A Paradigm Shift from Optimal Play to Mental Comfort: A Perspective from the Game Refinement Theory

The game refinement theory focuses on the game designer perspective, where its application in various types of games provides evidence of the occurring paradigm shift. Utilizing the logistical model of game outcome uncertainty, it provides a platform for incorporating gamified experience observed in games to be adopted in domains outside of game while retaining the context of the game. Making games as a testbed, the implications of the game refinement theory have been observed in the educational and business perspective, while further explored its utility in interpreting some states of the human mind. In addition, a holistic view of design in games and in the real-world environments was discussed, where the prospects of the game refinement theory were also highlighted

An Enhanced Artificial Immune System Approach For Assembly Line Balancing Problem Through Shifting Bottleneck Identification

The manufacturing industry has evolved rapidly in the past few years, due to the global competitive economy, high-quality market demands, and customized products with the lowest possible costs. This is achieved by partitioning the workloads among the available resource to obtain an equal amount of workloads in the assembly line system, which defines the assembly line balancing (ALB) problem. The most prominent ALB problem is the simple assembly line balancing (SALB) problem which has been utilized for decades to provide a basis for testing different approaches. Despite varieties of computational techniques have addressed the ALB problem, which can be categorized as exact, heuristic, and meta-heuristic approaches, little work had been done on SALB-E problem due to its difficulty of obtaining the optimal solutions. Additionally, bottlenecks can still occur during the assembly operations that affect the production quality and induce unnecessary costs. Identifying and optimizing machines with the likelihood of the next operation bottleneck had been rarely addressed in the assembly line especially when it shifts from one machine to another (called shifting bottleneck). This study propose an effective computational approach to address the SALB-E problem through the shifting bottleneck identification. A bio-inspired approach had been frequently adopted for handling complex and combinatorial optimization problem through a simple yet effective manner. As such, a computational method, known as artificial immune system (AIS) approach, had been proposed

Optimizing Crowd Evacuation In The Emergency Route Planning Problem

Situasi bencana, yang berlaku secara semula jadi (kebakaran, banjir, taufan) atau buatan manusia (contohnya pengeboman pengganas, tumpahan bahan kimia, dan lain-lain), telah meragut ribuan nyawa, mencetuskan keperluan untuk pemindahan kecemasan. Biasanya, mengoptimumkan pelan pemindahan kecemasan melibatkan berkesanan pemodelan orang ramai dan pemilihan laluan, dimana pelan yang optimum penting dalam masalah perancangan laluan kecemasan (ERP). Pelbagai pendekatan ERP telah dibangunkan dimana diklasifikasikan kepada pendekatan matematik, keputusan sokongan, heuristik, dan meta-heuristik. Ulasan kesusasteraan menyeluruh telah menunjukkan kepentingan untuk merapatkan jurang antara pemodelan dan pemilihan laluan, di mana di mana pendekatan bersepadu dan berdaya maju diperlukan. Dalam kajian ini, satu perancangan pemindahan rangka kerja bersepadu menggunakan model pemindahan orang ramai dan sistem imun (AIS) algoritma tiruan, yang dipanggil iEvaP, telah dicadangkan. iEvaP telah disahkan terhadap Lu et al. (2003) dan parameternya telah ditentukan untuk prestasi yang optimum. Disastrous situations, either natural (e.g. fires, floods, hurricane) or man-made (e.g. terrorist bombings, chemical spills, etc.), have claimed the lives of thousands, triggering the needs for emergency evacuation. Typically, optimizing an emergency evacuation plan involves both the effectiveness in crowd modelling and route selection, where an optimum evacuation plan is vital in the emergency route planning (ERP) problem. Various ERP approaches have been developed which are classified into mathematical, decision-support, heuristic, and meta-heuristic approaches. Exhaustive literature reviews have shown the significance of bridging the gap between modeling and routing, where an integrated and viable approach is needed. In this study, an integrated evacuation planning framework utilizing crowd evacuation model and an artificial immune system (AIS) algorithm, called iEvaP, was proposed. iEvaP was validated against Lu et al. (2003) and its parameters were calibrated for optimum performance

Analysis of The Attractiveness of Soccer: A Game Refinement Model and The Significance of “Antagonistic Rate”

Soccer (or association football) is now the most popular sports game in the world. Various underlying factors may explain its reasons to be popular. However, there is no underlying explanation as to why the nature of the game processes was appealing to all people of all ages. However, measuring such subjective metric were empirically challenging and costly. In this paper, a mathematical model of a soccer game is established based on the game refinement theory, where the internal processes of a soccer game are explored where interpretation based on the “antagonistic rate” is established. Based on such measures, two stages were identified in the soccer game, and various soccer leagues' data were utilized as the testbed. Further analysis of the soccer game was determined based on physics in mind measure using correspondence of Newtonian law of motions. These measures provide insights into the game stages' underlying entertainment value, as well as a new perspective on the soccer game attractiveness

Recent Developments in Game-Theory Approaches for the Detection and Defense against Advanced Persistent Threats (APTs): A Systematic Review

Cybersecurity has become a prominent issue in regard to ensuring information privacy and integrity in the internet age particularly with the rise of interconnected devices. However, advanced persistent threats (APTs) pose a significant danger to the current contemporary way of life, and effective APT detection and defense are vital. Game theory is one of the most sought-after approaches adopted against APTs, providing a framework for understanding and analyzing the strategic interactions between attackers and defenders. However, what are the most recent developments in game theory frameworks against APTs, and what approaches and contexts are applied in game theory frameworks to address APTs? In this systematic literature review, 48 articles published between 2017 and 2022 in various journals were extracted and analyzed according to PRISMA procedures and our formulated research questions. This review found that game-theory approaches have been optimized for the defensive performance of security measures and implemented to anticipate and prepare for countermeasures. Many have been designed as part of incentive-compatible and welfare-maximizing contracts and then applied to cyber–physical systems, social networks, and transportation systems, among others. The trends indicate that game theory provides the means to analyze and understand complex security scenarios based on technological advances, changes in the threat landscape, and the emergence of new trends in cyber-crime. In this study, new opportunities and challenges against APTs are outlined, such as the ways in which tactics and techniques to bypass defenses are likely to evolve in order to evade detection, and we focused on specific industries and sectors of high interest or value (e.g., healthcare, finance, critical infrastructure, and the government)

Objectivity and Subjectivity in Variation of Multiple Choice Questions: Linking the Theoretical Concepts Using Motion in Mind

Multiple-choice questions (MCQs) have been considerably used for assessing the individual’s performance in various contexts. The optimal number of options in MCQs is a debatable issue, followed by contradictions and discussions, and is needed for a firm conclusion from empirical and hypothetical findings. This study aims to link theoretical concepts, including challenge-based gamification, zone of proximal development, and prospect theory, and generate insight into educational assessment using motion-in-mind measures. Classical test theory was used to determine reliability and validity. Variations of MCQs experimented: the number of options, settings, and scoring methods. The experimental data was gathered from human and AI simulations and measured using motion-in-mind. It was found that increasing the number of options in the MCQ makes the test more challenging, explaining an increase of mass in mind $m$ . The findings also revealed that time pressure provides competitiveness while scaffolding provides support. In addition, the hybrid system demonstrates the balance of education and entertainment. Finally, the results addressed the general discussion and analogical interpretation in the education context based on physics-in-mind values. These findings can be promising for analyzing the balance between competitiveness and entertainment while enabling the learning process in the practical assessment

Application of Meta-Gaming Concept to the Publishing Platform: Analysis of the Steam Games Platform

The digital marketplace has rapidly grown, transitioning the market of video games from physical localized experiences to more networked, expanded, virtual spaces. With a highly competitive business market, platform governance policy allows for the emergence of rapidly growing publishing platforms for digital video games such as the Steam platform. This study demonstrated the importance of the meta-gaming of a platform based on the Steam platform; 18,658 Steam-listed games were acquired and analyzed from the Steam Store, Steam Spy, and Steam achievement databases. A detailed analysis was conducted where key research questions were formulated concerning the game information. This study found that digital badging (i.e., achievements) increases players’ engagement with the publishing platform with good auxiliary data (such as types, rating, releases, and prices). Based on such findings, an opportunity for a new business model is envisioned

The Dynamics of Minority versus Majority Behaviors: A Case Study of the Mafia Game

The game ‘Mafia’ is a logic puzzle that has been a top-rated party game played worldwide. Many studies have been dedicated to determining the best character combination to keep players engaged while analyzing the overall death toll. Although it has only two-sided plays, there are multiple combinations of characters in which each character’s rules are different. This paper explores the game’s sophistication using the game refinement theory and motion in mind model while measuring the entertainment of each character’s actions. It then focuses on the dynamics of minority versus majority behaviors during the game process. Computer simulations were conducted to collect the data of each character and assess the entertainment impacts. Moreover, the energy value of each character was computed based on the motion in mind model. The results show that when the number of ‘Mafia’ and the number of ‘Sheriffs’ are equal, the sophistication of each character is maximized. In addition, the data indicates the player engagement in the following order: Mafia>Sheriff>Citizen. Thus, it can be concluded that the actions of the Mafia character are the most complicated and significantly impact the game. It is expected that the results in this study enable game designers to improve each character’s perspective and examine possible enhancements from the viewpoint of entertainment

Bridging Ride and Play Comfort

The notion of comfort with respect to rides, such as roller coasters, is typically addressed from the perspective of a physical ride, where the convenience of transportation is redefined to minimize risk and maximize thrill. As a popular form of entertainment, roller coasters sit at the nexus of rides and games, providing a suitable environment to measure both mental and physical experiences of rider comfort. In this paper, the way risk and comfort affect such experiences is investigated, and the connection between play comfort and ride comfort is explored. A roller coaster ride simulation is adopted as the target environment for this research, which combines the feeling of being thrill and comfort simultaneously. At the same time, this paper also expands research on roller coaster rides while bridging the rides and games via the analogy of the law of physics, a concept currently known as motion in mind. This study’s contribution involves a roller coaster ride model, which provides an extended understanding of the relationship between physical performance and the mental experience relative to the concept of motion in mind while establishing critical criteria for a comfortable experience of both the ride and play

The Dynamics of Minority versus Majority Behaviors: A Case Study of the Mafia Game

The game ‘Mafia’ is a logic puzzle that has been a top-rated party game played worldwide. Many studies have been dedicated to determining the best character combination to keep players engaged while analyzing the overall death toll. Although it has only two-sided plays, there are multiple combinations of characters in which each character’s rules are different. This paper explores the game’s sophistication using the game refinement theory and motion in mind model while measuring the entertainment of each character’s actions. It then focuses on the dynamics of minority versus majority behaviors during the game process. Computer simulations were conducted to collect the data of each character and assess the entertainment impacts. Moreover, the energy value of each character was computed based on the motion in mind model. The results show that when the number of ‘Mafia’ and the number of ‘Sheriffs’ are equal, the sophistication of each character is maximized. In addition, the data indicates the player engagement in the following order: Mafia>Sheriff>Citizen. Thus, it can be concluded that the actions of the Mafia character are the most complicated and significantly impact the game. It is expected that the results in this study enable game designers to improve each character’s perspective and examine possible enhancements from the viewpoint of entertainment