• Journal of the military operations research society of Korea
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• v.34 no.2
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• pp.143-162
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• 2008

This paper aims to formulate the method of estimating the wartime stockpile requirement of 155mm self-propelled artillery including intelligent ammunition for armored vehicles, currently being developed. The usual method of utilizing war-game simulation results in considerable margins in expected occupancy ratio between ground forces and air forces for each weapon system for armored vehicles. Also, the method tends to produce excessive output greater than the minimal stockpile requirements; therefore, the study aims to overcome limitations like these by the allocation method for each weapon system according to targets. This allocation method is better than war-game simulation method.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.329-336
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• 2005

This paper proposes a method to provide intelligence for characters in fighting action games by using genetic algorithm. The proposed characters without any knowledge on the rules of the game learn the rules and techniques for generations, and have the capability of evolving. To evaluate adaptability for varying circumstances, we changed the rules and compared the results. The experimental results show that the intelligent characters can adapt to the new rules. An advantage of the proposed method is that it can be easily applied to characters for other category of games such as PC games and internet online games.

• Advances in Computational Design
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• v.3 no.4
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• pp.405-418
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• 2018

Building Information Modelling (BIM) and Discrete Event Simulation (DES) are tools widely used in the context of the construction industry. While BIM is used to represent the physical and functional characteristics of a facility, DES models are used to represent its construction process. Integrating both is beneficial to those interested in the field of construction management since it has many potential applications. Game engines provide a human navigable 3D virtual environment in which the integrated BIM and DES models can be visualised and interacted with. This paper reports the experience obtained while developing a simulator prototype which integrates a BIM and a DES model of a single construction activity within a commercial game engine. The simulator prototype allows the user to visualise how the duration of the construction activity is affected by different input parameters interactively. It provides an environment to conduct DES studies using the user's own BIM models. This approach could increase the use of DES technologies in the context of construction management and engineering outside the research community. The presented work is the first step towards the development of a serious game for construction management education and was carried out to determine the suitable IT tools for its development.

• Journal of Korea Game Society
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• v.8 no.3
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• pp.77-85
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• 2008

In the current online game field, many studies on the realization of AI have been carried out. It is, however, very hard to apply smart AI to the online games due to the limited use of resources. The Fuzzy extension method this thesis presents is suitable to online games because it causes less loads in the system and makes it possible to realize more human-like AI. To realize this kind of AI, this paper suggests AI system design methods suitable to fuzzy-based online game and presents practical plans to apply them through the produced demos.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.242-263
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• 2021

This paper presents a method to implement a low-cost driving simulator for developing autonomous driving algorithms. This is implemented by using GTA V, a physical engine-based commercial game software, containing a function to emulate output and data of various sensors for autonomous driving. For this, NF of Script Hook V is incorporated to acquire GT data by accessing internal data of the software engine, and then, various sensor data for autonomous driving are generated. We present an overall function of the developed driving simulator and perform a verification of individual functions. We explain the process of acquiring GT data via direct access to the internal memory of the game engine to build up an autonomous driving algorithm development environment. And, finally, an example applicable to artificial neural network training and performance evaluation by processing the emulated sensor output is included.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.1-12
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• 2003

In this paper, we Introduce the Unreal Tournament (UT) game and the Gamebots system. The former it a well-known 3D first-person action game and the latter is an intelligent agent research testbed based on UT And then we explain the design and implementation of KGBot, which is an intelligent non-player character deploying effectively within the 3D virtual environment provided by UT and the Gamebots system. KGBot is a bot client within the Gamebots System. KGBot accomplishes its own task to find out and dominate several domination points pro-located on the complex surface map of 3D virtual environment KGBot adopts UM-PRS as its control engine, which is a general BDI agent architecture. KGBot contains a hierarchical knowledge base representing its complex behaviors in multiple layers. In this paper, we explain details of KGBot's Intelligent behaviors, tuck af locating the hidden domination points by exploring the unknown world effectively. constructing a path map by collecting the waypoints and paths distributed over the world, and finding an optimal path to certain destination based on this path graph. Finally we analyze the performance of KGBot exploring strategy and control engine through some experiments on different 3D maps.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.41 no.4
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• pp.73-83
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• 2004

With increasing numbers of vehicles on restricted roads, It happens that we have much wasted time and decreased average car speed. This paper proposes a new concept of coordinating green time which controls 10 traffic intersection systems. For instance, if we have a baseball game at 8 pm today, traffic volume toward the baseball game at 8 pm today, franc volume toward the baseball game will be increased 1 hour or 1 hour and 30 minutes before the baseball game. At that time we can not predict optimal green time Even though there have smart electro-sensitive traffic light system. Therefore, in this paper to improve average vehicle speed and reduce average vehicle waiting time, we created optimal green time using fuzzy rules md neural network as a preprocessing. Also, we developed an Intelligent PLC(Programmable Logic Controller) for real time traffic forecasting as a postprocesing about unexpectable conditions. Computer simulation results proved reducing average vehicle waiting time which proposed coordinating green time better than electro-sensitive franc light system does not consider coordinating green time.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.390-399
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• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• 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.

• Proceedings of the Korea Contents Association Conference
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• 2010.05a
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• pp.58-60
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• 2010

지금까지 유아 대상의 체감형 게임을 개발하려는 여러 시도가 있었으나 사용자의 행동체계가 완성되었다는 가정하에 만들어져 정형화된 동작을 하지 않고 자유롭게 움직이는 유아의 동작을 인식하는데 부족하다는 문제점을 가지고 있었다. 또 유아의 감성에 맞춘 콘텐츠나 디자인을 이용하기 보다는 성인의 감각에 맞추어 개발된 것들이 많았다. 본 논문에서는 유아를 위한 체감형 줄넘기 게임 개발과정을 소개함으로써 유아의 동작 특징을 활용한 체감형 게임 개발에 필요한 요소들을 제안하려한다.