Game Strategy Research Articles

The application of artificial intelligence technology in games

The production of games requires many factors and a lot of human labor, and still the emergence of artificial intelligence has changed this, the efficiency and precision of artificial intelligence makes it gradually more used in the field of games. This paper mainly discusses the application of AI in the field of games from four aspects: the intelligence of AI for opponents, helping to develop game strategies, the story and plot of the game and game generation. Artificial intelligence can be used to simulate opponents with intelligent behavior in games. This can add to the challenge and realism of the game. It can also be used to develop game strategies and optimize how tasks are completed. Artificial intelligence helps in promoting the story and plot of the game. Finally, AI can be used to generate game content and plot. Also, this paper gives an outlook on the hot spots and development prospects of this research topic.

Improve speaking skills with Duolingo’s mobile game-based language learning

The purpose of this research is to evaluate the effectiveness of Duolingo's game-based methodology in improving speaking proficiency within mobile language learning, while also examining the specific attributes and strategies contributing to its success and exploring implications for language education and learner optimization. Given the growing prevalence of mobile language learning platforms, the research meticulously scrutinizes the specific attributes and strategies employed by Duolingo that contribute to the refinement of oral fluency. This study employs a mixed methods design, integrating phenomenological and experimental approaches through a pre, post and attainment speaking tests with a control group design supported with metaphorical perceptions. The findings underscore the pivotal role of assimilating technological advancements and gamified pedagogical approaches within language education to expedite effective intercultural communication across multifarious linguistic landscapes. Furthermore, the results emphasize the importance of continuously adapting language learning methodologies to leverage emerging technologies and gamification strategies in order to foster effective communication skills in diverse linguistic contexts. The implications for prospective inquiries advocate for longitudinal investigations delving into the enduring implications of mobile game-based language learning on comprehensive linguistic acquisition, necessitating comparative inquiries to ascertain the comparative efficacy of diverse mobile applications in fostering distinct language proficiencies. Additionally, probing the influence of individual learner attributes and predilections in optimizing the utilization of mobile language learning applications could yield valuable insights for tailoring language acquisition paradigms.

«Бьюти-пространство» Боттичелли, поп-арт и гностики (к вопросу о становлении классического искусства)

<p>The article continues the series of publications by the author on the art of the Renaissance and the work of Botticelli. The author's concept of “classical art” allows us to establish closer connections with subsequent stages of artistic development, as well as with the Early Renaissance. The multi-level structure of Botticelli’s art and the “collage” nature of his works are substantiated. The “universality” of the classics correlates with the gaming strategies of Neoplatonism and Gnosticism. The features that bring the intellectual culture of the Renaissance closer to modern scientific and artistic trends are revealed. New contexts and parallels (Michael Psellus, Honore de Balzac, Arthur Schopenhauer, Alois Riegl, David Hockney, Roy Lichtenstein) allow us to re-evaluate the transformation of the Neoplatonic tradition in European culture. The author rejects rigid interpretations of Gnosticism and Neoplatonism in connection with the work of Botticelli, preferring an “aesthetic” or “poetic” reading. Within the framework of this essentially psychological approach, the author draws attention to the problem of “presence” (“life-likeness”), characteristic of both medieval and modern art. Social issues of interpretation of classical art are touched upon in the article in connection with elements of elitism in the culture of the Medici circle. The concept of “poetry”, developed by Petrarch and Boccaccio and going back to ancient prototypes, is fully consistent with this type of “court” culture, which played a decisive role in the development of classical art. The "decadence" of the late Quattrocento and the work of Botticelli as its highest expression were thus the result of very complex intellectual strategies that were continued during the High Renaissance and Mannerism. Particular attention in the article is paid to the revision of the usual views on the historiography of the Renaissance, the actualization of classical art historical concepts. The article returns to the problem of the origins of the semiotic concept of art. Pragmatism and the “irrational” concept of art (appealing to the unconscious) turn out to be quite compatible, that has particular theoretical significance for the revaluation of conventional approaches to the classical heritage.</p>

Entry under placement uncertainty

We present a model of firm entry in an industry that operates under an aggregate production quota or cap-and-trade (CAT) regulation. Firms are heterogeneous in their own productivity; each knows its costs of production but is uncertain about where its costs rank among an entrant population. We show the existence of a unique, symmetric, dominance solvable, Bayesian Nash equilibrium in switching strategies in a parameterized game with a continuum of players. Our main result is that uncertainty over one's productivity rank is sufficient to cause socially inefficient over-entry when the average cost in the population of potential entrants is low. We find socially inefficient under-entry when the opposite conditions hold. Within both the class of models on global games with strategic substitutes and the class of models on firm entry, our model offers innovative insights into inefficient over-entry, under-entry, and introduces a novel underlying mechanism that drives entry bias.

Validation of the Gaming Skills Questionnaire in Adolescence: Effects of Gaming Skills on Cognitive and Affective Functioning.

Given the widespread popularity of videogames, research attempted to assess their effects on cognitive and affective abilities, especially in children and adolescents. Despite numerous correlational studies, robust evidence on the causal relationship between videogames and cognition remains scarce, hindered by the absence of a comprehensive assessment tool for gaming skills across various genres. In a sample of 347 adolescents, this study aimed to develop and validate the Gaming Skill Questionnaire (GSQ) and assess the impact of gaming skills in six different genres (sport, first-person shooters, role-playing games, action-adventure, strategy, and puzzle games) on cognitive and affective abilities of adolescents. The GSQ exhibited strong reliability and validity, highlighting its potential as a valuable tool. Gaming skills positively affected executive function, memory, overall cognition, cognitive flexibility, and emotion recognition, except for empathy. Various game genres had different effects on cognitive and affective abilities, with verbal fluency influenced mainly by sports, executive functions by action, strategy, and puzzle, and emotion recognition positively impacted by action and puzzle but negatively by sports and strategy games. Both age and gaming skills influenced cognitive flexibility, with gaming having a greater effect. These intriguing genre-specific effects on cognitive and affective functioning postulate further research with GSQ's contribution.

Investigation into the Benefits of Game-Based Educational Strategies for Enhancing the Physical Fitness of 10–12-Year-Old Kickboxing Athletes

This study examines the benefits of game-based educational strategies for enhancing the physical fitness of 10–12-year-old kickboxing athletes. Considering the developmental aspects of children in this age group, the study focuses on the effects of gaming strategies on enhancing core physical qualities such as strength, speed, endurance, agility, and coordination. Additionally, it addresses the motivational dimension, examining how these game-based approaches foster a growing interest in sports activities among young athletes.
 Integrating game-based techniques into the training routine not only inserts excitement and breaks the monotony but also facilitates the continuous incorporation of kickboxing's technical and tactical aspects. This approach enhances athletes' comprehension and quick mastery of essential skills. Emphasis is also placed on customizing the training approach, enabling the adjustment of sessions to meet the distinct requirements of each athlete while reducing the likelihood of sports-related injuries.
 The results of the study highlight the substantial benefits of including game-based educational strategies in the training of young kickboxers. These methods boost both the physical and mental growth of the athletes, nurturing a favorable perspective towards sports and competitive activities. It is advised that further exploration and formulation of targeted training schemes, embracing game-based educational strategies, be pursued for their fruitful integration into athletic training routines. Additionally, this research covers the way for a more profound comprehension of how game-based educational strategies can enhance the gaining of technical and tactical competencies among young sports enthusiasts, suggesting innovative training strategies that respect the unique aspects of childhood and the distinct traits of every participant.

From Nash Q-learning to nash-MADDPG: Advancements in multiagent control for multiproduct flexible manufacturing systems

The emergence of flexible manufacturing systems (FMS) capable of processing multiple product types is a result of the growing demand for product customization and personalization. Such multiproduct systems are characterized by a higher level of uncertainty and variability when compared to traditional manufacturing systems. This paper proposes a Nash integrated multiagent deep deterministic policy gradient method (Nash-MADDPG) to control the mobile robots’ assignment in a multiproduct FMS to enable intelligent decision-making, interaction, and dynamic learning capabilities. A mathematical model of a multiproduct FMS from a previous study is described, and system dynamic property is characterized by permanent production loss (PPL). Then, by observing PPL of the system and market demand for each product type, the multi-agent control scheme is developed to assign mobile robots to load/unload various product types at various machines. First, a Nash game is developed among the mobile robots and to improve the cooperation, a collaboration cost is defined. This collaboration cost is then used in the reward function of the multiagent deep deterministic policy gradient (MADDPG) algorithm. Second, the actions are jointly defined based on the action values of MADDPG, and the mobile robots’ strategies in the Nash game, which update the environment to a new state. The performance of the proposed method is verified by comparing it with conventional Nash Q-learning, vanilla MADDPG, Q-learning based single agent reinforcement learning (SARL) and a first-come-first-serve (FCFS) based control. The results demonstrate that the multi-agent control scheme under the proposed Nash-MADDPG is effective in dealing with cooperative FMS environment that involves complicated dynamics and uncertainties.

RunsGuard Framework: Context Aware Cricket Game Strategy for Field Placement and Score Containment

Sports analytics utilizes data analysis techniques and computational methods to gain insights, make informed decisions, and facilitate improvements in the performance of individuals and teams. Cricket is one of the most popular games and continues to evolve worldwide. The availability of ball-by-ball data demands in-depth investigation of player strategies, team dynamics, and the impact of contextual variables. Existing studies explored various aspects of cricket analytics, including detecting key events, predicting outcomes, and ranking teams. However, the literature lacks a comprehensive integrated framework that processes unstructured sports commentary, extracts actionable insights, conducts a thorough player analysis, and develops strategic plans while considering contextual factors. This work aims to propose a bowling and fielding strategy to contain a batsman. For this purpose, we developed a comprehensive context-aware framework that collects data, extracts insights from commentary, identifies player strengths and weaknesses, and proposes cricket bowling and fielding strategies according to the given context. To evaluate this work, we implemented a case study that simulated different scenarios, and our framework suggested bowling and fielding strategies. In these simulations, the proposed strategies consistently demonstrated a substantial reduction in the number of runs that were scored. On average, the framework reduces the batsman’s score rate by 33%. These findings underscore the practical effectiveness of research in optimizing field placement and effectively reducing scoring opportunities. Finally, by bridging the gap between data analytics and cricket game strategy, this methodology provides a competitive advantage to coaches, captains, and players. In the future, we aim to involve temporal patterns to understand the evolving behavior of players.

Digital labor in free-to-play games: player as commodity and interaction as labor in MMOGs

ABSTRACT As the lines between leisure and work have become increasingly indistinct, gaming has evolved from a purely recreational pastime to a productive endeavor, leading to a shift from players as consumers to players as laborers. Inspired by “women's work” studies and audience commodity theory, this research takes League of Legends (LoL) as a case to analyze how player interactions, as labor, create value within free-to-play (F2P) massively multiplayer online games (MMOGs). This article employs a combination of political economic, and critical analysis to demonstrate how free-to-play games monetize player interactions within them. It also proposes a pattern for understanding the exploitation of players' labor in three phases: the labor process, remuneration settlement, and consumption. Thus, this study contributes to the digital labor debate by combining the notions of “women's work” and digital labor and extending audience commodity theory into the domain of video games. It also enriches the scholarly conversation on the monetization strategies of video games and free-to-play commodities, emphasizing the unrecognized labor inherent in player interactions.

A Comprehensive Analysis of Game theory on Multi-Agent Reinforcement

In recent years, reinforcement learning has gradually emerged as a popular research field in artificial intelligence. However, for multi-agent systems, due to their complex environment and an abundance of agents, the learning target of maximizing the anticipated value of cumulative rewards for specific agents frequently fails to converge. Introducing game theory into reinforcement learning can effectively address the interactions among intelligent agents, provide a rationale for convergence points corresponding to strategies. To address the issue of non-existence of optimal solutions for certain tasks in multi-agent settings, this paper takes a game-theoretic perspective and summarizes classical reinforcement learning algorithms developed in recent years. The basic theory of multi-agent reinforcement learning, essential game theory, categorization of reinforcement learning using multiple agents game strategies, primary worries are addressed in the study. It also analyzes the challenges that game-theoretic multi-agent reinforcement learning algorithms may encounter in the future, along with the relevant optimization directions.

Applications and Learning Outcomes of Game Based Learning in Education

Game-based learning (GBL) is considered the most engaging means of learning and brings several benefits as regards the learning outputs. Game-based learning is applied in all different educational stages from pre-school education to tertiary education, and workplace. This review study discusses and extends previous findings by organizing the application of GBL approaches in different educational stages and presenting the main learning outcomes. The review study collects and analyzes 104 scientific papers ranging from 2013-2021. The benefits and limitations of GBL are also discussed in the paper, while different types of games including augmented reality (AR) approaches are considered. According to the findings, in primary and secondary education, GBL demonstrates a positive impact on learning outcomes and engagement, enhancing students' understanding of complex concepts and fostering real-world application of learned knowledge. While GBL in tertiary education facilitates deeper understanding, critical thinking, and skill development, its implementation requires careful design and evaluation aligned with learning objectives. The study also explores various types of GBL games, including memory, simulation, interactive, quiz, puzzle, strategy, and reality-testing games, each tailored to different educational objectives and subjects. Furthermore, Augmented Reality (AR) in GBL shows promise across subjects but faces challenges like technical limitations, training needs, privacy concerns, potential distractions, and a lack of comprehensive research on its efficacy. Overall, while GBL demonstrates considerable potential in enhancing education, its successful implementation requires careful consideration of age-appropriateness, varied game types, and integration of emerging technologies like AR.

Multi-agent low-carbon optimal dispatch of regional integrated energy system based on mixed game theory

In the context of global warming and energy scarcity, regional integrated energy system (RIES) can effectively improve energy utilization efficiency and reduce carbon emissions. However, this leads to the increased complexity of the market transactions. To this end, based on the mixed game strategy, a multi-agent low-carbon optimal dispatch model of RIES is proposed in this paper. Firstly, to fully consider the low-carbon objective of the system, a reward and punishment ladder carbon trading mechanism and a ladder integrated demand response (IDR) model are developed. Then, the decision models of the energy management operator (EMO), multiple energy hub agents (EHAs) and the user load aggregator (ULA) are constructed respectively with the goal of economy, and carbon emission flows are introduced as constraints. The interactive trading process of various stakeholders is simulated by a mixed game with master-slave game nested bidding strategy. Finally, the economics and carbon emissions of the system in different scenarios are analyzed by examples, and the effectiveness of the proposed model is verified. Numerical simulation results show that the proposed method not only has good economic and low-carbon environmental protection benefits, but also ensures the interests of various stakeholders.

Stability, period and chaos of the evolutionary game strategy induced by time-delay and mutation feedback

In the classical evolutionary game theory, mutation is usually considered as a constant, however strategy mutation is affected by strategies in the real game process. Therefore, the main purpose of this paper is to study the effects of mutation feedback and time delays on strategy dynamics, where mutation is a linear feedback related to strategy. First, we construct a co-evolutionary game model with two time delays induced by mutation feedback and analyze the existence and stability of the equilibria of the non-time delay system. The conditions for the coexistence of the two strategies and the mutation rate are obtained. Second, Sotomayor’s theorem is used to explore the transcritical bifurcation of the system. Then, the existence of Hopf bifurcation is investigated by using feedback delay and payoff delay as bifurcation parameters in the time-delay system. Furthermore, we discuss the direction of the Hopf bifurcation, stability and periodic change of the periodic solution in detail. Finally, a series of numerical simulations are used to describe the theoretical analysis. The main results are as follows: (i) Mutation causes negative feedback to cooperative strategy. (ii) As the time delay increases, the stable equilibrium point becomes unstable, and which branches a stable limit cycle. When the time delay continues to increase sufficiently, the stable limit cycle becomes unstable and produces irregular oscillation and chaos. (iii) When the two time delays are large enough, the coexistence of the two strategies becomes that defective strategy is dominant, and the mutation rate also reaches the maximum.

The Impact of Gamification on EFl Students’ Reading Comprehension

The 21st century has witnessed significant educational changes, primarily driven by technological advancements. These changes triggered the new learning systems and methods, marking the transition from the era of globalization to the age of Society 5.0. However, traditional teaching methods often fail to align with these technological developments, resulting in passive and unmotivated students. It highlights the need for new strategies that leverage technology and promote active student engagement. Reading comprehension is crucial in EFL education, enabling students to comprehensively grasp and analyze written content. Developing strong reading comprehension skills empowers students to gather, organize, and interpret information effectively. In this context, gamification has emerged as a powerful strategy. Based on that problem, this research aims to investigate the impact of gamification on EFL students' reading comprehension. This research used a library research method and analysis of ten selected empirical research articles on internet search engines such as Google Scholar, Mendeley, and ERIC websites. The study addresses fundamental questions regarding the effective game elements for enhancing EFL students' reading comprehension, the school levels at which gamification strategies can be effectively applied, and the impact of gamification on student engagement and motivation. The findings of this research provides references for teachers with evidence-based practices and valuable insights for designing and implementing gamified reading comprehension activities that maximize learning outcomes. By integrating gamification strategies into EFL classrooms, teachers can create dynamic and enjoyable learning environments that foster active student participation and promote improved reading comprehension skills. Keywords: Technological advancements, gamification, game elements, EFL students, reading comprehension

Optimisation of Game Strategies Under Information Asymmetry Between Insurance Companies and Consumers

The information asymmetry common in insurance markets has a profound impact on market operations and outcomes, and game theory provides a framework for understanding and responding to this problem. This paper explores the manifestation of information asymmetry in the insurance market and the application of game theory, as well as the optimisation of strategies between insurers and consumers. On the part of insurance companies, game strategies are optimised through measures such as improving information transparency, enhancing risk assessment and establishing long-term cooperative relationships, while consumers actively participate in the market game by enhancing their awareness of self-protection, improving their insurance knowledge and choosing reputable insurance companies. These optimisation measures help to improve the market environment, enhance market efficiency and achieve a win-win situation in the insurance market, laying the foundation for the healthy development and sustainable stability of the insurance market.

Distributed Minmax Strategy for Multiplayer Games: Stability, Robustness, and Algorithms.

This article studies a distributed minmax strategy for multiplayer games and develops reinforcement learning (RL) algorithms to solve it. The proposed minmax strategy is distributed, in the sense that it finds each player's optimal control policy without knowing all the other players' policies. Each player obtains its distributed control policy by solving a distributed algebraic Riccati equation in a multiplayer noncooperative game. This policy is found against the worst policies of all the other players. We guarantee the existence of distributed minmax solutions and study their L2 and asymptotic stabilities. Under mild conditions, the resulting minmax control policies are shown to improve robust gain and phase margins of multiplayer systems compared to the standard linear-quadratic regulator controller. Distributed minmax solutions are found using both model-based policy iteration and data-driven off-policy RL algorithms. Simulation examples verify the proposed formulation and its computational efficiency over the nondistributed Nash solutions.

Coaching Leadership on Team Culture of Basketball Coaches

This study focuses on the importance of educational leadership in the field of education in the 21st century, especially the key role of coaches in the field of college basketball. As basketball's status in our country increases, the leadership skills of coaches are crucial to the overall development of colleges and universities. The article emphasizes that in addition to professional skills, coaches also need to have strong leadership skills to meet students' psychological needs and promote students' growth. Secondly, the article explores the impact of coaches’ leadership behaviors on students’ potential development and team effectiveness. Excellent coaches not only teach techniques, but also formulate training plans and game strategies based on the characteristics of the team to enhance the competitiveness of the entire team. The coach's leadership behavior can also promote cooperation among team members and form a sense of team identity. Finally, the article emphasizes the close relationship between organizational team culture and coach leadership behavior, and explores the important impact of coach leadership behavior on team organizational culture. Research shows that a coach’s leadership behavior has a key impact on the overall effectiveness of the team, so exploring the relationship between the coach’s leadership behavior and the team’s organizational culture is of great significance for optimizing coaching practices. In summary, this article deeply explores the relationship between coaching leadership behavior and team organizational culture, providing an important reference for further optimizing coaching practice.

Dynamic game evolution complexity of new energy and fuel vehicle manufacturers under carbon cap‐and‐trade policy

AbstractConsidering customers' preferences for low‐carbon products, the paper delves into the short‐run and long‐run repetitive game involving three oligopolistic manufacturers engaged in the production of new energy vehicles (hybrid electric vehicles [HEV] and battery electric vehicles [BEV]) and conventional fuel vehicles (FV) within the framework of a carbon cap‐and‐trade policy (CaT). In the short‐run game model, this study explores the optimal decision of oligarchic manufacturers and analyzes the efficiency of the supply chain in the context of cooperation and non‐cooperation. In the long‐run repetitive scenario, the article examines the optimal decision of the manufacturer, assuming rational economic behavior aimed at maximizing individual profits within a non‐cooperation game strategy. Finally, the paper investigates the elements that influence the efficiency of the supply chain. The results reveal that (1) fuel vehicles possess greater flexibility in adjusting parameters compared to the other vehicle types; a judicious increase in manufacturers' price adjustment parameters in the stability domain is beneficial to their respective profits and enhances the overall supply chain profitability. (2) Maintaining customers' preference for low‐carbon products within a reasonable range is crucial for the mutual benefit of all manufacturers. (3) The government needs to allocate more carbon emission limits to fuel vehicle manufacturers in order to improve supply chain efficiency.

A Tripartite Game Strategy to Promote the Commercialization of Research Results: A Synergistic Development Path Between Universities, Government, and Enterprises

Purpose – The purpose of this paper is to explore the tripartite relationship between the government, universities, and enterprises in the process of improving China’s innovation index. We hope to gain an in-depth understanding of the dynamic game process among these three, and how various factors affect the way they cooperate in this process. Design/Methodology/Approach – Based on evolutionary game theory as a research tool, we constructed a tripartite evolutionary game model of universities, government, and commercial institutions, and analyzed the stability of each party's strategic choices and the relationship between the influence of each element. Findings – By simulating strategy combinations and the evolution process in different contexts, we derived the conditions for the occurrence of stable strategy combinations among universities, governments, and business organizations. Through the above study, we found that stable strategy combinations among government, universities, and enterprises are crucial in promoting the development of China’s innovation index. Research Implications – This study has important theoretical significance for understanding the dynamic relationship among government, universities, and firms, and also provides practical guidance for policy makers. Through this study, policy makers can have a clearer understanding of the needs and interests of each party, so that they can formulate more effective policies to promote the development of innovation activities.

JAHAN: A framework for procedural generation of game maps from design specifications

Procedural content generation is a field that focuses on creating game assets employing algorithmic procedures. A critical asset in many game genres is the map. Due to the sophistication of the game map development, procedural map generation has been the subject of many studies. Considering the fundamental complexity of the game maps, many of these studies try to engage human designers in the generation process to improve the output of algorithmic procedures. However, these studies have not paid adequate attention to important non-functional requirements such as generality, comprehensiveness, controllability, and adaptability to iterative development.This paper presents a procedural map generation framework that places map designers at the center of a pipeline architecture. This framework allows designers to configure different pipeline modules and specify the characteristics of their desired map. Moreover, this framework has assertion checking features that facilitate map evaluation.We demonstrate the capabilities of this framework through one running example, along with three case studies that generate maps for first-person shooter, real-time strategy, and dungeon crawler games. Furthermore, we present a user study to show the suitability of this framework in iterative development processes and demonstrate how it reduces the labor of human designers.