• Knowledge Management Research
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• v.14 no.5
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• pp.151-176
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• 2013

소셜네트워크 서비스(SNS)를 사용하는 이유는 무엇일까? 게임, 정보의 검색, 시간 보내기, 단순한 반복적인 습관 등 다양한 이유가 있을 수 있겠지만, 가장 공통적인 이유는 재미(fun)이다. 그렇다면 사용자들이 SNS를 이용하면서 느끼는 재미의 개념은 무엇이며 이러한 재미는 어떻게 이루어져 있는가? 라는 의문을 갖게 된다. 재미 현상을 이해하는 것이야말로 SNS현상의 본질을 이해하는 것이 될 것이며, 향후 개발되는 SNS의 많은 부분을 보다 재미있게 만드는데 필요한 단초를 제공할 수 있다는 점에서 매우 중요하다. 이에 본 연구에서는 (1)SNS 사용자들이 어떤 종류의 재미를 느끼는지를 살펴보고, (2)재미를 구하기 위하여 어떤 행동을 하는지를 고찰하였다. 또한, (3)이러한 행동을 체계적인 설명을 위하여 SNS에서 재미를 구하는 가치 양식이 어떻게 달라지는지를 하나의 모형(재미진화모형)으로 제시하였다. 재미진화모형은 보기(seeing), 가지기(having), 하기(doing), 되기(being)4가지 단계로 이루어지며, 각 단계로 진행되면서 몰입(commitment)는 커지게 된다. 보기단계에서는 사실 모든 SNS 행동에서 사람들은 가장 먼저 "보는 것"을 통해 재미를 느낀다. 가지기(having) 단계에서는 보는 것만으로 재미를 지속하기는 어려우며, 정상적인 경우 일정기간이 지나면 그 활동의 구성요소를 소유하고 싶어한다. 하기(doing) 단계에서는 가지기의 재미는 다시 발전하여 그 활동과 직접 관련된 행동으로 나타난다. 마지막으로 되기(being) 단계에서 동일시 과정이 발전하면 보다 성숙한 형태의 재미추구 양식이 나타난다.

• Journal of Korea Game Society
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• v.6 no.4
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• pp.89-95
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• 2006

The game has both directionalities that users are to choose and act accordingly. In this regard, the game scenario goes beyond just conveying the story, and trains users and guide them in playing the Same. However, this Same scenario is huge in size and every event is linked with each other so that it was rather difficult to have it made in practice. A study proposes that a script, the minimum unit, is built into a database, and based on which, quests are made, then the resulting quests are built back into a database. Scripts are classified into text, graphic and sound type and these are positioned in accordance with the quest structure. With this method, one can re-use the existing scenarios and can overcome the negatives of irregular qualities of scenarios.

• Journal of KIISE
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• v.44 no.3
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• pp.314-322
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• 2017

In MMORPG (Massively Multiplayer Online Role-Playing Game), users advance their own characters to get to the maximum (max) level by performing given tasks in the game scenario. Although it is crucial to retain users with high levels for running online games successfully, little efforts have been paid to investigate them. In this study, by analyzing approximately 60 million in-game logs of over 50,000 users, we aimed to investigate the process through which users achieve the max level and churn of such users since the moment of achieving the max level, and determine possible indicators related to churn after the max level. Based on the result, we can predict churn of the max level users by employing behavioral patterns before the max level. Moreover, we found users who are socially active and communicate with many people before the max level are less likely to leave the service (p<0.05). This study supports that communication patterns are important factors for persistent usage of the users who achieve the max level, which has practical implications to guide elite users on enjoying online games in the long run.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.

• Journal of Korea Game Society
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• v.15 no.6
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• pp.131-140
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• 2015

The character is one of most important interest-element in role playing game genres since it shows the individuality. In general cases, game players allocate points to talent clauses that they choose. However, it is not easy to provide the suitable character-growing to players in generic system since the cases are too simple and based on just humans choices. In this paper, we propose the character growing system based on the player type inference module. Growth morphology is determined by player's behavior or type. The determination is based on petri-net. Our experimental results and analysis show that our proposed approach is suitable for character-growing system.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.412-415
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• 2005

Recently, new games have been experimented to be given the adaptive interfaces equipped with AI algorithms which could interpret the user's personality, behavioral patterns, and physiological conditions in realtime. In this paper, we propose the intermediate form of tangible interface for PC package, which is currently decaying in commercial market.

• Journal of Digital Contents Society
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• v.18 no.8
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• pp.1677-1684
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• 2017

In this paper, we tried to combine the findings obtained from pedagogical analysis of serious game, which is a study of Soo-Cheol Ha [2, 3], and learning theories such as behaviorism, cognitivism, constructivism, situated learning, and other theories. Based on the previous research, we propose pedagogical elements of serious games based on theories and researches from models and other studies using learning theory. The suggested elements were applied on GSS(Global Startup Simulation), which is a serious game, and the results were confirmed through questionnaire evaluation of learners who are learning through it.

• Annual Conference of KIPS
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• 2020.11a
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• pp.988-991
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• 2020

다양한 실세계 응용 분야들에서 공동의 목표를 위해 여러 에이전트들이 상호 유기적으로 협력할 수 있는 행동 정책을 배우는 것은 매우 중요하다. 이러한 다중 에이전트 강화 학습(MARL) 환경에서 기존의 연구들은 대부분 중앙-집중형 훈련과 분산형 실행(CTDE) 방식을 사실상 표준 프레임워크로 채택해왔다. 하지만 이러한 다중 에이전트 강화 학습 방식은 훈련 시간 동안에는 경험하지 못한 새로운 환경 변화가 실전 상황에서 끊임없이 발생할 수 있는 동적 환경에서는 효과적으로 대처하기 어렵다. 이러한 동적 환경에 효과적으로 대응하기 위해, 본 논문에서는 새로운 다중 에이전트 강화 학습 체계인 C-COMA를 제안한다. C-COMA는 에이전트들의 훈련 시간과 실행 시간을 따로 나누지 않고, 처음부터 실전 상황을 가정하고 지속적으로 에이전트들의 협력적 행동 정책을 학습해나가는 지속 학습 모델이다. 본 논문에서는 대표적인 실시간 전략게임인 StarcraftII를 토대로 동적 미니게임을 구현하고 이 환경을 이용한 다양한 실험들을 수행함으로써, 제안 모델인 C-COMA의 효과와 우수성을 입증한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.4
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• pp.289-293
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• 2002

Learning Classifier System (LCS) finds a new rule set using genetic algorithm (GA). In this paper, The Zeroth Level Classifier System (ZCS) is applied to evolving the strategy of a robot soccer simulation game (SimuroSot), which is a state varying dynamical system changed over time, as GBML (Genetic Based Machine Learning) and we show the effectiveness of the proposed scheme through the simulation of robot soccer.

• Annual Conference of KIPS
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• 2002.11c
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• pp.2467-2470
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• 2002

사용자의 필요를 충족시켜 줄 수 있도록 사용자에 대한 연구가 인터넷 비즈니스에서 활발히 이루어지고 있다. 인터넷 비즈니스와 마찬가지로 컴퓨터 게임 산업 분야에서도 이러한 연구가 필요하다. 하지만 컴퓨터 게임의 특성상 기존의 인터넷 비즈니스 방식과 같은 방법으로는 게이머(Gamer)의 행동을 알기 어렵다. 이러한 문제점을 해결하고자 본 논문에서는 패킷 마이닝(Packet Mining)을 이용한 게이머의 행위 분석 시스템을 제안하고자 한다. 이 시스템은 게이머들과 시스템 사이에 전달된 패킷을 수집하여 프로토콜별 텍스트 형태로 저장하고, 일정 시간이 흐르면 텍스트 형태로 저장된 패킷을 데이터베이스로 생성한다. 게이머 행위 분석 시스템은 이렇게 생성된 데이터베이스를 분석하고, 다양한 정보를 추출해내어 게이머의 행위를 분석한다.