• Korean Journal of Child Studies
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• v.26 no.1
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• pp.31-46
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• 2005

This study examined internet game addiction and college adaptation(academic, social, personal-emotional, institutional attachment) by Internet game motivation types. The 475 subjects (235 male and 240 female college students) responded to the newly developed self-report measure, Internet Game Motivation Scale (IGMS). Cluster analyses of IGMS data identified 5 types of Internet game motivation: Active I, Active II, Moderate I, Moderate II, Passive. Active (I, II) types had the highest scores in Internet game addiction while the Passive type yielded the lowest. Except for academic adaptation, all aspects of college adaptation varied as a function of Internet game motivation types. Overall, Moderate II showed highest whereas Active I showed lowest academic adaptation scores.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5260-5275
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• 2019

In the process of constructing the traditional offensive and defensive game theory model, these are some shortages for considering the dynamic change of security risk problem. By analysing the critical indicators of the incomplete information game theory model, incomplete information attack and defense game theory model and the mathematical engineering method for solving Bayes-Nash equilibrium, the risk-averse income function for information assets is summarized as the problem of maximising the return of the equilibrium point. To obtain the functional relationship between the optimal strategy combination of the offense and defense and the information asset security probability and risk probability. At the same time, the offensive and defensive examples are used to visually analyse and demonstrate the incomplete information game and the Harsanyi conversion method. First, the incomplete information game and the Harsanyi conversion problem is discussed through the attack and defense examples and using the game tree. Then the strategy expression of incomplete information static game and the engineering mathematics method of Bayes-Nash equilibrium are given. After that, it focuses on the offensive and defensive game problem of unsafe information network based on risk aversion. The problem of attack and defense is obtained by the issue of maximizing utility, and then the Bayes-Nash equilibrium of offense and defense game is carried out around the security risk of assets. Finally, the application model in network security penetration and defense is analyzed by designing a simulation example of attack and defense penetration. The analysis results show that the constructed income function model is feasible and practical.

• The Journal of Korea Robotics Society
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• v.14 no.3
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• pp.157-162
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• 2019

The video game Tetris is one of most popular game and it is well known that its game rule can be modelled as MDP (Markov Decision Process). This paper presents a DQN (Deep Q-Network) based game agent for Tetris game. To this end, the state is defined as the captured image of the Tetris game board and the reward is designed as a function of cleared lines by the game agent. The action is defined as left, right, rotate, drop, and their finite number of combinations. In addition to this, PER (Prioritized Experience Replay) is employed in order to enhance learning performance. To train the network more than 500000 episodes are used. The game agent employs the trained network to make a decision. The performance of the developed algorithm is validated via not only simulation but also real Tetris robot agent which is made of a camera, two Arduinos, 4 servo motors, and artificial fingers by 3D printing.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.8
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• pp.4043-4060
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• 2017

Network Intrusion Detection (NID), an important topic in the field of information security, can be viewed as a pattern recognition problem. The existing pattern recognition methods can achieve a good performance when the number of training samples is large enough. However, modern network attacks are diverse and constantly updated, and the training samples have much smaller size. Furthermore, to improve the learning ability of SVM, the research of kernel functions mainly focus on the selection, construction and improvement of kernel functions. Nonetheless, in practice, there are no theories to solve the problem of the construction of kernel functions perfectly. In this paper, we effectively integrate the advantages of the radial basis function kernel and the polynomial kernel on the notion of the game theory and propose a novel kernel SVM algorithm with game theory for NID, called GTNID-SVM. The basic idea is to exploit the game theory in NID to get a SVM classifier with better learning ability and generalization performance. To the best of our knowledge, GTNID-SVM is the first algorithm that studies ensemble kernel function with game theory in NID. We conduct empirical studies on the DARPA dataset, and the results demonstrate that the proposed approach is feasible and more effective.

• Journal of the Korean Operations Research and Management Science Society
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• v.34 no.1
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• pp.39-59
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• 2009

Game theory is adapted to a variety of domains such as economics, biology, engineering, political science, computer science, and philosophy in order to analyze economic behaviors. This research is an application of game theory to wireless communication. In particular, in terms of bargaining game we dealt with a multimedia resource allocation problem in wireless communication, which is rapidly spreading such as Wibro, WCDML, IPTV, etc. The algorithm is assumed to allocate multimedia resources to users who can choose and access differentiated media services. For this purpose, 3 utility function of users is devised to reflect quality of service (QoS) and price. We illustrated experimental results with synthesis data which were made to mimic real multimedia data, and analyzed differentiated service providing and the effect of the utility function.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.79-85
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• 2019

We investigate the D2D utility maximization in the cellular system. We focus on the non cooperative game theoretic approach to maximize the individual utility. Cellular system's perspective, interference from the D2D links must be limited to protect the cellular users. To accommodate this interference issue, utility function is first defined to control the individual D2D user's transmit power. More specifically, utility function includes the pricing which limits the individual D2D user's transmit power. Then, non cooperative power game is formulated to maximize the individual utility. Distributed algorithm is proposed to maximize the individual utility, while limiting the interference. Convergence of the proposed distributed algorithm is verified through computer simulation. Also the effect of pricing factor to SIR and interference is provided to show the performance of the proposed distributed algorithm.

• Journal of Korean Institute of Industrial Engineers
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• v.3 no.1
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• pp.55-59
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• 1977

This paper develops a portfolio management game applicable to Korean Stock Market with an emphasis on teaching and training aid. It allows each participant to start out with a certain amount of money and pick his favorable stocks from a list of stocks chosen by instructor. Each participant must make a transaction at each time period and he gets a readout that states his individual performance, i.e., stock lists, cash on hand, net worth, transactions he has made and rank in accordance with his net worth. This game package consists of 10 subprograms and 7 files written with Fortran language for use on the Nova 840 computer and is divided into 3 main categories according to their functions, i.e., book-keeping function, data processing function and information searching function. This package may be used for training portfolio decison makings in the stock market and for comparing various investment methods through hypothetical investments.

• Journal of the Korea Society of Computer and Information
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• v.23 no.10
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• pp.81-86
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• 2018

In the field of mobile games, social network games are steadily increasing in market scale and public interest every year. This paper proposes a method to design a social network game, which is one of the most successful genres in mobile games. The method uses Unity3D, the most commonly used engine for mobile game development. NGUI, a versatile developmental tool of Unity3D, is used to create shops and battle UIs. This paper particularly focuses on how to use the web hosting service to search and operate the necessary data from the database in the server. In addition, the proposed social network game is easy to implement real-time battle using Animator and Raycast, and is characterized by efficient battle implementation through time delay using Coroutine function.

• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.21-26
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• 2018

A variety of game algorithms have been proposed in recent years. Racing games using these new algorithms have greatly improved compared to those in the past. According to the analysis of racing games done by wheelgamer.com, a website that specializes in racing games, cars are the most common subject in mainstream racing games. These results show there are very few racing games using special subjects such as boats. This paper proposes a method to develop a realistic boat racing game using the Buoyont Force, beyond the limitation of typical racing games that are restricted to cars. A Material Editor based on Unreal Engine 4.12 is used to manifest the Dynamic Material of realistic ocean water. Blueprint, a visual scripting function, is used to materialize buoyancy which allows the boat to move freely along the waves.

• Journal of Korea Game Society
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• v.19 no.4
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• pp.85-96
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• 2019

In this note, we propose a game system to fairly and transparently control and update game variables using blockchain. As an example, we present an Ethereum-based maze escape game, being the first blockchain-based maze game and the first attempt to control game level through blockchain. In this system, the level function computes maze level reflecting the amount of maze walls purchased/sold by users. Using blockchain for game management saves human and economic resources and prevents unfair practice of game developers unilaterally manipulating game level or item enhancement rate.