• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1258-1266
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• 2008

Most game players obtain more satisfactions by interacting with human players that have fluxed behavior patterns, than with NPC(Non-Player Character)s that have fixed behavior patterns. Since it is impossible that game players always interact with human players, adaptive NPCs that can variously behave are required. In this paper, we present a method to create adaptive NPCs using a dynamic FSM(Finite State Machine). This method configures a dynamic FSM by using behavior information at behavior database, and repeatedly updates the dynamic FSM so that the dynamic FSM's total efficiency approaches to a given target efficiency. NPC adapts to game players through this process. For an experiment, we have implemented a 2D game with this strategy, and experimented with various target efficiencies. We show that a dynamic FSM's total efficiency approaches to target efficiency by updating a dynamic FSM several times over. It means that the adaptive NPC to be generated, adapts to game players.

• Journal of Korea Game Society
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• v.8 no.1
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• pp.103-113
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• 2008

Although people have had more opportunities to enjoy various types of game, most of players have felt less satisfaction with the games. This is the reason that since most Non-player Characters (NPCs) are simple and uniform, they have some limitations for competing with a variety of players. Thus, technologies for creating intelligent NPCs that can compete with each player at a similar level are required. In this paper, we present an action information management method for creating adaptive NPCs based on the algorithm for calculating their action efficiency. This algorithm is useful to the adaptation method for saving and controlling player-appropriate action. In our method, adaptive NPCs observe the actions of players and collect the relationship data between status and action. The efficiency value of the action data is calculated and data of similar status are grouped, and finally stored at the action database. The game system of NPC updates the action database and stores diverse actions. Then, NPC selects action with high efficiency value. We have tested our algorithm on an action game. A random test subject performed a one-on-one game against an adaptive NPC in real-time. As a result, the action dispositions of both the subject and NPC are analyzed in a log file to determine whether or not the disposition of the subject is similar to that of the NPC. The statistics of the diverse test results shows that NPCs become adaptive to players with error rate within less than 6%.

• Journal of Korea Game Society
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• v.5 no.4
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• pp.23-32
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• 2005

This paper introduces environment analysis way to improve the game AI. The way of environment analysis can provide game user the more reality than generally used AI patterns. This paper suggests the way to make die NPC patterns variously. To realize this theory we designed the organization of NPC server newly, and also accomplished the experiment of NPC server simulation test to get the performance applied in real situation.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.345-348
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• 2004

플레이어의 상대 역할을 수행하는 NPC(Non-Player Character)의 구현은 게임에서 재미요소를 좌우하는 중요한 부분이다. 일반적인 NPC는 설정된 값에 따라, 동일한 조건에 대해 동일하게 반응하므로 플레이어로 하여금 예측 가능하게 하여 게임의 재미를 저하시키는 요인이 된다. 따라서 플레이어의 행동과 수준에 대하여 지능적으로 적절히 반응하는 NPC 기술이 필요하다. 본 논문은 퍼지 플러스터링을 이용한 플레이어의 게임 성향을 기반으로 NPC의 행동 반응을 조절함으로써 게임에 동적인 반응을 보이며 플레이어의 수준에 적절히 반응하도록 하는 NPC 기법을 제안한다.

• 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 the Korea Society of Computer and Information
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• v.25 no.4
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• pp.55-61
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• 2020

In this paper, we present a novel approach to efficiently control the location of NPC(Non-playable characters) in the interactive virtual world such as game, virtual reality. To control the NPC's movement path, we first calculate the main trajectory based on the user's path, and then move the NPC based on the weight map. Our method constructs automatically a navigation mesh that provides new paths for NPC by referencing the user trajectories. Our method enables adaptive changes to the virtual world over time and provides user-preferred path weights for smartagent path planning. We have tested the usefulness of our algorithm with several example scenarios from interactive worlds such as video games, virtual reality. In practice, our framework can be applied easily to any type of navigation in an interactive world.