• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.2
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• pp.101-107
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• 2015

Modern football has transformed into a scientific football based on data. With this trend, various methods for tactics studies and outcome prediction have been developed on the perspective of data analysis. In this paper, we propose a structural equation model for football game. We analyze critical factors that affect to the winning of game except psychological parts and the causal relationship between latent variables and observed variables is statistically verified through the proposed structural equation model. The results show that the Passing ability and the Ball possession affect to the Attack ability, and consequently it has a positive impact on the winning of game.

• Journal of Korea Game Society
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• v.3 no.2
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• pp.24-29
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• 2003

The market of digital avatar with internet and digital technology is increasing rapidly. The users want to express any free-formed motion of their avatars in the cyber space. The user s motion capturing method as the avatar's motion can express any free-formed motion of the avatar in real-time but the methods are expensive and inconvenient. In this paper, we proposed a new method of expressing any free-formed motion of the avatar in real-time. The proposed method is an algorithm for real-time control of a 3D avatar in symmetry-formed free motion. Specially, the algorithm aims at the motion control of a 3D avatar for online dancing games. The proposed algorithm uses the skeleton character model and controls any one of two hands of the character model by a joystick with two sticks. In the symmetry-formed motion, the position and orientation of one hand can determine the position and orientation of the other hand. And the position and orientation of a hand as an end-effector can determine the pose of the arm by Inverse Kinematics. So the algorithm can control the symmetry-formed free motions of two arms by one joystick with two sticks. In the dance game, the algorithm controls the arm motion by the joystick and the other motion by the motion captured DB.

• Journal of the Korea Institute of Military Science and Technology
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• v.23 no.4
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• pp.337-345
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• 2020

The Weapon-Target Assignment(WTA) problem can be formulated as an optimization problem that minimize the threat of targets. Existing methods consider the trade-off between optimality and execution time to meet the various mission objectives. We propose a multi-agent reinforcement learning algorithm for WTA based on mean field game to solve the problem in real-time with nearly optimal accuracy. Mean field game is a recent method introduced to relieve the curse of dimensionality in multi-agent learning algorithm. In addition, previous reinforcement learning models for WTA generally do not consider weapon interference, which may be critical in real world operations. Therefore, we modify the reward function to discourage the crossing of weapon trajectories. The feasibility of the proposed method was verified through simulation of a WTA problem with multiple targets in realtime and the proposed algorithm can assign the weapons to all targets without crossing trajectories of weapons.

• Journal of Digital Convergence
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• v.19 no.12
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• pp.435-441
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• 2021

In recent years, with thedevelopment of digital media technology immersive experiential exhibitions that provide realistic and realistic exhibition experiences to the audience are increasing In this study, the representative cases of these immersiveexperiential exhibitions were analyzed with a focus on the elements of the exhibition design. We also introduced the exhibition case of 'A Hero's Adventure' which was held and operated by applying game design elements to thethe directing planning of an immersive experience exhibition. In addition, the effects and utilization methods of the exhibition that applied game planning elements such as challenges goals conflicts rules and wins and losses were considered.

• Journal of Information Processing Systems
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• v.17 no.5
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• pp.879-891
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• 2021

With improvements in living conditions, an increasing number of people are choosing to spend their time traveling. Comfortable tour routes are affected by the season, time, and other local factors. In this paper, the influencing factors and principles of scenic spots are analyzed, a model used to find the available routes is built, and a multi-route choice model based on a game theory utilizing a path recommendation weight is developed. A Monte Carlo analysis of a tourist route subjected to fixed access point conditions is applied to account for uncertainties such as the season, start time, end time, stay time, number of scenic spots, destination, and start point. We use the Dijkstra method to obtain multiple path plans and calculate the path evaluation score using the Monte Carlo method. Finally, according to the user preference in the input path, game theory generates path ordering for user choice. The proposed approach achieves a state-of-the-art performance at the pseudo-imperial palace. Compared with other methods, the proposed method can avoid congestion and reduce the time cost.

• Journal of Korea Game Society
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• v.19 no.3
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• pp.5-14
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• 2019

The gaming server is based on a distributed server. In order to distribute workloads of gaming servers, distributed gaming servers apply some algorithms which divide each of gaming server's workload into balanced workload among the gaming servers and as a result, efficiently manage response time and fusibility of server requested by the clients. In this paper, we propose a load balancing agent using PPO(Proximal Policy Optimization) which is one of the methods from a greedy algorithm and Policy Gradient which is from Reinforcement Learning. The proposed load balancing agent is compared with the previous researches based on the simulation.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.119-138
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• 2019

Digital interactives in museums are expanding and user experience is becoming the focus of exhibition design. The purpose of this study was to suggest guidelines for serious games as a part of museum exhibits. To achieve this, studies on museum education, public space HCI, serious games, and universal design were analyzed by using content analysis methods. Results included 16 quality standards from cognitive, physical, and personal/social models. The findings from this study could benefit the design of future museum gaming interactives.

• Journal of Korea Game Society
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• v.19 no.2
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• pp.23-32
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• 2019

The popularization of VR content is slow. It's because they have not created a new visual experience, that is, 'utility' beyond 'interest'. The utility of VR content starts from functional reality. And to enhanced it, realistic interaction is required. Specifically, this study presents three methods of network play, character artificial intelligence, and Haptic implementation. In order to confirm the hypothesis, we conducted all phases of VR content production from baseball to contents production, play test, and technical verification. Through the test of the user and the evaluation institution about the final product, it was evaluated that it contributed to the realization of the content realism through the realistic visual effect, the play presentation, and the impact evaluation by the vibration.

• Smart Media Journal
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• v.12 no.9
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• pp.116-123
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• 2023

In this study, I will describe the difference in operating methods centered on the game operating system between beginners and expert groups in MORPG PC games and focus on the methodology to analyze them. First of all, a hypothesis was established to distinguish between beginners and expert groups based on the manipulation system of character movements commonly used in MORPG, and through this distinction, it was analyzed whether finger movement data and key stroke data related to the manipulation system can be significantly used in the future. Based on these analysis results, it was found that the analysis methodology that combines finger motion data and key stroke analysis is meaningful as a user test methodology for the PC MORPG game operating system in the future.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.45-51
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• 2020

Recently, many games provide data related to the users' game play, and there have been a few studies that predict opponent move by combining machine learning methods. This study predicts opponent move using match data of a real-time strategy game named ClashRoyale and a multi-label classification based on machine learning. In the initial experiment, binary card properties, binary card coordinates, and normalized time information are input, and card type and card coordinates are predicted using random forest and multi-layer perceptron. Subsequently, experiments were conducted sequentially using the next three data preprocessing methods. First, some property information of the input data were transformed. Next, input data were converted to nested form considering the consecutive card input system. Finally, input data were predicted by dividing into the early and the latter according to the normalized time information. As a result, the best preprocessing step was shown about 2.6% improvement in card type and about 1.8% improvement in card coordinates when nested data divided into the early.