• 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.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.598-601
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• 2016

최근 알파고로 인해 인공지능의 인기가 급부상하고 있고 '머신러닝'의 가능성과 위상을 널리 알려 컴퓨터 및 여러 분야에서 연구단계를 넘어 실용화, 상업화 될 가능성을 확인 시켜주었다. 본 연구는 전망 있는 인공지능산업에 발맞춰 비록 '알파고' 같은 고성능 완벽한 인공지능이 아니지만 랜덤 상태의 초기에서 한 최적의 해를 찾기 위한 도구로서, 유전알고리즘(genetic algorithms)을 사용하여 목표 값에는 최대한 수렴하도록 하는 학습형 AI 게임을 개발하였다. 본 연구에서 개발한 게임은 향후 각각의 다양한 개성을 가진 양산형 인공지능 게임개발에 응용되리가 사료된다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.117-118
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• 2023

본 논문에서는 메타버스 플랫폼과 생성형 AI와의 관련성과 상호작용을 살펴보고 생성형 AI가 메타버스에 영향을 주는 요소들의 특징과 메타버스와의 연계성을 기반으로 메타버스와 생성형 AI의 관계에 대한 방향성을 찾는 연구에 대한 기준을 제시한다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2014.07a
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• pp.297-301
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• 2014

게임에는 많은 종류의 장르가 있다. 어떤 장르의 게임이 되었건 플레이어와 많은 상호작용을 하는 A.I는 게임에 있어 중요한 요소 이며 어드벤처 게임(Adventure Game) 장르도 예외는 아니다. A.I(Artificial Intelligence)I의 행동이나 상황에 따른 플레이어와의 상호작용은 게임에 있어 플레이어에게 몰입감을 주며 게임을 좀 더 현실감 있게 해주는 게임의 수많은 요소 중 하나다. 본 논문에서는 FSM(Finite-State Machine) 기법을 사용하여 어드벤처 게임에서플레이어에게 '몰입'을 유발 시키는 방법으로 FSM 기법의 NPC(None-Player Character) A.I 패턴을 디자인을 통해 플레이어의 '몰입'을 유발 하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2361-2368
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• 2009

Recently AI(Artificial Intelligence) is one of the issues in the on-line game, a research that a game character seems to be realistic and is progressing using AI technique. Especially NPC is an important part of the AI researches of on-line game, and it is concerned by a game player and an architect. We proposed an intelligent agent framework to implement the NPC technique after studying the NPC technique using context awareness that reacts to the PC(Player Character) actively. Also, it can be developed gradually, and apply to various application because it has the capability to of adding an agent or deleting an agent easily.

• Journal of Korea Game Society
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• v.16 no.6
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• pp.79-90
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• 2016

Recently, many researchers have paid attention to the improved generation of AI agent in the area of game industry. Monte-Carlo Tree Search(MCTS) is one of the algorithms to search an optimal solution through random search with perfect information, and it is suitable for the purpose of calculating an approximate value to the solution of an equation which cannot be expressed explicitly. Games in Trading Card Game(TCG) genre such as the heartstone has imperfect information because the cards and play of an opponent are not predictable. In this study, MCTS is suggested in imperfect information card games so as to generate AI agents. In addition, the practicality of MCTS algorithm is verified by applying to heartstone game which is currently used.

• Journal of Korea Society of Digital Industry and Information Management
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• v.18 no.1
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• pp.55-64
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• 2022

This study analyzes the success factors of OTT original content through big data, and intends to suggest scenarios, casting, fun, and moving elements when producing the next work. In addition, I would like to offer suggestions for the success of 'Squid Game Season 2'. The success factor of 'Squid Game' through big data is first, it is a simple psychological experimental game. Second, it is a retro strategy. Third, modern visual beauty and color. Fourth, it is simple aesthetics. Fifth, it is the platform of OTT Netflix. Sixth, Netflix's video recommendation algorithm. Seventh, it induced Binge-Watch. Lastly, it can be said that the consensus was high as it was related to the time to think about 'death' and 'money' in a pandemic situation. The suggestions for 'Squid Game Season 2' are as follows. First, it is a fusion of famous traditional games of each country. Second, it is an AI-based planned MD product production and sales strategy. Third, it is casting based on artificial intelligence big data. Fourth, secondary copyright and copyright sales strategy. The limitations of this study were analyzed only through external data. Data inside the Netflix platform was not utilized. In this study, if AI big data is used not only in the OTT field but also in entertainment and film companies, it will be possible to discover better business models and generate stable profits.

• Journal of Korea Game Society
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• v.21 no.3
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• pp.79-90
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• 2021

Currently, for teenagers, the metaverse is becoming an important space for communication and experience. Due to the development of AI technology, experiences in the metaverse space are diversifying, which means that experiences in the virtual world can affect the real self. Therefore, this study attempted to examine the necessity of establishing a new concept of empathy across the metaverse for the AI era. In accordance with literature studies related to empathy, one was confirmed that the concept of empathy has been changing according to social ideas in times. In addition, with the result of the analysis of recent research trends, it was considered that the current study of empathy is generally taking a view as a measure of 'upright sociality.' In the end, this study suggest the necessity of redefined empathy in order to cultivate upright sociality in the metaverse.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.693-696
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• 2021

There are various algorithms in reinforcement learning, and the algorithm used differs depending on the field. Even in games, specific algorithms are used when developing AI (artificial intelligence) using reinforcement learning. Different algorithms have different learning methods, so artificial intelligence is created differently. Therefore, the developer has to choose the appropriate algorithm to implement the AI for the purpose. To do that, the developer needs to know the algorithm's learning method and which algorithms are effective for which AI. Therefore, this paper compares the learning methods of three algorithms, SAC, PPO, and POCA, which are algorithms used to implement game AI. These algorithms are practical to apply to which types of AI implementations.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.45-52
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• 2022

A tangible sports game is an exercise game that uses sensors or cameras to track the user's body movements and to feel a sense of reality. Recently, VR indoor sports room systems installed to utilize tangible sports game for physical activity in schools. However, these systems primarily use screen-touch user interaction. In this research, we developed a V-Catch Vision system that uses AI image recognition technology to enable tracking of user movements in three-dimensional space rather than two-dimensional wall touch interaction. We also conducted a usability evaluation experiment to investigate the exercise effects of this system. We tried to evaluate quantitative exercise effects by measuring blood oxygen saturation level, the real-time ECG heart rate variability, and user body movement and angle change of Kinect skeleton. The experiment result showed that there was a statistically significant increase in heart rate and an increase in the amount of body movement when using the V-Catch Vision system. In the subjective evaluation, most subjects found the exercise using this system fun and satisfactory.