game theroy
225721182
Game theory based models in green supply chain management: a review of the literature
This paper provides a systematic review and analysis of the game theroy based research in Green Supply Chains Management (GSCM) Based on a rigorous content analysis of 108 papers carefully selected from the literature, we present a detailed picture of the current state of this research and point to the promising future directions. Our analysis shows a rapid increase in the number of publications during the last three years, with an imbalance in the contribution of the publishing outlets, as nearly two third of the reviewed papers are published by only four journals. Results also show the dominance of deterministic static models and simple two level SC structures. Developing stochastic models, considering the risk and the evolutionary nature that inherently characterise the business environment and investigating more complex multi level SC structures are among the promising future research opportunities.
Maher A N Agi Sohrab Faramarzi-Oghani Oncu Hazir
37941741
Deep Learning for Video Game Playing
In this paper, we review recent deep learning advances in the context of how they have been applied to play different types of video games such as first person shooters, arcade games, and real time strategy games. We analyze the unique requirements that different game genres pose to a deep learning system and highlight important open challenges in the context of applying these machine learning methods to video games, such as general game playing, dealing with extremely large decision spaces and sparse rewards.
IEEE Transactions on Games
Niels Justesen Philip Bontrager Julian Togelius Sebastian Risi
58004680
Game theoretic modelling of infectious disease dynamics and intervention methods: a review
We review research studies which use game theory to model the decision making of individuals during an epidemic, attempting to classify the literature and identify the emerging trends in this field. The literature is classified based on (i) type of population modelling (classical or network based) (ii) frequency of the game (non repeated or repeated) and (iii) type of strategy adoption (self learning or imitation) The choice of model is shown to depend on many factors such as the immunity to the disease, the strength of immunity conferred by the vaccine, the size of population and the level of mixing therein. We highlight that while early studies used classical compartmental modelling with self learning games, in recent years, there is a substantial growth of network based modelling with imitation games. The review indicates that game theory continues to be an effective tool to model decision making by individuals with respect to intervention (vaccination or social distancing)
Journal of biological dynamics
Sheryl Chang Mahendra Piraveenan Philippa Pattison Mikhail Prokopenko
201871608
Digital game based L2 learning outcomes for primary through high school students: A systematic literature review
Abstract The aim of this systematic literature review was to examine the empirical evidence for the effectiveness of digital games on second language learning between 2014 and 2018, with a focus on participants 6 18 years old. The initial search yielded 578 results, from which a total of 26 articles were included in the final content analysis. The analysis of the included studies revealed: (1) the majority of studies were conducted with a mixed methods design; (2) most studies used computers as the gaming platform; (3) the most common game genre was educational games or educational mini games; (5) most games were designed for learning; (4) research was mainly conducted in East Asia and the Middle East; (5) the primary context of study was within a formal learning environment; and (6) the target language was usually English. Further analysis suggests that digital learning games (DLGs) may benefit players' language acquisition, affective/psychological state, contemporary competences, and participatory behavior. An inductive analysis revealed six key game features highlighted within the studies that influenced the outcomes: ease of use, challenge (at one's zone of proximal development) rewards and feedback, control or autonomy, goal orientation, and interactivity. In addition to game features, associations between context and outcomes were also explored: studies conducted within a formal learning environment, with or without teacher facilitation, resulted in mostly positive language acquisition results, meaning DLGs can be implemented successfully within schools. Based on the overall findings, it is clear that DLGs are an effective tool, but future research should explore how they can best be implemented in the classroom setting.
Comput. Educ.
Emmanuel O Acquah Heidi T Katz
125659062
Game Theory Approaches for the Solution of Power System Problems: A Comprehensive Review
Deregulation and competition appearance in electric power systems and fundamental changes in control and operation structures of such systems require a strong tool for handling such issues. Game theory approach, which is defined as an analytical concept for dealing with the decision making process in a variety of sciences, is vastly employed in power system problems. This paper provides a comprehensive review of the application of game theory approach to the solution of electric power system problems. The basic foundation of game theory approach and the basic concepts of such concept will be introduced to make the readers familiar with principals of game theory. Moreover, the introduction and a brief definition of main classifications of game theory including cooperative game, dynamic game, evolutionary game theory and strategic game will be studied. In addition, the implementation of different types of game theory approach to accomplish decision making process in power system problems will be reviewed. The main contributions of recent researches in the area of employment of game theory to power system problems are studied and discussed in details.
Saeed Abapour Morteza Nazari-Heris Behnam Mohammadi-ivatloo Mehrdad Tarafdar Hagh
125634298
A Survey on the Combined Use of Optimization Methods and Game Theory
Game theory is a field of applied mathematics that studies strategic behavior of rational factors. In other words, game theory is a collection of analytical tools that can be used to make optimal choices in interactional and decision making problems. Optimization in mathematics and computer science is the choice of the best member of an existing collection for a specific purpose. Several optimization methods have been used in many problems to minimize costs or maximize profits. From a particular point of view, it can be said that the game theory is in fact a kind of optimization. In this paper, a combined use of game theory and optimization algorithms has been reviewed and a new categorization is presented for researches which have been conducted in this area. In some of these combinations, game theory has been used to improve the performance of optimization algorithms, and in some others, optimizations methods help to solve game theory problems. Game theory and optimization algorithms are also used together to solve some other problems.
Mohammad Karim Sohrabi Hossein Azgomi
213603804
Predicting students' knowledge after playing a serious game based on learning analytics data: A case study
Peer Review The peer review history for this article is available at https:/publons.com/publon/10. 1111/jcal.12405. Abstract Serious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict knowledge change based on in game student interactions. We have tested this approach in a case study for which we have conducted preexperiments postexperiments with 227 students playing a previously validated serious game on first aid techniques. We collected student interaction data while students played, using a game learning analytics infrastructure and the standard data format Experience API for Serious Games. After data collection, we developed and tested prediction models to determine whether knowledge, given as posttest results, can be accurately predicted. Additionally, we compared models both with and without pretest information to determine the importance of previous knowledge when predicting postgame knowledge. The high accuracy of the obtained prediction models suggests that serious games can be used not only to teach but also to measure knowledge acquisition after playing. This will simplify serious games application for educational settings and especially in the classroom easing teachers' evaluation tasks.
J. Comput. Assist. Learn.
Cristina Alonso-Fernandez Ivan Martinez-Ortiz Rafael Caballero Manuel Freire-Moran Baltasar Fernandez-Manjon
211073696
The agency effect: The impact of student agency on learning, emotions, and problem solving behaviors in a game based learning environment
Abstract Game based learning environments are designed to foster high levels of student engagement and motivation during learning of complex topics. Game based learning environments allow students freedom to navigate a space to interact with game elements that foster learning, i.e. agency. Agency has been studied in learning, and it has been demonstrated that increased student agency results in greater learning outcomes. However, it is unclear what is the level of agency that is required to demonstrate this effect, and whether this effect applies only to learning or to problem solving and affect during game based learning as well. To investigate how the level of student agency impacts learning, problem solving, and affect, a study was conducted with 138 college students interacting with a game based learning environment for microbiology, Crystal Island. This study is an extension of a previous study that examined the impact of agency on learning and problem solving behaviors during game based learning with Crystal Island. Students were randomly assigned to either a High Agency condition, a Low Agency condition, or a No Agency condition. It was found that students in the Low Agency condition achieved significantly higher normalized learning gain scores than students in the No Agency condition, and marginally higher normalized learning gains than the High Agency condition. Post surveys of interest and presence indicated that students in the No Agency condition were less interested, and perceived themselves as less present in the virtual environment, than students in the other conditions. Students in the No Agency condition also experienced less frustration, confusion, and joy than the other agency conditions, indicating a less cognitively stimulating experience. Overall the results indicate that a moderate degree of agency provided to students in game based learning environments leads to better learning outcomes without sacrificing interest and without yielding a negative emotional experience, demonstrating how even low levels of agency can positively impact learning, problem solving, and affect during game based learning.
Comput. Educ.
Michelle Taub R Keith Sawyer A Smith Jonathan P Rowe Roger Azevedo James C Lester
182924152
Lack of consensus among scholars on the issue of video game "addiction"
Whether pathological video game overuse constitutes a distinct mental disorder remains an issue of controversy among scholars. Both empirical data and scholarly opinions differ regarding the status of pathological gaming and whether "addiction" is the best frame by which to understand video game use. The current study sought to examine the status of scholarly opinions in a survey of 214 scholars to examine their opinion of possible behavioral effects of games. Results indicated a variance of opinions. About 60.8% of scholars agreed pathological gaming could be a mental health problem, whereas 30.4% were skeptical. However, only 49.7% believed the DSM criteria for "internet gaming disorder" were valid, with slightly higher numbers, 56.5% supporting the World Health Organization "gaming disorder" diagnosis. More scholars worried about both the DSM and WHO criteria over pathologizing normal youth than weren't worried about this. Scholars were likewise split over whether the DSM/WHO had precipitated moral panics over video games. Belief in pathological gaming was positively predicted by hostile attitudes toward children and negatively by participants' experience with games. Overall results indicated continued significant disagreements among scholars related to pathological gaming. Claims of consensus are, at this juncture, likely premature
Christopher J Ferguson John Colwell
211170603
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI
This paper reviews the field of Game AI, which not only deals with creating agents that can play a certain game, but also with areas as diverse as creating game content automatically, game analytics, or player modelling. While Game AI was for a long time not very well recognized by the larger scientific community, it has established itself as a research area for developing and testing the most advanced forms of AI algorithms and articles covering advances in mastering video games such as StarCraft 2 and Quake III appear in the most prestigious journals. Because of the growth of the field, a single review cannot cover it completely. Therefore, we put a focus on important recent developments, including that advances in Game AI are starting to be extended to areas outside of games, such as robotics or the synthesis of chemicals. In this article, we review the algorithms and methods that have paved the way for these breakthroughs, report on the other important areas of Game AI research, and also point out exciting directions for the future of Game AI.
KI Kunstliche Intelligenz
Sebastian Risi Mike Preuss