflicts of interest. To promote the benefit distribution of DCs and DCERs to achieve a win–win situation, our study proposes an optimal scheduling method based on multiple games and establishes a mixed game model by integrating the master–slave game method and the cooperative game method, in which DCERs take profit maximization as the optimization goal, while Internet DCs take the lowest total cost as the optimization goal. The master–slave game is adopted between the DCER and the DC, and the cooperative game is adopted among the members of the DC. The benefits are distributed through Nash bargaining. The model is solved by using the particle swarm optimization algorithm combined with the alternating direction method of multipliers. To demonstrate the effectiveness of our proposed method, we provide an illustrative example that showcases its ability to not only increase DCER revenue by 136.04% but also decrease total DC costs by 9.39%. As a result, our method facilitates a more equitable distribution of cooperation revenues.

Poster 380: Decreased concussion incidence following revised contact rules; An updated epidemiology of NFL concussions from 2017-2022

Objectives: The incidence of concussions in football, and the media attention that followed, has garnered scientific investigation, prompted technological advances in protective gear, and altered the rules of the game, including the NFL’s “Targeting” rule, which began in 2018. In previously studied seasons, certain positions, such as offensive skill players, had higher rates of concussions while defensive secondary and offensive line players suffered the greatest number of concussions, but the severity of these concussions has not been reported. The advent of the “Targeting” rule has been shown to reduce concussions in collegiate football leagues, but its effect on NFL and professional-level players is unknown. The objectives of this retrospective study were to describe the epidemiology of concussions among professional football players in the NFL during the last five seasons, determine changes in incidence over the study period, and characterize positional differences in rate and games missed. Methods: The current study was a descriptive epidemiological study that retrospectively reviewed all concussions that occurred in the five NFL seasons from the 2017-2018 season through the 2021-2022 season that resulted in at least one game missed. Total concussions, total games missed due to concussion, and average games missed per concussion were extracted from publicly available injury reports and were cross-referenced with publicly available sources. Concussion rates were calculated per 1,000 athletic exposures (AEs). A sub-analysis was performed by year, game unit, position type, and game week. Results: In 1,216 regular season games in the five NFL seasons, there were a total of 368 concussions for a rate of 0.30 concussions per game and 7.04 concussions per 1,000 AEs. More concussions were concentrated in the last one-third of the regular season. There was a statically significant decrease (38%; p<0.05) in total concussions between the 2017-2018 season (102 total concussions) and the four seasons between 2018-2019 and 2021-2022 (average of 73.8 concussions per year). During the five seasons, there were 1,014 games missed due to concussion, an average of 2.76 games missed per concussion, and 0.056 games missed due to concussion per 1,000 AEs. Following the 2017-2018 season, there was a 53% decrease in the total games missed due to concussion (Figure 1b) and a 38% decrease in the average games missed per concussion (Figure 1c). Descriptively, both offensive and defensive units had decreased concussion rates and average games missed per concussion in the four seasons after 2017 (Figure 2). Defensive backs (10.46 per 1,000 AEs) and tight ends (10.69 per 1,000 AEs) had the highest concussion rates. The defensive line had the highest average games missed per concussion at 3.97 (Table 1). Conclusions: The introduction of the “Targeting” rule in the NFL beginning in the 2018 season correlated with a decrease in total concussions per year, total games missed per concussion, and games missed per concussion. Both offensive and defensive units experienced similar reductions in concussion incidence and severity. Overall, the updated epidemiology of NFL concussions suggests that efforts to protect professional football players from concussions have been successful, however, players continue to experience concussions that require them to miss multiple games. [Table: see text]

The Construction of Chinese Metropolitan Area from the Perspective of Politics of Scale: A Case Study of Nanjing Metropolitan Area, China

The spatial political logic of the construction of Chinese metropolitan areas (CMAs) is unique and complex, involving the interaction of power, spatial production, and the construction of political rationality between multiple scales. Taking the representative Nanjing metropolitan area as an example, we use the “material–organizational–discursive” analytical framework of politics of scale theory to analyze the construction logic of CMAs. This study finds the following: (1) In general, the CMA is a high-quality spatial construction resulting from multi-city negotiation, inter-provincial collaboration, and central–territory linkage, and has generally undergone a process of increasing the power of subjects, nested power relations, frequent scale interactions, and complex interest games; among them, planning is not only a scale tool for competing for power, but also an important representation of the results of multiple power games. (2) In terms of the construction of material space, both the delineation of boundaries and the cross-border connection of infrastructure represent rational thinking and stand as two-way choices of the two power subjects in the MA based on the maintenance and expansion of their own spatial development rights. (3) In terms of organizational space construction, CMAs mainly adopt flexible means, with bilateral and multilateral cooperation at the horizontal level, while there is a certain power inequality at the vertical level. (4) In the construction of discursive space, CMAs have experienced increasing construction significance, escalating scale subjects, and overlapping discourse narratives, and the contrast of power relations has also changed. The contribution of this paper is an expansion of the analytical framework of politics of scale based on the division of spatial dimensions, which provides a new perspective for understanding the construction of CMAs, and also helps us to picture Chinese city–regionalism.

On the relationship between mobile-based extramural activities and vocabulary development of EFL learners: a mixed-method study

Mobile-based extramural English (EE) activities, including watching movies, playing digital games, and listening to music outside the classroom, have played an important role in increasing learners' interest in English as a foreign language (EFL). This mixed-method design study aimed to investigate the role of EE activities in the vocabulary development of intermediate EFL learners. The study included a group of 60 learners, including 30 male and 30 female students from two language institutes. A pretest, posttest, and delayed posttest were used. The experimental group utilized WhatsApp to receive electronic vocabulary instruction four days per week for two months as part of the EE activities. In contrast, the control group received classroom instruction using the conventional approach typically employed in EFL contexts for teaching the same textbook vocabulary. A semi-structured interview was conducted to investigate the participants' beliefs regarding their preference for EE-based activities. The results of the EG group revealed that EE-based activities significantly impacted the students' vocabulary learning (p < 0.001). The findings also revealed no significant differences in vocabulary knowledge between male and female students after using EE activities (p = 0.34). The themes that emerged from the qualitative phase suggested that participants preferred EE-based activities as they can result in less mental stress, more vocabulary learning, improved conversation, and improved pronunciation and grammar. Also, the participants preferred various mobile-based EE activities, including watching movies, listening to music, playing multiple games, watching cartoons, and focusing on movie subtitles, which resulted in their vocabulary development. The findings call for language educators to integrate more virtual and online-based EE activities to supplement traditional vocabulary teaching practices.

An Evolutionary Game Theory-Based Method to Mitigate Block Withholding Attack in Blockchain System

Consensus algorithms are the essential components of blockchain systems. They guarantee the blockchain’s fault tolerance and security. The Proof of Work (PoW) consensus algorithm is one of the most widely used consensus algorithms in blockchain systems, using computational puzzles to enable mining pools to compete for block rewards. However, this excessive competition for computational power will bring security threats to blockchain systems. A block withholding (BWH) attack is one of the most critical security threats blockchain systems face. A BWH attack obtains the reward of illegal block extraction by replacing full proof with partial mining proof. However, the current research on the BWH game could be more extensive, considering the problem from the perspective of a static game, and it needs an optimal strategy that dynamically reflects the mining pool for multiple games. Therefore, to solve the above problems, this paper uses the method of the evolutionary game to design a time-varying dynamic game model through the degree of system supervision and punishment. Based on establishing the game model, we use the method of replicating dynamic equations to analyze and find the optimal strategy for mining pool profits under different BWH attacks. The experimental results demonstrate that the mining pools will choose honest mining for the best profit over time under severe punishment and high supervision. On the contrary, if the blockchain system is supervised with a low penalty, the mining pools will eventually choose to launch BWH attacks against each other to obtain the optimal mining reward. These experimental results also prove the validity and correctness of our model and solution.