• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.1
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• pp.171-176
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• 2020

Reinforcement learning is a well-known method for training an artificial software agent for a video game. Even though many reinforcement learning algorithms have been proposed, their performance was varies depending on an application area. This paper compares the performance of the algorithms when we train our reinforcement learning agent for a 2D racing game. We defined performance metrics to analyze the results and plotted them into various graphs. As a result, we found ACER (Actor Critic with Experience Replay) achieved the best rewards than other algorithms. There was 157% gap between ACER and the worst algorithm.

• Journal of Digital Convergence
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• v.14 no.5
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• pp.403-410
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• 2016

Computer game is a result of integration of various academic areas, and the production of computer game requires knowledge and experience from various areas. This study demonstrates a game production process using Scratch. The intent was to experience the game development process and the production principle through actually building the core functions of a game using Scratch. As such, the computer game production principle was understood and it was made possible to learn more easily and more enjoyably the functions of multimedia and programming necessary for the production process. As the result, the learning of game production principles using Scratch was found to enhance the interest of the learner, and help with the understanding of game structure and learning software/programming language.

• The Journal of Korean Association of Computer Education
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• v.10 no.1
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• pp.41-53
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• 2007

Recently, there has been much research to improve immersiveness and learning achievement using the edutainment that combines learning with game. However, from the viewpoint of instructors, there has been little research to solve technical difficulties and to reduce the authoring time in tailoring a game-type learning content. Therefore, in this paper, we propose an authoring tool, which enable instructors to tailor game-type learning contents reflecting their own preferences in spite of no backgrounds of technical skills. The authoring tool proposed has key features to hide authoring handicaps and reduce authoring time by providing the overall template for customized game-type learning contents based on template concept. To evaluate the effectiveness of the authoring tool, we applied it to teachers and elementary school students. From the evaluation, the result represented that instructors can make their own learning contents without being aware of technical problems within a short time. Also, the result showed that the learning achievement degree and immersive depth of students have been significantly improved.

• Journal of Korea Game Society
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• v.11 no.3
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• pp.55-62
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• 2011

G-learning, based on online game, virtual reality activities and communities, is considered as a fresh, differentiated idea at learning which drives learners' interest and attention. The paper is to analyzed effectiveness of G-learning at the mathematics classes in elementary school. Fourth, fifth and sixth grade students in Seoul are selected as an experimental groups and their achievement scores are measured. The difference between G learning group and textbook group was significant. This result shows that G-learning has a positive effect on learning.

• ETRI Journal
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• v.45 no.4
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• pp.713-723
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• 2023

Game bots are illegal programs that facilitate account growth and goods acquisition through continuous and automatic play. Early detection is required to minimize the damage caused by evolving game bots. In this study, we propose a game bot detection method based on action time intervals (ATIs). We observe the actions of the bots in a game and identify the most frequently occurring actions. We extract the frequency, ATI average, and ATI standard deviation for each identified action, which is to used as machine learning features. Furthermore, we measure the performance using actual logs of the Aion game to verify the validity of the proposed method. The accuracy and precision of the proposed method are 97% and 100%, respectively. Results show that the game bots can be detected early because the proposed method performs well using only data from a single day, which shows similar performance with those proposed in a previous study using the same dataset. The detection performance of the model is maintained even after 2 months of training without any revision process.

• Journal of Digital Contents Society
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• v.10 no.1
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• pp.17-26
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• 2009

Recently, an interest in mobile games is increasing according to the extension of the high speed network infra and the development of mobile devices. Specially, the mobile game for learning can help to reinforce an academic performance and an interest for a brief time anytime anywhere. Thus, we propose new mobile contents named V-Killer which combines learning with a game. V-Killer is a word puzzle game which has functions of ranking and searching. The game can get feedback on your learning or progress and choose the degree of difficulty according to the ability of the user. The game lead to an interaction of user and games as sets questions by user, in addition, it is easy to operate and has a simple construction. In the paper, we implement the proposed game on the mobile and present the game.

• Journal of the Korean Operations Research and Management Science Society
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• v.39 no.4
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• pp.115-136
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• 2014

The game industry has grown steadily and the online game has become one of the most attractive game segments for its remarkable growth. Customer management in the online game industry, however, has received little attention from the academic field. The purpose of this study is to analyze the drivers of customer defection in the online game setting and suggest not only theoretical but also managerial insights into increasing customer retention rates. Prior to empirical analysis, the authors hypothesized that 3 variables of interests (Learning, Playing, Achievement) would explain the customer defection according to preceeding researches. To demonstrate these hypotheses, the authors obtained data from one of the biggest game publishers in Korea, and the empirical analysis model was developed considering context of research settings. The results of analyses provide the following insights. First, the key behavioral variables of Learning, Playing, and Achievement play substantial roles in explaining the customer defection. Next, the effects of these variables vary between customer types: novice and experienced customers. The defection decisions by novice customers are predicted by all key behavioral variables and Playing serves as the most influential indicator of the defection decisions. However, experienced customers are influenced by Playing and Achievement, while Learning has no impact on the defection decisions. Finally, the authors investigated hypothetical customer retention strategies, using the empirical results. The market outcomes indicate that the customer retention strategies work well with novice customers and it is hard-to-impossible to prevent experienced customers from defection using their behavioral data. These findings together deliver several meaningful insights to management as follow. First, the management should support customers to get involved in Learning activities at the very first stage. Second, customer's Achievement and appropriate compensation for it would work as defection barriers. Last, to optimize the outcomes of firm's marketing investments, it is better to focus on retention of novice users not experienced ones.

• The Journal of the Korea Contents Association
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• v.13 no.11
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• pp.551-561
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• 2013

The purpose of this study was firstly, to evaluate the contents of vocabulary game applications for young children's language learning. and secondly, to examine whether there is any differences between Korean and English word games in terms of the evaluation score. For this purpose, the word game applications in smart phone and tablet PC were analyzed, which included 30 Korean word games and another 30 English ones. The criteria to evaluate the contents were developed based on Children's Software Evaluation Instrument developed by CTR, the multimedia evaluation standard by Hee Sook Park, Young Joo Lee, and mobile contents evaluation standard by Soo Ui Choi. As a result, the educational value got the highest score whereas the design characteristics area got the lowest score in the whole evaluation analysis. And English word game applications mostly got higher score than Korean versions. The result of this study would suggest the way to evaluate educational game applications in use and to contribute to developing educational game contents aimed at young children's language learning.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.1-6
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• 2021

Most of the match-3 puzzle games supports automatic play using the MCTS algorithm. However, implementing reinforcement learning agents is not an easy job because it requires both the knowledge of machine learning and the way of complex interactions within the development environment. This study proposes a method in which we can easily design reinforcement learning agents and implement game play agents by applying PPO(Proximal Policy Optimization) algorithms. And we could identify the performance was increased about 44% than the conventional method. The tools we used are the Unity 3D game engine and Unity ML SDK. The experimental result shows that agents became to learn game rules and make better strategic decisions as experiments go on. On average, the puzzle gameplay agents implemented in this study played puzzle games better than normal people. It is expected that the designed agent could be used to speed up the game level design process.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.143-153
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• 2019

In order to save lives by recognizing the deteriorating changes of the patients, patient's assessment and reporting should be foundation, but this task is mainly delegated to nursing students or inexperienced nurses. A whisper game is a game in which the first person whisper selects a word, phrase or sentence and delivers it to the team member and finally confirms how many original message have changed during the transmit process. The purpose of this study was to develop a whisper game program to transmit the information of the children included in the DVD using in the pediatric advanced life support process. After four times of games, the experiences of 31 nursing students in the fourth grade were explored by analyzing the reflective journal. The results of the study showed three themes: learning motivation, metacognitive ability, and situated contextual learning. Repeated practice through a whisper game is expected to be widely used because it has been identified as a fresh and interesting learning method that enables nursing students to metacognize the process of assessing patients and conveying information in the contextual situation.