• 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%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.2
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• pp.113-118
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• 2024

In this study, we designed and analyzed two main structures for effectively implementing the behavior of intelligent NPCs the Hierarchical Finite State Machine (HFSM) and the Behavior Tree, by creating experimental games. The HFSM was found to be efficient for complex interaction-centered actions where state changes and transitions are crucial, while the Behavior Tree was effective in dynamic environments where ease of modification and expansion are required for dynamic responses under various conditions. These structures were experimentally applied using the Unity engine to verify their efficiency. This study focused on the basic structure design and plans to apply these structures to an upcoming action-adventure escape game. The results of this research are expected to assist game developers in efficiently implementing intelligent NPCs, thereby contributing to the improvement of game quality and player satisfaction.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.6
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• pp.192-207
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• 2020

In industrial fields like big factories, efficient management of resources is critical in terms of time and expense. So, inefficient management of resources leads to additional costs. Nevertheless, in many cases, there is no proper system to manage resources. This study proposes a system to manage and track large-scale resources efficiently. We attached Bluetooth 5.0-based beacons to our target resources to track them in real time, and by saving their transportation data we can understand flows of resources. Also, we applied a diagonal survey method to estimate the location of beacons so we are able to build an efficient and accurate system. As a result, We achieve 47% more accurate results than traditional trilateration method.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.6
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• pp.777-784
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• 2017

In the architectural space, the user's behavior is the most important factor in evaluating the quality of architecture. Normally, the evaluation of user behavioral performance was carried out after a building was completed. Recently, interest in and efforts at pre-simulation based on information technology are accelerating. However, since existing user simulation technology is concerned mainly with simply escaping from a large space, it is impossible to simulate the behavior of multiple users in an architectural space. The present study strives to develop a human-figured intelligent agent for advanced user simulation based on ontology. The main purpose of the study is to employ the intelligent behaviors of a NPC(Non-player Character) to infer the ontology of both spatial and user information. In this paper, we intend to integrate ontology inference technology into the virtual space. And also, this study suggest the ontology visualization technology which illustrate the ontology-based information and their change in the spatial information.

• Journal of Korea Game Society
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• v.9 no.2
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• pp.125-133
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• 2009

Game artificial intelligence is usually used to provide intelligent and adjusted game environment for user. Previously, it was used for Non-player character(NPC) playing a role of a company or an enemy through collecting and analyzing a user's behaviour. However, it was just mimicking the user's behavior. This paper introduces a method to change game environment by analyzing a user's game behavior. Game behavior data has been used to understand user's game preference. Also, the user's preference was used to provide more active game environment by reflecting decision of geographical features, items and distribution of NPC. For experiment of the suggested method, we utilized a real 2D action game and confirmed the game environment which changing properly according to the user's game play.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2002.11a
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• pp.379-384
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• 2002

개발적인 측면에서 온라인 게임 환경에서의 NPC(Non Playable Character)들은 환경인식능력, 이동능력, 특수 능력 및 아이템의 소유 배분 등을 원활히 하기 위한 능력들을 소유해야 하며, 게임 환경을 인식, 저장하기 위한 데이터구조와 자신만의 독특한 임무(mission)를 달성하기 위한 계획을 갖고 행위를 해야 한다. 이런 의미에서 NPC는 자신만의 고유한 규칙과 행동 패턴, 그리고 목표(Goal)와 이를 실행하기 위한 계획(plan)을 소유하는 에이전트로 인식되어야 할 것이다. 그러나, 기존 게임의 NPC 제어 구조나 구현 방법은 이러한 요구조건에 부합되지 못한 부분이 많았다. C/C++ 같은 컴퓨터 언어들을 이용한 구현은 NPC의 유연성이나, 행위에 많은 문제점이 있었다. 이들 언어의 switch 문법은 NPC의 몇몇 특정 상태를 묘사하고, 그에 대한 행위를 지정하는 방법으로 사용되었으나, 게임 환경이 복잡해지면서, 더욱더 방대한 코드를 만들어야 했고, 해석하는데 많은 어려움을 주었으며, 동일한 NPC에 다른 행동패턴을 적용시키기도 어려웠다. 또한, 대부분의 제어권을 게임 서버 폭에서 도맡아 함으로써, 서버측에 많은 과부하 요인이 되기도 하였다. 이러한 어려움을 제거하기 위해서 게임 스크립트를 사용하기도 하였지만, 그 또한 단순 반복적인 패턴에 사용되거나, 캐릭터의 속성적인 측면만을 기술 할 수 있을 뿐이었다 이러한 어려움을 해소하기 위해서는 NPC들의 작업에 필요한 지식의 계층적 분화를 해야 하고, 현재 상황과 목표 변화에 적합한 반응을 표현할 수 있는 스크립트의 개발이 필수 적이라 할 수 있다 또한 스크립트의 실행도 게임 서버 측이 아닌 클라이언트 측에서 수행됨으로써, 서버에 걸리는 많은 부하를 줄일 수 있어야 할 것이다. 본 논문에서는, 대표적인 반응형 에이전트 시스템인 UMPRS/JAM을 이용하여, 에이전트 기반의 게임 캐릭터 구현 방법론에 대해 알아본다.퓨터 부품조립을 사용해서 Template-based reasoning 예를 보인다 본 방법론은 검색노력을 줄이고, 검색에 있어 Feasibility와 Admissibility를 보장한다.매김할 수 있는 중요한 계기가 될 것이다.재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity of computation. Adaptive transversal filter with proposed data recycling buffer algorithm could efficiently reject ISI of channel and increase speed of convergence in avoidance burden of computational complexity in reality when it was experimented having

• Proceedings of the Korean Information Science Society Conference
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• 2002.10d
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• pp.319-321
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• 2002

본 논문에서는 대표적인 3차원 일인칭 액션 게임(first-person action game)인 Unreal Tournament 게임과 이것에 기초한 Gamebots시스템을 소개하고, 이러한 환경에서 효과적으로 동작하는 지능형 NPC인 KGBot의 설계와 구현에 대해 설명한다. KGBot는 Gamebots시스템에서 하나의 보트 클라이언트(bot client)로 동작하면서 지형이 복잡한 3차원 가상환경 안에서 적들에 대항해 아군과 연합하여 특정 목표 지점(domination point)들을 찾아 점령하는 자율 NPC이다. KGBot는 BDI기반의 범용 에이전트 구조인 UM-PRS를 제어엔진으로 채용하고 있으며, 복잡한 행위들을 효과적으로 구현하기 위해 계충화된 지식베이스를 가지고 있다. 본 논문에서는 특히 제한적인 센서정보와 이동점(waypoint)에 기초하여 자신이 놓여진 월드의 전체지도를 작성하고 임의의 목적지까지 효율적인 이동경로를 계획할 수 있는 KGBot의 행위의 구현과 실험에 대해 설명한다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.12A
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• pp.1181-1187
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• 2010

This paper proposes a mobile AI (Artificial Intelligence) conducting decision-making in the game through education for intelligent character on the basis of Neural Network. Neural Network is learned through the input/output value of the algorithm which defines the game rule and the problem solving method. The learned character is able to perceive the circumstances and make proper action. In this paper, the mobile AI using Neural Network has been step-by-step designed, and a simple game has been materialized for its functional experiment. In this game, the goal, the character, and obstacles exist on regular 2D space, and the character, evading obstacles, has to move where the goal is. The mobile AI can achieve its goals in changing environment by learning the solution to several problems through the algorithm defined in each experiment. The defined algorithm and Neural Network are designed to make the input/output system the same. As the experimental results, the suggested mobile AI showed that it could perceive the circumstances to conduct action and to complete its mission. If mobile AI learns the defined algorithm even in the game of complex structure, its Neural Network will be able to show proper results even in the changing environment.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.228-241
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• 2021

This study verified the performance change of a LiDAR when it detects road signs, which are potential cooperation targets for an autonomous vehicle. In particular, road signs of different colors and materials were produced and tested in controlled rainfall on the real road environment. The NPC and intensity were selected as the performance indicators, and a T-Test was used for comparison. The study results show that the performance of LiDAR for the detection of road signs was reduced with the increase of rainfall. The degradation of performance in retroreflective sheets was lesser than painted road signs, but at the amount of 40 mm/h or more, the detection performance of retroreflective sheets deteriorates to an extent that data cannot be collected. The performance level of black paint was lower than that of other colors on a clear day. In addition, the white sheet was most sensitively degraded with the increase in precipitation. These performance verification results are expected to be utilized in the manufacturing of road facilities that improve the visibility of sensors in the future.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.4
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• pp.190-211
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• 2022

This study investigated the effect of the shape and height of road signs on detection performance when detecting road signs with LiDAR, which is recognized as an essential sensor for autonomous vehicles. For the study, four types of road signs with the same area and material and different shapes were produced, and a road driving test was performed by installing a 32Ch rotating LiDAR on the upper part of the vehicle. As a result of comparing the shape of the point cloud and the NPC according to the shape of the road sign, It is expected that a distance of less than 40m is required to recognize the overall shape of a road sign using 32Ch LiDAR, and shapes such as triangles and rectangles are more advantageous than squares in securing the maximum point cloud from a long distance. As a result of the study according to the height of the road sign, At short distances (within 20m), if the height of the sign is raised to more than 2m, it deviates from the vertical viewing angle of the LiDAR and cannot express the complete point cloud shape. However, it showed a negligible effect compared to the near-field height change. These research results are expected to be utilized in the development of road facilities dedicated to LiDAR for the commercialization of autonomous cooperative driving technology.