• Korean Journal of Artificial Intelligence
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• v.9 no.2
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• pp.35-40
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• 2021

In this paper, many game companies seek better optimization and easy-to-apply logic to prolong the game's lifespan and provide a better game environment for users. Therefore, research will be showing the game's key input response method called RoS (Response of Speed). The purpose of the method is to simultaneously perform various motions with the character showing natural motion without errors even if the character's control key is duplicated. This method is for the developers so they can reduce bugs and development time in future game development. To be used with quickly generating game environments, the new method compares with the popular motion method, so which method is faster and can adapt to diverse games. The paper suggested that the Response of Speed method is a better method for optimizing frames and reducing the number of reacting seconds by showing a faster response and speed). With the method popularity of scrollers, many 2D cross-scroll games follow the formula of Dash, Shoot, Walk, Stay, and Crouch. With the development of game engines, it is becoming easier to implement them. Therefore, although the method presented in the above paper differs from the popular method, it is expected that there will be no great difficulty in applying it to the game because transplantation is easy. In the future, we plan to study to minimize the delay of each connection of the character motion so that the game can be optimized to best.

• Journal of Information Processing Systems
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• v.7 no.3
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• pp.531-542
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• 2011

In this paper, we propose a new congestion control scheme for high-speed networks. The basic idea of our proposed scheme is to adopt a game theory called, "Minority Game" (MG), to realize a selective reduction of the transmission speed of senders. More concretely, upon detecting any congestion, the scheme starts a game among all senders who are participating in the communication. The losers of the game reduce the transmission speed by a multiplicative factor. MG is a game that has recently attracted considerable attention, and it is known to have a remarkable property so that the number of winners converges to a half the number of players in spite of the selfish behavior of the players to increase its own profit. By using this property of MG, we can realize a fair reduction of the transmission speed, which is more efficient than the previous schemes in which all senders uniformly reduce their transmission speed. The effect of the proposed scheme is evaluated by simulation. The result of simulations indicates that the proposed scheme certainly realizes a selective reduction of the transmission speed. It is sufficiently fair compared to other simple randomized schemes and is sufficiently efficient compared to other conventional schemes.

• Journal of Korea Game Society
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• v.18 no.4
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• pp.99-106
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• 2018

Board games have many game characters and many state spaces. Therefore, games must be long learning. This paper used reinforcement learning algorithm. But, there is weakness with reinforcement learning. At the beginning of learning, reinforcement learning has the drawback of slow learning speed. Therefore, we tried to improve the learning speed by using the heuristic using the knowledge of the problem domain considering the game tree when there is the same best value during learning. In order to compare the existing character the improved one. I produced a board game. So I compete with one-sided attacking character. Improved character attacked the opponent's one considering the game tree. As a result of experiment, improved character's capability was improved on learning speed.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.109-116
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• 2017

It takes quite amount of time to study a board game because there are many game characters and many state spaces are exist for board games. Therefore, game must do learning long. But, there is weakness with reinforcement learning. On Learning early, the learning speed becomes slow. 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 board game was created, and then they fought against each other. As a result, improved character's ability was improved on learning speed.

• Journal of Korea Game Society
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• v.10 no.1
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• pp.105-113
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• 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 Game Society
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• v.20 no.6
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• pp.23-30
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• 2020

There are many cases in the game. So, Game have to learn a lot. This paper uses reinforcement learning to improve the learning speed. However, because reinforcement learning has many cases, it slows down early in learning. So, the speed of learning was improved by using the minimax algorithm. In order to compare the improved performance, a Gonu game was produced and tested. As for the experimental results, the win rate was high, but the result of a tie occurred. The game tree was further explored using progressive deepening to reduce tie cases and win rate has improved by about 75%.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.337-339
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• 2020

Speed-run is a gameplay style in what the player tries to finish the game as quickly as possible. The purpose of this study is to observe and analyze the difference between a normal player and a speed runner in a speed run to better understand their interaction with the game and to extrapolate the applications of the analyzed frameworks to scenarios that extent normal gameplay. For this purpose, MDA (Mechanic, Dynamic, Aesthetics) and DPE (Experience, Design, Play) were used. As a result, the average player was found to focus on aesthetics or affects while the speed runner focused on mechanics and gameplay.

• Journal of Internet Computing and Services
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• v.11 no.3
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• pp.25-32
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• 2010

It takes quite amount of time to study a game because there are many game characters and different stages are exist for games. This paper used reinforcement learning algorithm for characters to learn, and so they can move intelligently. On learning early, the learning speed becomes slow. Improved sequential prediction method was used to improve the speed of learning. To compare a normal learning to an improved one, a game was created. As a result, improved character‘s ability was improved 30% on learning speed.

• Journal of the Korean Home Economics Association
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• v.42 no.10 s.200
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• pp.79-89
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• 2004

This study was designed to investigated children's spatial cognitive skills as based on their practice with computer games. The sixty children were divided into 3 groups there were twenty children in experimental group 1 (the geometric game experimental group), twenty children in experimental group 2 (the arcade game experimental group), and twenty children in the control group. The sSpatial cognitive skills of the children were assessed according to by visual speed, mental rotation, and spatial visualization tasks. The rResults showed that computer game practice enhanced the children's spatial skills (visual speed, mental rotation and, spatial visualization). The c Children's mental rotation and spatial visualization showed a significant difference with the type of computer game.

• Journal of the Korea Society of Computer and Information
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• v.22 no.9
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• pp.73-80
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• 2017

In this paper, we design and implement a mobile game based on Kinect sensor. This game is a motion recognition maze game based on Kinect sensor using XNA Game Studio. The game consists of three stages. Each maze has different size and clear time limit. A player can move to the next stage only if the player finds the exit within a limited time. However, if the exit is not found within the time limit, the game ends. In addition, two kinds of mini games are included in the game. The first game is a fruit catch game using motion recognition tracking of the Kinect sensor, and player have to pick up a certain number of randomly falling fruits. If a player acquire a certain number of fruits at this time, the movement speed of the player is increased. However, if a player takes a skeleton that appears randomly, the movement speed will decrease. The second game is a Quiz game using the speech recognition function of the Kinect sensor, and a question from random genres of common sense, nonsense, ancient creature, capital, constellation, etc. are issued. If a player correctly answers more than 7 of 10 questions, the player gets useful items to use in finding the maze. This item is a navigator fairy that helps the player to escape the forest.