Intelligent Game Research Articles

Examining Gender Disparities In Adolescent Online Gaming Addiction

This study examines the disparities between gender and online gaming addiction among adolescents. Adolescence is a period of significant change between childhood and adulthood, typically occurring between 10 and 19 years of age (WHO,2024).The sample of this study’s respondents is between 14 and 16 years. The study population comprised 460 adolescents using a simple random sampling method. The samples were drawn from 210 adolescents comprising 93 females (44.5per cent) and 116 males (55.5per cent). The self-prepared questionnaire will be used to collect the sociodemographic data of the respondents, and the 7-item shorter version of the Gaming Addiction Scale (Lemmens et al., 2011)will be used to collect the level of online gaming addiction among adolescents. The results indicate that there is no longer a gender gap in adolescent online gaming and that gender differences are largely influenced by game type and hourly spending. Also, The discoveries uncover that in opposition to normal discernments, there is no critical orientation hole in the degrees of web-based gaming dependence among the youths examined. In any case, the outcomes demonstrate prominent contrasts in the kinds of games played and how much time is spent gaming between sexual orientations. Guys are figured out to spend greater opportunity playing and favor more cutthroat and system-based games, while females lean towards less tedious and socially intelligent games. These bits of knowledge highlight the intricacy of gaming conduct and challenge the customary comprehension of gaming compulsion as consistently influencing people to pay little mind to orientation.

UTILIZAÇÃO DA INTELIGÊNCIA ARTIFICIAL (IA) NO JOGO ELETRÔNICO “NO MAN`S SKY”

The objective of this work is to present the use of artificial intelligence in electronic games. A bibliographical research was conducted, and basic concepts, the evolution of its use, the main types of artificial intelligence, and future challenges in the use of this technology in electronic games were presented. To narrow the scope of the content, the main object of analysis was the game "No Man's Sky", which is known for being one of the electronic games that utilizes artificial intelligence in a very specific way.

Editorial: Applications of Artificial Intelligence and Machine Learning in Games

Recent developments in AI and machine learning technologies have significantly expanded their application area in games [...]

Research on the Development of Intelligent Game Dialogue System and Game Experience Based on ChatGPT

Research on the Development of Intelligent Game Dialogue System and Game Experience Based on ChatGPT

Examining the pre-service science teachers views on intelligence games used in science teaching

Examining the pre-service science teachers views on intelligence games used in science teaching

An effective DDoS attack mitigation strategy for IoT using an optimization-based adaptive security model

The Internet of Things enables the creation of transmitted use cases for interconnected devices and complementary channels. The varied structure of it creates additional security needs and problems. In particular, the safeguards used in the IoT should adjust to the changing environment. One of the major dangers to the World Wide Web (WWW) things is Distributed Denial of Service (DDoS). Therefore, in this work, an intelligent Game Theory-based Adaptive security (GT-AS) mathematical model was developed to maximize the effectiveness of DDoS attack mitigation. Moreover, this strategy can strongly derive the five parameters such as energy channel, memory, intruder, and hybrid. These all can achieve a stronger defense posture against DDoS attacks from the newly designed IoT. Consequently, the Recurrent Bat (RB) framework is developed to classify the nodes into two classes such as trusted node and malicious node. In addition, the proposed frameworks analyze how protection effectiveness and energy consumption interact when evaluating adaptive security techniques. To analyze the effectiveness of the suggested paradigm, researchers also give the outcomes of simulation experiments. Researchers demonstrate that, in comparison to existing models, the developed approach has increased the lifespan of the connected objects by 47 %. Also, the developed strategy has attained better accuracy and lower error rates when comparing traditional strategies. Moreover, the packet delivery ratio is 60 KB, energy consumption is 116 KJ, Mean Location Error is 0.078 and resource usage is 148.

The Effect of Intelligence Games on Primary School 4th Grade Students' Mental Skill Levels

This research was aimed to analyze the effects of intelligence games on the mental skill levels of fourth grade students. The research was carried out in a public school located in Manavgat district of Antalya province. The study group of the research consists of 40 volunteer students (20 in the experimental group, 20 in the control group) studying in two different branches of the 4th grades in the spring term of the 2021-2022 academic year. The research was designed in the form of a pre-test and post-test control group and the quantitative data of the research were collected through the 'Mental Skill Assessment Test' developed by Marangoz (2018). The experimental group was given a total of 16 hours of intelligence games training for eight weeks, two lessons per week (80 minutes). In the research, a valid and reliable ready-made test developed by Marangoz (2018) (Mental Skill Assessment Test) was used to evaluate students' mental skill levels (concentration of attention, strategic thinking, analysing, part-whole relationship, visual perception and use of clues). This test was applied to the experimental and control groups as a pre-test and post-test. The Normality Test was conducted to investigate the normal distribution of the data as a result of the research. In the research, 6 different intelligence games were used for eight weeks. In order to examine the relationship between the pre-test and post-test scores of the experimental and control groups before the application, the dependent sample t-test was performed. In the research, it was observed that there was a significant increase in the mental skills of the experimental group students, who were played 6 different intelligence games for eight weeks. According to the results of the research, we can say that intelligence games improve the mental skills levels of students.

The Effect of Intelligence Games on 5th Grade Students' Mathematics Attitudes and Academic Achievement

The Effect of Intelligence Games on 5th Grade Students' Mathematics Attitudes and Academic Achievement

The use of artificial intelligence in games : based on the perspective of service players and ethical principles

The use of artificial intelligence in games : based on the perspective of service players and ethical principles

The application of reinforcement learning algorithms in intelligent games

The ongoing advancement of computer hardware has spurred the need for high-quality gaming experiences. The pressing need for intelligent games, the proven efficacy of reinforcement learning in various fields, the advancement of deep reinforcement learning technology, and the desire for customized gaming experiences collectively propel the ongoing exploration and implementation of reinforcement learning in intelligent games.This study use algorithms sourced from the literature review to examine multiple facets of reinforcement learning, including the modeling of game settings, reward design, the utilization of deep learning approaches, and adversarial learning. The utilization of reinforcement learning in intelligent games holds immense importance. Initially, it enhances the gaming encounter and renders intelligent games more demanding and tailored. Furthermore, the game gains complexity and intrigue by the implementation of intelligent adversaries capable of assimilating and adjusting to the player's tactics. This not only fosters the advancement of AI technology through research and development, but also broadens the utilization of reinforcement learning in other domains, like autonomous driving and smart manufacturing. Furthermore, tailored encounters, cutting-edge game design, and utilization in schooling are likewise significant contributions, rendering reinforcement learning a pivotal element in propelling technological advancement and augmenting user experience.

A review of artificial intelligence in video games: From preset scripts to self-learning

It is now the 21st century, with the progressive development of various science and technology, such as artificial intelligence, big data, and so on, and these ever-evolving technologies have also greatly contributed to the development of today's flourishing video game field. This paper focuses on the development of artificial intelligence applications in video games over the past two decades, from preset scripts to self-learning processes, and adopts the research method of literature review. The paper concludes that the shift from pre-scripted to self-learning AI marks a shift in video games from experiences with clear rules and controlled processes to complex, dynamic, personalized experiences. This shift brings not only new opportunities but also new challenges. In the future, we can expect to see more research and practice to explore and take advantage of more of the possibilities of self-learning AI in video games.

Attitudes of University Students Towards Intelligence Games Ardahan University Sample

It is thought that the attitudes of students studying at universities towards intelligence games will contribute to digitalization and innovation processes. The aim of the current research is to examine the attitudes of university students towards intelligence games in terms of some variables. The descriptive survey model, which is a quantitative research method, was used in the research. The study group of the research consists of students from the Child Development Program, Medical Documentation and Secretarial Department, Hair Care and Beauty Services Program, Elderly Care Program, Medical Laboratory Techniques Program and Medical Imaging Techniques Program at Ardahan University. ‘Attitude Scale Towards Intelligence Games’ was used as a data collection tool in the research. Data were analyzed with the SPSS 21.0 package program. Based on the results of the 'test of normality' conducted in the data analysis, it was determined that university students showed a normal distribution in the context of age, gender, department and department-based class variables in which their attitudes towards intelligence games were examined; however, they did not show a normal distribution in the context of class and previous education variables for intelligence games. According to the data obtained from the research findings, female students have higher attitudes towards intelligence games at a level that will make a significant difference compared to male students.

The application of artificial intelligence in MOBA games

With the development of science and technology, artificial intelligence (AI) has developed rapidly and made great progress in various fields, and its application in the field of electronic games has also continued to expand. Currently, front-end companies in all major gaming fields are trying to apply AI technology to games. This article will review some specific application projects of artificial intelligence in Multiplayer Online Battle Arena (MOBA) games, and explore its application, impact and future development direction in games. The paper found that AI can currently adapt well to the game development rhythm of MOBA games, helping developers solve many problems related to game design or enhance the fun of the game, such as: using AI to improve the intelligence of intelligent non-player characters (NPCs), helping to adjust and improve Game balance and adaptability, as well as helping to predict game results and improve players' gaming experience. In the future, AI will not only be further used in MOBA games, but many games will also apply AI to games to achieve game development and market competitiveness.

Integrating Biofeedback and Artificial Intelligence into eXtended Reality Training Scenarios: A Systematic Literature Review

Background The addition of biofeedback and artificial intelligence (AI) in simulation training and serious games has shown promising results in improving the effectiveness of training and can lead to increased engagement, motivation, and retention of information. This systematic literature review explores the integration of biofeedback and artificial intelligence into eXtended reality (XR) training scenarios and is the first review to provide a consolidated overview of applied biofeedback and AI technologies in this area. Method This review was conducted using keywords related to biofeedback, AI, XR, and training and included papers that: contained the use of biofeedback and AI in XR training scenarios; reported on at least one outcome related to training effectiveness; were published in English; were peer-reviewed; date from 1 January 2016 – 7 February 2022. Results The results indicate that many studies collect two or more biosignals using a single biosensing device. This is particularly relevant in applied settings, where ease of use and minimal interference in training/education activities is desired. Also, that light, portable devices such as wrist bands, wireless straps, or headbands are preferred. Additionally, eye tracking, electrodermal activity (EDA), and photoplethysmograms (PPG) present as particularly useful biomarkers of stress and/or cognitive load in XR training contexts. A wide variety of machine learning (ML) approaches were used to support biofeedback systems in XR environments. However, a limited number of studies employed real-time analysis of biosignals (just 1% of studies) which indicates current challenges in implementing such systems. Conclusion The majority of papers meeting the selection criteria were from the fields of education and healthcare. Further research in other domains, such as defense and general industry, is needed to gain a comprehensive understanding of the potential for biofeedback and AI integration in XR training scenarios used in these domains.

Multiattribute Decision-Making in Wargames Leveraging the Entropy–Weight Method in Conjunction With Deep Reinforcement Learning

With the development of society, intelligent games have gradually become a hot research field. The paper proposes an algorithm that combines the multi-attribute decision-making and reinforcement learning methods to apply to multi-agents' decision-making for wargaming AI (artificial intelligence). This algorithm solves the problem of the agent's low rate of winning against specific rules and its inability to quickly converge during intelligent wargame training. At the same time, a multi-attribute decision-making method based on Entropy-Weight method was proposed to obtain the normalized weighting for each attribute that feeds into a deep reinforcement learning model. A simulation experiment confirms that the RNM-PPO (Real Number Multi-attribute decision-making-PPO) algorithm of multi-attribute decision-making combined with reinforcement learning presented in the paper is significantly more intelligent than the pure reinforcement learning algorithm.

Advancements in Artificial Intelligence for Games

Abstract: Interactive entertainments using AI have become possible due to merging AI with games. The paper explores in-depth multi-dimensional relations among AI in gaming, including Game AI, Adaptive Gameplay, and ML in VE. The study intends to investigate how the current AI in games landscape impacts gameplay dynamics and customer experience. The paper discusses the latest approaches such as AI-driven NPCs and procedural generation of content that transforms gameplay experience. Secondly, it analyzes how machine-learning can help in designing adaptable gaming situations to satisfy different tastes and skills players. Further, this study identifies trends and envisages future breakthroughs in AI in gaming. This work aims at addressing challenges and ethical issues associated with artificial intelligence and virtual environment domain in order to understand where is future heading for gaming experience.

Study on Multisensory Information Fusion and Interaction Techniques in Experience Design and Optimization of Intelligent Game Systems

Study on Multisensory Information Fusion and Interaction Techniques in Experience Design and Optimization of Intelligent Game Systems

The application of artificial intelligence in the game field

With the rapid development of artificial intelligence technology, its application in the field of games is increasingly widespread. At present, the application of artificial intelligence in games has become a research hotspot. This article mainly explores the application of AI in various types of games such as first person shooter (FPS), Role playing Games (RPGs), Strategy, and analyzes their advantages and disadvantages based on the category of the game. Specifically, this article explores the application of AI in FPS games, focusing on how AI controls the behavior and strategies of enemies to provide players with challenging and realistic experiences. In the context of RPGs, the paper analyzes AI's impact on intelligent decision-making and interaction with non-playable characters (NPCs). Intelligent NPCs create a more authentic and immersive interaction between players and game characters. In the case of strategy games, AI enhances the strategic and challenging aspects, offering a more layered and dynamic gaming experience, and pushing players' decision-making abilities and strategic thinking. Additionally, the article discusses the limitations and challenges of AI in games. This paper summarizes and prospects the application of AI in the field of games.

Analysis of the influence of artificial intelligence technology on the immersion of game players

Since the application of artificial intelligence in games, a variety of different games have come out, and more and more people consume their rest time by playing games as entertainment. This paper mainly studies the influence of artificial intelligence technology on the immersion of game players and its reflection on the development of games. The purpose of the research is to prove how artificial intelligence technology has an impact on the immersion of game players and what aspects of the game. Mainly through the analysis of the relationship between artificial intelligence and game development, peoples views on the application of artificial intelligence in games and feedback to study. This paper finds that artificial intelligence technology has a very positive and positive impact on the immersion of game players and still has a profound impact on the future development of games.

Метод оптимизации организационной структуры централизованных многоагентных систем в автоматическом режиме

The organizational structure of a multi-agent system (MAS) is a set of roles and relationships of agents, com-ponents that control their behavior, as well as rules governing the interaction of system elements. The effectiveness of the MAS largely depends on the characteristics of the organizational structure used. Existing solutions in this area have a significant disadvantage, namely low adaptability to changes in environmental parameters or adjustment of the conditions of the task, which consists in the need to restart the procedure for synthesizing the organizational structure of the MAS. The problem of automatic optimization of the organizational structure of centralized MAS in the conditions of changed environmental parameters or the task is of particular relevance for centralized MAS with a strict hierarchical structure, whose agents can be divided into two classes – agents-managers, agents-subordinates. The subject of the study is the methods of synthesis of the organizational structure of the MAS. The aim of the work is to develop a method for optimizing the organizational structure of centralized MAS in automatic mode. To achieve this goal, the concepts of primary and secondary agent resources were introduced, based on a biogeographic algorithm, a method was developed that regulates the movement of subordinate agents between groups depending on the degree of attractiveness of the agent manager (depends on the sum of estimates of the effectiveness of subordinate agents managed by him, as well as on the distance from this subordinate agent). The developed method can find its practical application in the implementation of the following tasks: inspection or patrolling (protection) of infrastructure facilities by mobile robots, the implementation of artificial intelligence in computer games.