• 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 Game Society
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• v.21 no.6
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• pp.87-96
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• 2021

As the industry develops, the technology used for games is also being advanced. In particular, AI technology is used to game automation and intelligence. These game player patterns are widely used in online games such as player matchmaking, generation of friendly or hostile NPCs, and balancing of game worlds. This study proposes a model generation method for game players. For model generation, attributes such as hunting, collection, movement, combat, crisis management, production, and interaction were defined, and patterns were extracted and modeled using decision tree method. To evaluate the proposed method, we used the game log of a commercial game and confirmed the meaningful results.

• Journal of Korea Technology Innovation Society
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• v.6 no.2
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• pp.213-227
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• 2003

초고속 인터넷 서비스는 사용자수의 증가와 더불어 고객의 다양한 욕구 즉 인터넷 방송, 주문형비디오(VOD)서비스, 원격교육, 고화질 TV 등 대용량의 멀티미디어 서비스에 대한 욕구가 폭발적으로 증가하고 있다. 이러한 욕구를 충족하기 위해서는 현재의 초고속 인터넷서비스로서는 속도에 대한 한계에 부딪치게 되어 통신사업자들은 새로운 기술 또는 여러 가지 기술적 대안들을 추구하고 있다. 2002년부터 시작하여 2003년 이후에는 멀티미디어 수요의 증가에 따라 ADSL을 대체하는 기술로 VDSL이 등장하여 매년 꾸준한 신규가입자 수요가 발생하고 있으나, 통신사업자들은 각각의 망 특성, 시장위치, 전략적 필요성 둥에 의해 상용화를 적극 검토,추진하고 있으나 각각 전개하는 방식은 조금씩 다르다. 따라서 본 연구에서는 통신사업자들의 가입자망 진화 전략에 대해 살펴 본 다음 Lot3n-Volterra Competition (LVC) 모델을 이용 ADSL 과 VDSL 두 기술간의 상호 경쟁 및 대체를 통해 어떻게 진화 되어가는지를 살펴보았다. 대표적인 통신사업자인 KT는 막강한 자금력을 바탕으로 시장 확대 및 경쟁사와의 차별화를 위해 VDSL 서비스 조기도입을 서두르고 있고, 하나로는 자금의 열세로 인한 ADSL 투자비를 회수 할때까지 VDSL 서비스를 연기하고 있는 실정이다. ADSL과 VDSL 두 기술의 관계는 Lotka-Volterra Competition (LVC) 모델을 이용한 시뮬레이션 결과를 통해 빠른 속도와 비슷한 가격대의 VDSL이 침략자(predator)로 기존 시장 지배자인 ADSL을 사냥감(prey)으로 빠른 속도로 대체해 나가는 것을 알 수 있었다.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.548-553
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• 2014

In order to evaluate the performance of arrow that manufactures through production process, it is used that personal experiences such as hunters who have been using bow and arrow for a long time, technicians who produces leisure and sports equipment, and experts related with this industries. Also, the intensity of arrow's impact point which obtains from repeated shooting experiments is an important indicator for evaluating the performance of arrow. There are some ongoing researches for evaluating performance of arrow using intensity of the arrow's impact point and the arrow's flying image that obtained from high-speed camera. However, the research that deals with mutual relation between distribution of the arrow's impact point and characteristics of the arrow (length, weight, spine, overlap, straightness) is not enough. Therefore, this paper suggests both the system that could describes the distribution of the arrow's impact point into numerical representation and the correlation model between characteristics of arrow and impact points. The inputs of the model are characteristics of arrow (spine, straightness). And the output is MAD (mean absolute distance) of triangular shaped coordinates that could be obtained from 3 times repeated shooting by changing knock degree 120. The input-output data is collected for learning the correlation model, and ANN (artificial neural network) is used for implementing the model.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.3
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• pp.422-427
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• 2010

Korean Game industry, especially MMORPG(Massively Multiplayer Online Game) has been rapidly expanding in these days. But As game industry is growing, lots of online game security incidents have also been increasing and getting prevailing. One of the most critical security incidents is 'Game Bots', which are programs to play MMORPG instead of human players. If player let the game bots play for them, they can get a lot of benefic game elements (experience points, items, etc.) without any effort, and it is considered unfair to other players. Plenty of game companies try to prevent bots, but it does not work well. In this paper, we propose a behavior pattern model for detecting bots. We analyzed behaviors of human players as well as bots and identified six game features to build the model to differentiate game bots from human players. Based on these features, we made a Naive Bayesian classifier to reasoning the game bot or not. To evaluated our method, we used 10 game bot data and 6 human Player data. As a result, we classify Game bot and human player with 88% accuracy.