• Proceedings of the Korean Information Science Society Conference
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• 2004.10a
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• pp.658-660
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• 2004

최근 컴퓨터 게임에 있어 인공지능에 관한 관심이 높아지고 있다. 이에 따라 게임에서 인공지능 구현을 지원하는 게임 NPC 지능 개발 플랫폼에 관한 연구도 많이 진행되고 있다. 본 논문에서는 게임에서 NPC의 지능을 개발하는 측면에서 게임 NPC 지능 개발 플랫폼 설계 시에 요구되는 사항들을 알아보고, 실제게임 NPC 지능 개발 플랫폼들-FEAR SOAR, Gamebots-의 구조를 비교, 분석한다 또한 기존 게임 NPC 지능 개발 플랫폼에서 발생하는 문제점을 알아보고, 이를 해결하기 위한 방법을 제안한다.

• Journal of Digital Convergence
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• v.12 no.1
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• pp.555-561
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• 2014

Artificial intelligence in the game is mainly used to determine patterns of behavior of NPC (Non Player Character) and the enemy, path finding. These artificial intelligence is implemented by FSM (Finite State Machine) or Flocking method. The number of NPC behavior in FSM method is limited by the number of FSM states. If the number of states is too small, then NPC player can know the behavior patterns easily. On the other hand, too many implementation cases make it complicated. The NPC behaviors in Flocking method are determined by the leader's decision. Therefore, players can know easily direction of movement patterns or attack pattern of NPCs. To overcome these problem, this paper proposes agonistic behaviors(attacks, threats, showing courtesy, avoidance, submission)in animals to apply for the NPC, and implements agonistic behaviors using Unity3D engine. This paper can help developing a real sense of the NPC artificial intelligence.

• Proceedings of the Korea Contents Association Conference
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• 2006.05a
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• pp.388-391
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• 2006

In the lately fews years, it take a growing interested in game AI and study zealously on game AI. In this paper, we research an usual individuality of NPC(Non-Player Character) on MMORPG(Massively Multiplayor Online Role Playing Game) and An AI technique on computer game. we study on a role and an individuality of NPC for take-up the game, moreover, we research on technique of game AI for take-up the game.

• 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 Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.40-51
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• 2006

As computer games become more complex and consumers demand more sophisticated computer controlled NPCs, developers are required to place a greater emphasis on the artificial intelligence aspects for their games. The platform for game NPC Intelligence Development should support real-time, independence, flexibility, group behavior, and various A.I to NPC that are reactive, realistic and easy to develop. This paper presents an architecture to satisfy these criteria for the platform of game NPC intelligence development. The proposed platform shows the higher performance than existing platform through the load sharing, and it also has some advantages which are supporting the various AI techniques, efficient group behavior, and independence to develop NPC intelligence.

• CDE review
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• v.10 no.2
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• pp.34-39
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• 2004

포괄적인 개념에서, 게임에서 인공지능이란 PC(Player Character, 사용자에 의해서 조정되는 게임 오브젝트)를 제외한 모든 것들을 제어하기 위해 사용되는 일련의 기술이라고 정의할 수 있다. 예를 들면, PC를 둘러싸고 있는 환경, PC를 대적하거나 경쟁관계에 있는 NPC(Non-Player Character), PC에 조언을 해주는 조언자 NPC 등을 제어하고 사용자가 느끼기에 지능적이면서 실제적인 것으로 보이도록 하여 게임의 흥미를 더하기 위한 기술들이다. (중략)

• Journal of Korea Game Society
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• v.14 no.5
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• pp.127-136
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• 2014

NPC in game is an important factor to increase the fun of the game by cooperating with player or confrontation with player. NPC's behavior patterns in the previous games are limited. Also, there is not much difference in NPC's ability among the existing games because it's designed to FSM. Therefore, players who have matched with NPCs which have the characteristics may have difficulty to play. This paper is for improving the problem and production and evaluation of the game NPC behavior model based on wolves hunting model in real life. To achieve it, first, the research surveys and studies behavior states for wolves to capture prey in the real world. Secondly, it is implemented using the Unity3D engine. Third, this paper compares the implemented state transition probability to state transition probability in real world, state transition probability in general game. The comparison shows that the number of state transitions of NPCs increases, proportions of implemented NPC behavior patterns converges to probabilities of state transition in real-world. This means that the aggressive behavior pattern of NPC implemented is similar to the wolf hunting behavior pattern of the real world, and it can thereby provide more player experience.

• Journal of Korea Multimedia Society
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• v.12 no.2
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• pp.290-299
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• 2009

Evolutionary Artificial Neural Networks (EANNs) has been highly effective in Artificial Intelligence (AI) and in training NPCs in video games. When EANNs is applied to design game NPCs' smart AI which can make the game more interesting, there always comes two important problems: the more complex situation NPCs are in, the more complex structure of neural networks needed which leads to large operation cost. In this paper, the Dynamic State Evolutionary Neural Networks (DSENNs) is proposed based on EANNs which deletes or fixes the connection of the neurons to reduce the operation cost in evolution and evaluation process. Darwin Platform is chosen as our test bed to show its efficiency: Darwin offers the competitive team game playing behaviors by teams of virtual football game players.

• Journal of Korea Game Society
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• v.14 no.4
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• pp.37-44
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• 2014

In this paper, we propose a NPC decision making model based on Prospect Theory which tries to model real-life choice, rather than optimal decision. For this purpose, we analyse the problems of reference point setting, diminishing sensitivity and loss aversion which are known as limitations of the utility theory and then apply these characteristics into the decision making in game. Dynamic Terrain Analysis is utilized to evaluate the proposed model and experimental result shows the method have effects on inducing diverse personality and emergent behavior on NPC.

• Proceedings of the Korea Information Processing Society Conference
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• 2006.11a
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• pp.183-186
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• 2006

NPC(Non playable Character)모델은 온라인 게임뿐만 아니라 가상공간 시스템 구축 시 빠질 수 없는 중요한 요소이다. 현재 가장 널리 사용되는 인공지능 처리방식의 하나인 FSM(Finite State Machine)은 NPC의 행동양식을 표현하기 위해 유한한 개수의 상태를 이용하는 알고리즘이다. 인공지능이 적용된 NPC 모델 설계시 정확한 명세는 구현 단계에서 발생되는 자원의 손실을 막아주고 요구명세에 따른 검증을 가능하게 한다. 본 논문에서는 해저가상공간 구축 시 발생되는 어류 객체의 행동패턴을 분석하여 속성을 정의하였으며, 환경변화에 따른 행동 특성의 상호관계를 설정하여 정형화하였다. 정의된 속성을 가진 NPC 모델을 FSM 알고리즘을 적용해 설계하고 구현한다. 설계된 NPC모델은 CTL기반의 모델체커인 SMV(Symbolic Model Verification)를 통해 검증함으로써 설계에 대한 타상성을 입증하였다.