• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.349-350
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• 2019

게임에서 장르를 불문하고 모든 몬스터와 NPC는 AI를 가지고 있다. 따라서 적 몬스터 캐릭터와 전투를 즐기는 액션 게임의 경우 그만큼 인공지능이 게임 안에서 차지하는 비율이 높다고 할 수 있을 것이다. 본 논문에서는 FSM, HFSM, BT와 같은 AI 기법을 비교하여 분석하였다. 각 기법에는 주의해야 할 점이 명확하게 존재하기 때문에 구체적으로 어떠한 문제점들이 존재하는지에 대한 결과를 얻는데 연구 목적이 있다. 따라서 몬스터 AI를 구현할 때 각 인공지능 기법의 장단점을 고려하여 설계하여 유지 보수를 줄이는 방법을 연구해야 한다는 것을 확인할 수 있었다.

• Journal of Korea Game Society
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• v.17 no.4
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• pp.63-70
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• 2017

It has been a year since the $Pok{\acute{e}}monGo$ has been released. Over the past year, the $Pok{\acute{e}}monGo$ have become a social phenomenon. This study analyzes the dual characteristics play of the original $Pok{\acute{e}}mon$ game. The Pocket Monster game, which has both casual and hardcore capabilities, has a broader player base and enjoys popularity for 20 years, satisfying the requirement of easy and convenient access, which is an advantage of casual games. In addition, the rating battle system of $Pok{\acute{e}}mon$ game turns casual play into hardcore play. In this paper, we analyze the dual play characteristics of longevity games such as Pocket Monsters, and propose strategies and directions for game development that can survive long term in the competitive game market.

• Cartoon and Animation Studies
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• s.40
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• pp.33-53
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• 2015

The movement of characters is one of the crucial elements to deliver their emotion flowing inside. Though it is the same movement, it may appear or be expressed differently according to the character's personality or emotion or the particular situation. The purpose of this study is to analyze not only the movement found superficially in an animation but also a character's internal emotion and attitude with Laban's movement analysis system, particularly effort, one of its analysis categories, and examine how effectively Laban's movement analysis often employed at the circles of dance can analyze movement in an animation. is about a monster that constantly makes efforts to realize its dream to be a scarer. Functional movement forms the most part, but expressive movement to show how a character thinks or feels also appears harmoniously. Characters' externally shown movement can express their internal emotion properly sometimes, but they also often move expressing their feelings in moderation. Therefore, this study analyzes the movement of characters found in the four scenes of with LMA's effort. According to the findings, at the scene where Michael enters the door leading to the human world following the scarer, the emotional state of Michael envious of the scarer is expressed with the Vision Drive giving the strong feel of dreaming. At the scene of the second game to choose the best scare team, it shows us the Spell Drive with its careful and light movement having clear intention to survive at the game. At the scene where there is a party held for the teams that have survived, it shows the Passion Drive of being eagerly expressing happy and delightful feelings without considering what is around. At the scene where Michael and Sullivan are pursued by people, the Action Drive was used to express movement that was heavy and strong and was getting faster gradually by focusing the feelings of the characters in haste into one place.

• Journal of Korea Game Society
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• v.9 no.5
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• pp.25-41
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• 2009

The objective of this study is to develop an analytic framework to code systematically the gamer's behaviour in MMO(Massively Multi-player Online) gameplay experience, to explore their gameplay as a problem solving procedure empirically. Previous studies about model human processor, content based protocol, and procedure based protocol are reviewed in order to build the outline of the analytic framework related to MMO gameplay. The specific gameplay actions and contents were derived by using concurrent protocol analysis method through the empirical experiment executed in MMORPG gameplay. Consequently, gameplay are divided into six actions : kinematics, perception, function, representation, simulation, and rule (heuristics, following, and transcedence). The analytic framework suitable for MMO gameplay was built. As a result of this study, we found three rule spaces in the problem solving domain of gameplay that are an heuristics, a following of the rule, and a transcendence of the rule. 'Heuristics' denotes the rule action that discovers the rule of game through trial-and-error. 'Following' indicates the rule action that follows the rule of game embedded in game by game designers. 'Transcendence' presents the rule action that transcends that. The new discovered rule spaces where 'Following' and 'Transcendence' actions occur and the gameplay pattern in them is provided with the key basis to determine the level design elements of MMO game, such as terrain feature, monster attribute, item, and skill et cetera. Therefore, this study is concludes with key implications to support game design to improve the quality of MMO game product.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.25 no.5
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• pp.1131-1141
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• 2015

In this paper, we proposed a new approach of machine learning based method for detecting game-bots from normal players in MMORPG by inspecting the player's action log data especially in-game money increasing/decreasing event log data. DBSCAN (Density Based Spatial Clustering of Applications with Noise), an one of density based clustering algorithms, is used to extract the attributes of spatial characteristics of each players such as a number of clusters, a ratio of core points, member points and noise points. Most of all, even game-bot developers know principles of this detection system, they cannot avoid the system because moving a wide area to hunt the monster is very inefficient and unproductive. As the result, game-bots show definite differences from normal players in spatial characteristics such as very low ratio, less than 5%, of noise points while normal player's ratio of noise points is high. In experiments on real action log data of MMORPG, our game-bot detection system shows a good performance with high game-bot detection accuracy.