• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.11-19
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• 2018

With the development of smart grid technology, it has become a hotspot to increase benefits of both residential users and electric power companies through demand response technology and interactive technology. In this paper, the game theory is introduced to the interaction between residential users and an electric company, making a mutually beneficial situation for the two. This paper solves the problem of electricity pricing and load shifting in the interactive behavior by building the game-theoretic process, proposing the interaction strategy and doing the optimization. In the simulation results, the residential users decrease their cost by 11% mainly through shifting the thermal loads and the electric company improves its benefits by 5.6% though electricity pricing. Simulation analysis verifies the validity of the proposed method and shows great revenue for the economy of both sides.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.615-629
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• 2021

With the development of mobile edge computing, how to utilize the computing power of edge computing to effectively and efficiently offload data and to compute offloading is of great research value. This paper studies the computation offloading problem of multi-user and multi-server in mobile edge computing. Firstly, in order to minimize system energy consumption, the problem is modeled by considering the joint optimization of the offloading strategy and the wireless and computing resource allocation in a multi-user and multi-server scenario. Additionally, this paper explores the computation offloading scheme to optimize the overall cost. As the centralized optimization method is an NP problem, the game method is used to achieve effective computation offloading in a distributed manner. The decision problem of distributed computation offloading between the mobile equipment is modeled as a multi-user computation offloading game. There is a Nash equilibrium in this game, and it can be achieved by a limited number of iterations. Then, we propose a distributed computation offloading algorithm, which first calculates offloading weights, and then distributedly iterates by the time slot to update the computation offloading decision. Finally, the algorithm is verified by simulation experiments. Simulation results show that our proposed algorithm can achieve the balance by a limited number of iterations. At the same time, the algorithm outperforms several other advanced computation offloading algorithms in terms of the number of users and overall overheads for beneficial decision-making.

• Journal of Engineering Education Research
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• v.25 no.6
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• pp.38-46
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• 2022

In order to improve students' interest, class participation and class comprehension in engineering theory classes, a class applying review games as Jinjinga, Bingo, etc. were designed and developed. Through applying them to three engineering theory subjects, the specific effects of the strategy on students' understanding, interest, participation, and academic achievement were analyzed and the usefulness of each review game strategy was analyzed. Analyzing class data over the past 11 years, there was a clear correlation between performance of the students in the review game and their actual grades, which was found to be greater than the negative effect of absence rate on the test performance or grades. This study also researched students' perceptions compared to other general subjects not applying the review games. The results of a survey of the students who took the review game class showed the usual amount of usual studying hours increased, the burden of examination or the amount of studying hours for preparing the exam was reduced, and the class interest and achievement significantly increased compared to other subjects in the same major.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.819-824
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• 1997

This paper presents a cell-based motion control strategy for soccer playing mobile robots. In the central robot motion planner, the planar ground is divided into rectangular cells with variable sizes and motion indices to which direction the mobile robot should move. At every time the multiple objects-the goal gate, ball, and robots-detected, integer values of motion indices are assigned to the cells occupied by mobile robots. Once the indices being calculated, the most desirable state-action pair is chosen from the state and action sets to achieve successful soccer game strategy. The proposed strategy is computationally simple enough to be used for fast robotic soccer system.

• Journal of Korean Institute of Industrial Engineers
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• v.42 no.1
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• pp.65-72
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• 2016

Curling is compared to the Chess because of variety and importance of strategies. For winning the Curling game, selecting optimal strategies at decision making points are important. However, there is lack of research on optimal strategies for Curling. 'Aggressive' and 'Conservative' strategies are common strategies of Curling; nevertheless, even those two strategies have never been studied before. In this study, Markov Decision Process would be applied for Curling strategy analysis. Those two strategies are defined as actions of Markov Decision Process. By solving the model, the optimal strategy could be found at any in-game states.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.683-691
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• 2002

In a game called red and black, you can stake any amount s in your possession. Suppose your goal is 1 and your current fortune is ｆ, with 0 < f < 1. You win back your stake and as much more with probability p and lose your stake with probability, q = 1- p. Ahn(2000) considered optimum strategy for this game with the value of p less than $\frac{1}{2}$ where the house has the advantage over the player. The optimum strategy at any f when p < $\frac{1}{2}$ is to play boldly, which is to bet as much as you can. In this paper we perform the simulation study to show that the Bold strategy is optimum.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.235-240
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• 2021

Recently, the number of users has risen sharply while the development speed of the Chinese game industry is rapidly developing. The game industry has already become a promising industry in China's cultural industry. With the rapid development of the Chinese game industry, the demand for specialized game designers and game development personnel is urgent. Still, at present, it is difficult for graduates to get a job at a game company every year even if a new game design department is established at a Chinese university. This may be due to a conflict between the education of the game major in the game market. In this paper, we present a customized development strategy while summarizing the problems that existed in the Chinese game design department in the rapidly developing background of the game industry, Try to provide a valuable opinion. and use it as a reference for the future development of education in the Chinese game major.

• The KIPS Transactions:PartB
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• v.11B no.1
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• pp.83-90
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• 2004

Strategic games are missing special qualities of genre these days. Game engines neither reason about behaviors of computer objects nor have learning ability that can prepare countermeasure in variously command user's strategy. This paper suggests a strategic game engine that applies non-monotonic reasoning and inductive machine learning. The engine emphasizes three components -“user behavior monitor”to abstract user's objects behavior,“learning engine”to learn user's strategy,“behavior display handler”to reflect abstracted behavior of computer objects on game. Especially, this paper proposes two layered-structure to apply non-monotonic reasoning and inductive learning to make behaviors of computer objects that learns strategy behaviors of user objects exactly, and corresponds in user's objects. The engine decides actions and strategies of computer objects with created information through inductive learning. Main contribution of this paper is that computer objects command excellent strategies and reveal differentiation with behavior of existing computer objects to apply non-monotonic reasoning and inductive machine learning.

• Korea Trade Review
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• v.44 no.1
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• pp.31-44
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• 2019

This study examines the normalization of Korean GM management between the Korean government and GM in terms of external negotiation game and internal negotiation game using Putnam's Two-Level Games. In addition, GM's Win-set change and negotiation strategy were analyzed. This analysis suggested implications for the optimal negotiation strategy for mutual cooperation between multinational corporations and local governments in the global business environment. First, the negotiation strategy for Korea's normalization of GM management in Korea can be shifted to both the concession theory and the opposition theory depending on the situation change and the government policy centered on the cautious theory. Second, GM will maximize its bargaining power through 'brink-end tactics' by utilizing the fact that the labor market is stabilized, which is the biggest weakness of the Korean government, while maintaining a typical Win-set reduction strategy. GM will be able to restructure at any time in terms of global management strategy, and if the financial support of the Korean government is provided, it will maintain the local factory but withdraw the local plant at the moment of stopping the support. In negotiations on the normalization of GM management in Korea, it is necessary to prepare a problem and countermeasures for various scenarios and to maintain a balance so that the policy does not deviate to any one side.

• Journal of Korea Game Society
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• v.17 no.2
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• pp.85-94
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• 2017

Over the recent years, there has been a sudden surge in interest over character-related products among mobile game developers in South Korea as a business strategy to extend mobile game lifespans. However, even with the majority of mobile game players aging around 18~35 and higher, there has been a lack of study regarding design preferences and consumption tendencies of adult players-or kidults-when it comes to character-related products. In this study, three distinctive decision patterns among kidults were identified using an online Q-Sort method: (a) Character Oriented, (b) Item Oriented, and (c) Character-item Oriented. The similarities and differences of these three types are further analyzed to provide insight into important factors that play decisive roles in purchasing decisions made by kidults. The results from this study can aid mobile game developers in establishing reference points for future character business directions.