• Journal of Korea Game Society
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• v.8 no.1
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• pp.79-90
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• 2008

This paper describes a motivation-based hierarchical behavior planning framework to allow autonomous agents to select adaptive actions in simulation game environments. The combined behavior planning system is formed by four levels of specification, which are motivation extraction, goal list generation, action list determination and optimization. Our model increases the complexity of virtual human behavior planning by adding motivation with sudden and cumulative attributes. The motivation selection by probability distribution allows NPC to make multiple decisions in certain situations in order to embody realistic virtual humans. Hierarchical goal tree enhances the effective reactivity. Optimizing for potential actions provides NPC with safe and satisfying actions to adapt to the virtual environment. A restaurant simulation game was used to elucidate the mechanism of the framework.

• The KIPS Transactions:PartB
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• v.15B no.3
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• pp.253-258
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• 2008

Recently, game players want new game requiring more various tactics and strategies in the complex environment beyond simple and repetitive play. Various artificial intelligence techniques have been suggested to make the game characters learn within this environment, and the recent researches include the neural network and the genetic algorithm. The Genetic programming(GP) has been used in this study for learning strategy of the agent in the pursuit-evasion problem which is used widely in the game theories. The suggested GP algorithm is faster than the existing algorithm such as neural network, it can be understood instinctively, and it has high adaptability since the evolving chromosomes can be transformed to the reasoning rules.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.303-310
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• 2015

Game technologies are now applied in various engineering areas such as the simulation of surgical operation or the implementation of a cyber model house. One of the essential and important technology in these applications is cutting of the 3D polygon model in real time. Real-time cutting technology is an essential technology needed to implement the simulation of a building demolition or a car assembly for training or educational purpose. Previous cutting method using the conventional BSP-Tree structure has some limitations in that they divide the whole world including the 3D model and its environment, only into two parts with respect to an infinite plane. In this paper, we show a technique cutting the 3D model in a finite extent in order to solve this problem. Specifically, we restricted the cut surface in a finite rectangular area and constructed the mesh for the divided surface. To show the usefulness of our partial cutting technique, an example of the dismantling process simulation of a nuclear reactor polygon model was illustrated.

• IE interfaces
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• v.17 no.2
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• pp.158-168
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• 2004

A technology roadmap was developed for haptic interface technologies to be applied to games. Haptic interface technologies are expected to play an important role in games to provide gamers with interaction and immersive perception in near future, even though haptic interface technologies have been less studied than other perception-related technologies with respect to games. Information on two types of haptic interfaces - portable and desktop - and their evolution processes were analyzed in terms of technological demands. Haptic feedback technologies to realize these demands were inspected with the time frame and haptic feedback technologies were derived using a technology tree. The technology roadmap of haptic interfaces in game was finally constructed by mapping the technological demands in time with game technology trends. The technology roadmap of haptic interfaces will have implications on developing haptic interfaces to be applied to many applications including virtual realities and games.

• Journal of Korea Game Society
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• v.20 no.2
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• pp.91-100
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• 2020

Life-and-death problem in Go is a fundamental problem to be overcome for implementing a computer Go. To solve it, an important consideration is to find out who surrounds or is surrounded between black and white players. To figure out the boundary between black and white groups, we applied an influence function and a contour tracing algorithm. We found that applying the Moore-neighbor tracing among various contour tracing algorithms can create boundaries, and also suggested the possibility of tremendously reducing the search space of a game tree.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.4
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• pp.77-89
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• 2001

Recently, with the explosive growth of communication technologies, group oriented services such as teleconference and multi-player game are increasing. Access control to information is handled by secret communications with group keys shared among members, and efficient updating of group keys is vital to such secret communications of large and dynamic groups. In this paper, we employ (2,4)-tree as a key tree, which is one of height balanced trees, to reduce the number of key updates caused by join or leave of members. Especially, we use CBT(Core Based Tree) to gather network configurations of group members and reflect this information to key tree structure to update group keys efficiently when splitting or merging of subgroups occurs by network failure or recovery.

• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.38-46
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• 2010

A stable game managing system is absolutely needed to accept simultaneous interlacing of many users for on- line game system. The proposed P2P on-line game system in this paper is able to get stable and real-time game managing within limited time stamp utilizing through reorganizing peers according to synchronous time which can be avoid congestion on one region, it is possible to synchronize for game nodes within limited time stamp utilizing. Reorganizing M-tree which leads 10 distribute loads. The system manages each region unit, and it is execute no matter how big game sizes are. Thus to ensure such as the problems of expand server and stabilization or message transmission. Also, prove efficiency of the suggested system through the simulation.

• Journal of Information Technology Applications and Management
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• v.18 no.3
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• pp.91-110
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• 2011

Korea professional baseball industry has grown to take the lion's share of the domestic sports industry, but still does not make break even. The purpose of this study is to examine the financial impact of adopting the Customer Relation Management (CRM) approach on the profitability of Korea professional baseball industry. We use a measuring tool called entropy used in ID3 decision tree algorithm. In the paper, we specify five the most important factors that affect spectator satisfaction based on the previous literature, perform survey analysis, calculate entropy values, and find the results. We predicted the change in revenues when we adopt CRM by checking the spectators' willingness to pay more when the conditions of each factor are improved. We find that we can reap significant fruits of the effect of CRM introduction through enhancing 'game content factor' and 'game promotion factor' among the five factors. We also find that we can increase the revenues of domestic professional baseball teams to 2.4 times or 2.1 times the current level if we manage intensively those two factors respectively. It is very surprising to see that the improvement in total revenues makes both ends meet for domestic professional baseball teams. This clearly demonstrates the effectiveness of CRM approach in improving the profitability of organizations.

• Journal of Korea Game Society
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• v.11 no.3
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• pp.63-72
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• 2011

In this paper, we propose a novel database creation and retrieval method of feature descriptors to support real-time marker-less tracking in the augmented reality environments. Each feature descriptor is encoded by integer and multi-level database is created in order to retrieve a feature descriptor efficiently. The retrieval of a feature descriptor is performed as follows: Firstly, candidate feature descriptors are searched by traversing the multi-level database. Secondly, the euclidean distance between input feature descriptor and each candidate one is compared. The shortest one is retrieved. The proposed method is 16 ms faster than previous KD-Tree method for each feature descriptor.

• Journal of Convergence for Information Technology
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• v.11 no.3
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• pp.1-6
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• 2021

Most of the match-3 puzzle games supports automatic play using the MCTS algorithm. However, implementing reinforcement learning agents is not an easy job because it requires both the knowledge of machine learning and the way of complex interactions within the development environment. This study proposes a method in which we can easily design reinforcement learning agents and implement game play agents by applying PPO(Proximal Policy Optimization) algorithms. And we could identify the performance was increased about 44% than the conventional method. The tools we used are the Unity 3D game engine and Unity ML SDK. The experimental result shows that agents became to learn game rules and make better strategic decisions as experiments go on. On average, the puzzle gameplay agents implemented in this study played puzzle games better than normal people. It is expected that the designed agent could be used to speed up the game level design process.