Class Of Games Research Articles

Variance, norms and cooperative behavior in public goods games.

This study examines the relationship between the variance of others' contributions, social norms (empirical and normative expectations), and cooperative behavior using a classic linear public goods game. The following results are observed. First, the variance of a participant's group members' contributions had a negative impact on their contributions, empirical expectations, and normative expectations. Second, deviations from the mean, whether negative or positive, were deemed less socially appropriate. Third, while there was a strong relationship between variance, social norms, and cooperative behavior, the mediating effect of social norms was found to be insignificant. Finally, there were some notable findings regarding behavior type. Although free riders and cooperators exhibited distinct behavioral patterns, their normative expectations were similar. Free riders expected others to cooperate, but their empirical expectations were significantly lower than cooperators' expectations, which were aligned with their actual contributions. These findings contribute to research on the relationship between distribution heterogeneity, social norms and cooperative behavior. Furthermore, these findings provide valuable insights into management practices.

Emerging Trends in Play-to-Earn (P2E) Games

This research aims to establish the primary drivers influencing the development and consumers’ decision-making process in web3 games—decentralized games that function according to the play-to-earn paradigm. We observe several types of micro-economies developed within five play-to-earn games and highlight four roles consumers play at any given time. Our study offers a different perspective on rational consumer behaviour in cryptocurrency-based games and paves the way to better understanding their dynamics and evolution. Results shed light on the construction of in-game economies and how individuals of a given type engage in different playing activities. Furthermore, we compare the key features of web3 games with those similar to classic online games and assess if the play-and-earn implementations represent an evolution from previous revenue models. Using our proposed methodology, researchers can compare and classify any P2E games. We conclude by establishing a set of actions that enable consumers to benefit from this new phenomenon.

Puzzle and Dragons is hard

Candy Crush Saga (CCS) is a mobile game released in 2012. Based on a specific game-play, it was proven to be NP-complete in 2014. The 15-slide puzzle is also a classic game that has been proven to be NP-complete. In 2012, a brand new ball-spinning game called Puzzle and Dragons emerged. Puzzle and Dragons (PAD) combines the three-elimination game-play of Candy Crush Saga and the 15-puzzle. This study developed a construction and proved that under certain rules, PAD can be reduced to a one-in-three positive Boolean satisfiability problem (1-3-SAT+), which also proves that PAD is NP-Hard.

Decision Making in Monopoly Using a Hybrid Deep Reinforcement Learning Approach

Abstract: This research introduces a novel approach to decision-making in the classic board game Monopoly by leveraging a hybrid deep reinforcement learning framework. Traditional methods for decision-making in Monopoly often rely on heuristic strategies or rule-based systems, which may lack adaptability and fail to capture the dynamic and complex nature of the game. In contrast, this study proposes a hybrid model that combines the strengths of deep learning and reinforcement learning to enable an agent to autonomously learn effective decision-making strategies through interactions with the Monopoly environment. The hybrid deep reinforcement learning model is designed to process and interpret the intricate game state representations, learning optimal decision policies over time. The incorporation of deep neural networks allows the model to capture complex patterns and dependencies in the data, while reinforcement learning enables the agent to iteratively improve its decision-making abilities through trial and error. The research focuses on developing a suitable reward structure and feature representation that enhances the model's ability to navigate the diverse scenarios encountered in Monopoly, ultimately aiming to achieve superior decision-making performance compared to traditional approaches.

The Excellent Symbol in Sports: Pierre de Coubertin’s Rings

Baron de Coubertin, the founder of the modern Olympic Games, made many attempts to make the games more effective and recognizable. One of these attempts is the design of the Olympic flag, because there was a need for a visual symbol. The idea of Olympism created by Coubertin aims to interlock the world with the bonds of love and friendship as a result of the unity of mind, soul and body. This ideal which also constitutes the meaning infrastructure of the rings, is coded on six different colors and five rings. It can be said that the intellectual origin of the rings is based on the institutions Coubertin was in and on some symbols and visuals he witnessed. The rings first appeared in two letters Coubertin sent to a close friend. They were then formally announced in a written declaration in 1913 and introduced at the 1914 Paris convention. The flag was first waved at a sporting event in Egypt, at a non-Olympic event. After that the usage areas of the rings expanded considerably. The Olympic Games in Antwerp in 1920 and in Paris in 1924 increased the popularity of the flag and it was used in many different places. The officialization of the flag also promoted the flag ritual over time. The attempt to associate the ring symbol with the ancient Olympic Games remained a mistake. The aim of the study is to bring to the forefront the birth and developmental stages of the world's most popular flag, the Olympic flag with five rings, along with the ideas, contradictions, and disagreements found in the literature on the subject, and to provide a clearer and more understandable chronological structure.

A Turing test of whether AI chatbots are behaviorally similar to humans

We administer a Turing test to AI chatbots. We examine how chatbots behave in a suite of classic behavioral games that are designed to elicit characteristics such as trust, fairness, risk-aversion, cooperation, etc., as well as how they respond to a traditional Big-5 psychological survey that measures personality traits. ChatGPT-4 exhibits behavioral and personality traits that are statistically indistinguishable from a random human from tens of thousands of human subjects from more than 50 countries. Chatbots also modify their behavior based on previous experience and contexts "as if" they were learning from the interactions and change their behavior in response to different framings of the same strategic situation. Their behaviors are often distinct from average and modal human behaviors, in which case they tend to behave on the more altruistic and cooperative end of the distribution. We estimate that they act as if they are maximizing an average of their own and partner's payoffs.

The strategic prize game Le Her

AbstractLe Her is a strategic two-person prize game the classic version of which uses a deck of cards. Despite its simple rules, the analysis of the game is surprisingly complex. I describe a modern variant of Le Her that is amenable to elementary analysis, yet retains and highlights all central aspects of the classical game. This elementary analysis combines naturally central concepts of calculus (partial derivatives, multidimensional optimization, double integrals, fixed and saddle points) with major probabilistic concepts (random variable, event, independence) and basic notions in decision theory (Nash equilibrium). Due to its stimulating context as a strategic prize game Le Her offers an attractive illustration and an appealing application of learning goals and curricular contents which are otherwise often perceived as remote and abstract.

Is there a nexus between pro-social behavior and well-being? Correlational evidence

AbstractIs there a connection between pro-social behavior and well-being? This question has long been of interest, with Aristotle famously suggesting a nexus between virtues and well-being. To delve into this relationship, I conducted an extensive study encompassing multiple classical economic games and nearly 100 well-being questions. My findings confirm that different patterns of pro-sociality are robustly correlated with each other. On top, I find reliable correlations between well-being and pro-social behavior, as well as certain forms of punishment. In terms of underlying explanations, I observe that pro-sociality is particularly associated with a form of long-term well-being known as eudaimonia, suggesting that pro-social behavior plays a fundamental role in people perceiving their life as meaningful.

A model of a two-level hierarchical system with cooperative behavior of lower-level elements

One of the possible generalizations to the case of many persons of the classical hierarchical Germeier game is investigated. It is assumed that the lower level players choose one of the weakly efficient points. The maximal guaranteed result of the top-level player is calculated. Two variants of formulation of the problems are considered: games with and ithoutfeedback.

QESRL: Exploring Selfish Reinforcement Learning for Repeated Quantum Games

A novel unified learning algorithm that seamlessly applies to both classical and quantum non-zero sum games is presented. Building upon the exploring selfish reinforcement learning (ESRL) framework previously proposed in the context of classical games, we extend this approach to handle quantum games with imperfect information. A comparison is made between performance and fairness among agents learning using plain QRL vs. QESRL. The latter enables agents to explore and learn periodic policy strategies in quantum games, leveraging the quantization of games to uncover fairer results. By addressing the challenges posed by the expanded strategy space in quantum games, we test the algorithm’s scalability by increasing the number of agents. Empirical evidence is provided to showcase its performance and to compare classical and quantum game scenarios. The proposed learning algorithm represents a significant step towards understanding the convergence and optimality of strategies in non-zero sum games across classical and quantum settings, bringing us closer to harnessing the potential of independent reinforcement learning and quantum computing in game theory applications.

Reinforcement learning strategies using Monte-Carlo to solve the blackjack problem

Blackjack is a classic casino game in which the player attempts to outsmart the dealer by drawing a combination of cards with face values that add up to just under or equal to 21 but are more incredible than the hand of the dealer he manages to come up with. This study considers a simplified variation of blackjack, which has a dealer and plays no active role after the first two draws. A different game regime will be modeled for everyone to ten multiples of the conventional 52-card deck. Irrespective of the number of standard decks utilized, the game is played as a randomized discrete-time process. For determining the optimum course of action in terms of policy, we teach an agent-a decision maker-to optimize across the decision space of the game, considering the procedure as a finite Markov decision chain. To choose the most effective course of action, we mainly research Monte Carlo-based reinforcement learning approaches and compare them with q-learning, dynamic programming, and temporal difference. The performance of the distinct model-free policy iteration techniques is presented in this study, framing the game as a reinforcement learning problem.

Stochastic Adaptive Linear Quadratic Differential Games

Game theory is playing more and more important roles in understanding complex systems and in investigating intelligent machines with various uncertainties. As a starting point, we consider the classical two-player zero-sum linear-quadratic stochastic differential games, but in contrast to most of the existing studies, the coefficient matrices of the systems are assumed to be unknown to both players, and consequently it is necessary to study adaptive strategies of the players, which may be termed as adaptive games and which has rarely been explored in the literature. In this paper, by introducing a suitable information structure for adaptive games, we will show that a theory can be established on adaptive strategies that are designed based on both the certainty equivalence principle and the diminishing excitation technique. Under almost the same physical structure conditions as those in the traditional known parameters case, it is shown that the closed-loop adaptive game systems will be globally stable and asymptotically reach the Nash equilibrium.

Methodology for regional industrial complex management: Architecture of an agent-based model

Industry is the backbone of the economy of developed countries and individual regions. To optimize management processes in such a complex and multi-level sector, specific economic-mathematical models and practical tools have to be developed. The paper discusses the optimal architecture of the regional industrial complex management model on a modern theoretical-methodological and instrumental (program) basis. The classical management theory, optimization theory and game theory constitute the methodology of this study. Among the research methods applied are agent-based and minimax approaches. We substantiate the use of agent-based modelling to simulate administering the regional industrial complex. The paper presents a three-tiered management architecture consisting of federal, regional and company level authorities (united by type of activity). For each level, control agents are identified and a set of indicators formed, which cover the structure of the phase vector, including its attributes, key parameters, control actions used, risks, a model of the parameters’ dynamics, and a model of the data possessed by the object. We build a hierarchical structure of administration and information relationships in the model and, based on the minimax approach, create an algorithm of agents’ efforts to select optimal control actions. The proposed architecture will allow forming a flexible toolkit for assessing industrial development scenarios and producing the best step-by-step management pattern of the regional industrial complex.

Adaptive rock-paper-scissors game enhances eco-evolutionary performance at cost of dynamic stability

The rock-paper-scissors (RPS) game is a classic model for exploring the performance of how multiple strategies interact and evolve over time. The classic RPS game assumes a fixed benefit and cost for each strategy against another one when two players meet, while its evolutionary game considers the frequency dynamics of the three strategies with each's fitness influenced by its net payoff. This may not reflect the complexity of real-world scenarios as strategies can co-adapt with each other. We introduce an adaptive RPS game that captures the dynamics of strategy densities with trait-mediated payoffs, and the adaptive dynamics of coevolving traits via incremental mutations leading to adaptively evolving payoffs. Results show that the adaptive RPS game approaches a steady state of strategy density, if any, faster than the evolutionary RPS game. The stable coexistence of all strategies in the evolutionary game can be easily destabilized in the adaptive game. Strategies that are allowed to adaptively change their traits also performed better and achieved greater strategy densities than those fixed strategies in the adaptive game. The coevolving strategies in the adaptive RPS game exhibit complex and diverse attractors in the trait space, sensitive to both initial conditions and model parameters, but exhibiting positive payoffs with greater benefits than costs. These findings highlight how adaptive games enhance strategy performance by sacrificing eco-evolutionary dynamic stability.

Promotion by KOL and Acquaintances in Differentiated Products: By the Case of Nintendo Switch

Nintendo, founded in 1889, is a Japanese company mainly engaged in the development of electronic game hardware and software and is the pioneer of the modern electronic game industry. Nintendo Corporation is headquartered in Kyoto City, Japan. Nintendo has sold more than 2 billion copies of its software worldwide, created some of the most famous characters in the history of gaming, such as Mario, and created some of the most classic games in the history of gaming, such as The Legend of Zelda.According to Pu Yamauchi, the head of the game department, it is known that Nintendo strives to be a paradise for game artists. Nintendo believes that people who develop great games should be artists, not technicians, and therefore should be given enough freedom. That's why the Switch is so innovative today. This paper mainly focuses on the analysis of Nintendo's customer characteristics and product characteristics and puts forward corresponding marketing strategies and cures.

Operating Under Stress: An Experiential Exercise to Illustrate the Sources and Consequences of Work Stress

This experiential exercise is crafted around the classic board game Operation® (Hasbro 2008). Students are instructed that they are members of an emergency room team responsible for curing their patient of their ailments. However, unlike the board game, students in roles of doctors, nurses, and chief of surgery grapple with numerous sources of work-related challenge and hindrance stressors while trying to complete their job duties. In addition, participants are intermittently exposed to various types of work and non–work-related stressors throughout the exercise that cause interruptions to job fulfillment. These various conditions serve to illuminate the sources of job stress as well as the implications of both challenge and hindrance stressors on critical workplace outcomes, such as motivation, satisfaction, and workplace performance. This experiential exercise can be expanded to incorporate several organizational behavior topics, such as justice/fairness, leadership, teamwork, and work redesign.

Videogames as Interactive Cinema - New Perspectives

The concept of interactive cinema has been explored in depth since the first incipient manifestations of (non-interactive) cinema. If our first attempts at creating interactive experiences out of narrative, linear film objects have been notoriously clunky and awkward, with the birth of videogames new attempts have been made, bringing fresh ideas and possibilities unto the table. Interactive works that include films as objects are common today. However, interactive cinema as a concept appears to have been abandoned.Cinema continues to be largely non interactive, this dimension seemingly relegated to videogames, apps and websites. We consider that some videogames can be considered interactive cinema. The Last of Us is an example that set the trend of mostly linear, narrative games. Other games have explored this model, achieving better and worse results. We propose that these games could be categorized as interactive cinema.In this paper we aim to continue an exploration of this idea - that there can be interesting, elegantly implemented creations we can name interactive cinema - distinguishing them from video games. We analyze two video games in this light, ‘Pentiment and Everything, trying to understand how they relate to, and differ from, classic cinema and the classic video game experience. We will also discuss the exhibition “Mundos Paralelos” (Parallel Worlds), on display at the the 25th edition of the Avanca Film Festival, to understand the cinematic characteristics of the artworks presented. We conclude by proposing that, perhaps, closed categories might not serve us when creating new objects, and that hybridization is beneficial, creative, and should occur.

The Intersection of Place and Game Design: The Case of Two Classic African Board Games

The Intersection of Place and Game Design: The Case of Two Classic African Board Games

An evolutionary game-theoretic analysis of the "multi-agent co-governance" system of unfair competition on internet platforms.

The increasingly prominent issue of unfair competition on Internet platforms (IPUC) severely restricts the healthy and sustainable development of the platform economy. Based on the IPUC "multi-agent co-governance" scenario, this paper introduces stochastic disturbances and continuous strategy set to improve the classical binary deterministic evolutionary game system. The results show that after considering stochastic disturbances, the positive state corresponding to the equilibrium point (1,1) is no longer stable, and the required parameter conditions are more stringent. The IPUC "multi-agent co-governance" system under stochastic disturbances exhibits specific vulnerability. In the continuous strategy set evolutionary game system, government departments and Internet platforms can flexibly make optimal decisions based on maximizing expected returns, and strategy selection has better elasticity. Regardless of the evolutionary game scenario, maintaining the participation level of NGOs and the public above a certain threshold while increasing the penalty intensity is conducive to the evolution of the game system toward the positive state. The analysis process and conclusions provide insights and guidance for the governments to design the IPUC regulatory system and frameworks.

Quantum game— “PQ” problem

This paper reviews the coin flipping problem of “PQ” in a classical two-player game, and shows that when one player adopts quantum strategy, he can beat his classical opponent and gain higher returns. By using quantitative means, the whole “PQ” problem is put under a more general and fair condition, and it is generalized and studied again from many aspects and angles. Finally, we obtain some more essential and important conclusions, and explain the conclusions and its practical significance through some practical examples. At the same time, this paper gives the definition of imperfect fair game and the definition of perfect fair game, revises the quantum coin flipping game to make the game fair, and studies a multi-round version of quantum coin flipping. Some basic conclusions of fair quantum game are obtained, and the meaning of perfectly fair game is explained in practice.