• Journal of Korea Game Society
• /
• v.19 no.6
• /
• pp.61-70
• /
• 2019

In this paper, we apply reinforcement learning in the field of management simulation game to check whether game agents achieve autonomously given goal. In this system, we apply PPO (Proximal Policy Optimization) algorithm in the Unity Machine Learning (ML) Agent environment and the game agent is designed to automatically find a way to play. Five game scenario simulation experiments were conducted to verify their usefulness. As a result, it was confirmed that the game agent achieves the goal through learning despite the change of environment variables in the game.

• The Journal of Korean Association of Computer Education
• /
• v.10 no.2
• /
• pp.65-75
• /
• 2007

SCORM is an implementation reference model and also a de-facto standard technology designed for developing e-learning contents and systems effectively. For recent years, as many researchers have been more interested than ever in game based learning, ADL as a SCORM developer, has initiated a basic research on game based learning. However, the game based learning research of ADL has been performed conceptually as well as separately from SCORM so that it lacks in efforts for developing a game based learning SCORM content by incorporating concrete game data into SCORM data model. In this paper, we first present a method for applying game data elements to SCORM data Model, and then illustrate a game based learning SCORM content developed by our method.

• Journal of Digital Contents Society
• /
• v.10 no.1
• /
• pp.45-54
• /
• 2009

This paper proposes object-oriented learning method of using reverse-engineering based on game development environment. The game has advantages such as interest and enjoyment. Also, the reverse analysis of game help us understand the technique to be used in game. Through this process, we introduce learning method enabling us to actively understand object-oriented concept. Thus, the proposed method describes case learning based on XNA game development environment, and presents a scenario according to role of teacher and learner.

• International Journal of Internet, Broadcasting and Communication
• /
• v.16 no.2
• /
• pp.267-277
• /
• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.

• Journal of Information Processing Systems
• /
• v.16 no.5
• /
• pp.1074-1082
• /
• 2020

Recently, research has been actively conducted to create artificial intelligence agents that learn games through reinforcement learning. There are several factors that determine performance when the agent learns a game, but using any of the activation functions is also an important factor. This paper compares and evaluates which activation function gets the best results if the agent learns the game through reinforcement learning in the 2D racing game environment. We built the agent using a reinforcement learning algorithm and a neural network. We evaluated the activation functions in the network by switching them together. We measured the reward, the output of the advantage function, and the output of the loss function while training and testing. As a result of performance evaluation, we found out the best activation function for the agent to learn the game. The difference between the best and the worst was 35.4%.

• Journal of the Korean Chemical Society
• /
• v.62 no.2
• /
• pp.159-165
• /
• 2018

For the first time, the spot the differences (STD) game was employed in the teaching of basic organic chemistry course. Three sets of paired pictures associated with selected topics in organic chemistry were presented to the students and they were required to spot the differences between the two pictures. Based on the students' pre and post self-assessment, the STD game resulted in several positive learning outcomes as indicated in the students' reflective writing, including knowledge recall, deeper understanding of a subject, enhanced analytical skill, motivation and fun-filled learning, learning from peers and self-empowerment in learning. The STD game is a desirable teaching and learning tool, as learning in an entertaining and interactive way is highly sought after in today's classroom, especially to novice students. In the future, the STD game can be modified and implemented to cater the needs of different courses and topics.

• Journal of Korea Game Society
• /
• v.10 no.1
• /
• pp.105-113
• /
• 2010

It takes quite amount of time to study a board game because there are many game characters and different stages are exist for board games. Also, the opponent is not just a single character that means it is not one on one game, but group vs. group. That is why strategy is needed, and therefore applying optimum learning is a must. If there were equal result that both are considered to be best ones during the course of learning stage, Heuristic which utilizes learning of problem area of Jul-Gonu was used to improve the speed of learning. To compare a normal character to an improved one, a jul-gonu game was created, and then they fought against each other. Improved character considered distance and attacked other one. As a result, improved character's ability was improved on learning speed.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.20 no.1
• /
• pp.59-74
• /
• 2024

In order to improve safety consciousness due to the increase in disasters and safety accidents, safety education is necessary to prepare for disasters with interest in safety. This study is a board game design for disaster safety education for elementary school students based on Keller's learning motivation theory. By considering the school safety curriculum and the safety education contents of the School Safety Mutual Aid Association and the Ministry of Public Administration and Security, the content and goals of learning were derived and the order of learning was determined. When designing game content, the fun elements of the game were applied to Keller's learning motivation inducing factors such as attention concentration (A), relevance (R), confidence (C), satisfaction (S), and educational game design elements to induce the achievement of learning goals at the game planning stage. It is expected that the existing safety education focusing on lecture-style and audiovisual will be supplemented and used in the educational field.

• Journal of Korea Game Society
• /
• v.12 no.1
• /
• pp.113-122
• /
• 2012

This study is focused on the effect and satisfaction of Education of Music Appreciation by utilizing music game. In order to come up with the result, the study has conducted an experimental comparison using 107 male and female 4th grade students at G-elementary school in Gyeonggi-do. As a result, the class that teaches with the game has relatively higher learning assessment, study involvement and in particular, has a significantly increased satisfaction level than the class that only uses music appreciation. In addition, it analyzes that study involvement and satisfaction has an effect on learning assessment. The results of this research deemed to contribute direction of planning on learning contents by applying Smart Devices in regular school classes.

• Journal of Korea Game Society
• /
• v.11 no.3
• /
• pp.3-8
• /
• 2011

The learning by computer games, is in the spotlight as an effective education method for the game generation. The educational games need to provide additionally an omniscient view of the learning as an objective viewpoint for storytelling of learning. The omniscient viewpoint needs good readability in real-time, and to provide systematically overall and detailed informations of learning. In this paper, we propose the visual learning map as the omniscient view for storytelling of learning. The proposed learning map is composed of the district map, the topic map, and the progress map for the omniscient view of the learning. The proposed learning map is represented by several visual diagrams for real-time readability. The proposed learning map can apply to all the educational games which provide the game minimaps.