• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1145-1157
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• 2020

A convolution neural networks (CNNs) has demonstrated outstanding performance compared to other algorithms in the field of face recognition. Regarding the over-fitting problem of CNN, researchers have proposed a residual network to ease the training for recognition accuracy improvement. In this study, a novel face recognition model based on game theory for call-over in the classroom was proposed. In the proposed scheme, an image with multiple faces was used as input, and the residual network identified each face with a confidence score to form a list of student identities. Face tracking of the same identity or low confidence were determined to be the optimisation objective, with the game participants set formed from the student identity list. Game theory optimises the authentication strategy according to the confidence value and identity set to improve recognition accuracy. We observed that there exists an optimal mapping relation between face and identity to avoid multiple faces associated with one identity in the proposed scheme and that the proposed game-based scheme can reduce the error rate, as compared to the existing schemes with deeper neural network.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.215-222
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• 2007

As Korean online game market is saturated, Korean online game companies are trying to push into North American market. In order to succeed in foreign markets, understanding of user characteristics in that country is most important. In this study, investigation on user characteristics has been performed using user DB from A online game and B online game. They are currently in service by M company in America. Connection time, payment, and royalty are analyzed as a results. Based on the analysis, several advance strategies into North America are suggested. This results could be very useful for Korean MMORPG company to try to push into North America.

• Journal of Korea Game Society
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• v.6 no.4
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• pp.17-23
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• 2006

Most companies operate their business unit by products which occupy mostly their sales or can increase their sales. The evaluation of business units is very important part to check the market position of its business, the value of investment and business diversification. This paper applies 5 game flat forms to Korean game industry at base on GE model which can evaluate business unit with market merit and competitive advantage in market. the result of study indicates that main flat form and the other flat form distribute diversely, and can determine the time for the new product development, the flat form of main investment and marketing strategy.

• Journal of Korea Game Society
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• v.18 no.1
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• pp.135-148
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• 2018

In this study, we suggest that Copying Theory suggested by Pym could be effective in translating games. Languages used in games are based on English because of the history of games mainly developed in America. When people are playing games, people pursue effective communication. Because of this, they transform translated words into simple forms or original foreign languages to communicate each other for effective communication, The usage of English in game translation and communication support the idea that Copying strategy could be effective in translating games.

• Journal of Communications and Networks
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• v.18 no.3
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• pp.411-419
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• 2016

This article investigates the problem of distributed channel selection in opportunistic spectrum access networks from a perspective of interference minimization. The traditional physical (PHY)-layer interference model is for information theoretic analysis. When practical multiple access mechanisms are considered, the recently developed binary medium access control (MAC)-layer interference model in the previous work is more useful, in which the experienced interference of a user is defined as the number of competing users. However, the binary model is not accurate in mathematics analysis with poor achievable performance. Therefore, we propose a real-valued one called stochastic MAC-layer interference model, where the utility of a player is defined as a function of the aggregate weight of the stochastic interference of competing neighbors. Then, the distributed channel selection problem in the stochastic MAC-layer interference model is formulated as a weighted stochastic MAC-layer interference minimization game and we proved that the game is an exact potential game which exists one pure strategy Nash equilibrium point at least. By using the proposed stochastic learning-automata based uncoupled algorithm with heterogeneous learning parameter (SLA-H), we can achieve suboptimal convergence averagely and this result can be verified in the simulation. Moreover, the simulated results also prove that the proposed stochastic model can achieve higher throughput performance and faster convergence behavior than the binary one.

• 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.

• Review of Culture and Economy
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• v.17 no.2
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• pp.29-62
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• 2014

Game industry, one of cultural-content industry which is considered as a typical knowledge-based industry and creative industry, is not like the overseas expansion of traditional manufacture, and has different strategy and performance of export expansion through product or project-based strategy. Therefore, it should be approached by each content unit, and necessary to look at the factors that make their decision makings of foreign market entry vary. This study focuses on discovering creativity, absorptive capacity and strategic orientation(market orientation and innovation orientation) which affect the difference of distribution's decision making of entry into foreign market in game industry This paper examined 252 cases of online games in order to investigate creativity, absorptive capacity and strategic orientations for each foreign market and what entry type(among licensing, joint distribution, exclusive distribution) they chose according to the products developed in team level. This helps us analyze the factors affecting market orientation and innovation orientation in the perspectives of creativity and absorptive capacity in comprehensive way, and notice the phenomena which use different foreign distribution strategy though there are company incorporated abroad and their results. This study supplements the limit of the existing Resource-Based View, Resource-Dependent View, and traditional international business theories such as Transaction Cost Theory or OLI Paradigm(Eclectic Framework), and proves how company could reduce asymmetry of uncertainty and information in creative industry and whether they accomplish successful overseas expansion according to strategic orientations.

• Journal of Communications and Networks
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• v.16 no.6
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• pp.627-638
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• 2014

In this paper, we study the joint price and power allocation in spectrum sharing macro-femtocell networks. The proposed game theoretic framework is based on bi-level Stackelberg game where macro base station (MBS) works as a leader and underlaid femto base stations (FBSs) work as followers. MBS has fixed data rate and imposes interference price on FBSs for maintaining its data rate and earns revenue while FBSs jointly adjust their power for maximizing their data rates and utility functions. Since the interference from FBSs to macro user equipment is kept under a given threshold and FBSs compete against each other for power allocation, there is a need to determine a power allocation strategy which converges to Stackelberg equilibrium. We consider two cases for MBS power allocation, i.e., fixed and dynamic power. MBS can adjust its power in case of dynamic power allocation according to its minimum data rate requirement and number of FBSs willing to share the spectrum. For both cases we consider uniform and non-uniform pricing where MBS charges same price to all FBSs for uniform pricing and different price to each FBS for non-uniform pricing according to its induced interference. We obtain unique closed form solution for each case if the co-interference at FBSs is assumed fixed. And an iterative algorithm which converges rapidly is also proposed to take into account the effect of co-tier interference on interference price and power allocation strategy. The results are explained with numerical simulation examples which validate the effectiveness of our proposed solutions.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3565-3583
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• 2022

The task scheduling problem has received a lot of attention in recent years as a crucial area for research in the cloud environment. However, due to the difference in objectives considered by service providers and users, it has become a major challenge to resolve the conflicting interests of service providers and users while both can still take into account their respective objectives. Therefore, the task scheduling problem as a bi-objective game problem is formulated first, and then a task scheduling model based on the bi-objective game (TSBOG) is constructed. In this model, energy consumption and resource utilization, which are of concern to the service provider, and cost and task completion rate, which are of concern to the user, are calculated simultaneously. Furthermore, a many-objective evolutionary algorithm based on a partitioned collaborative selection strategy (MaOEA-PCS) has been developed to solve the TSBOG. The MaOEA-PCS can find a balance between population convergence and diversity by partitioning the objective space and selecting the best converging individuals from each region into the next generation. To balance the players' multiple objectives, a crossover and mutation operator based on dynamic games is proposed and applied to MaPEA-PCS as a player's strategy update mechanism. Finally, through a series of experiments, not only the effectiveness of the model compared to a normal many-objective model is demonstrated, but also the performance of MaOEA-PCS and the validity of DGame.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.44 no.2
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• pp.215-221
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• 2024

The government is encouraging the expansion of renewable energy facilities through national renewable energy policy. However, the installation of renewable energy generation facilities has led to local resident complaints due to landscape degradation, electromagnetic wave emission, real estate devaluation, and environmental pollution. This creates conflicts between power project developers and residents, making the progress of projects more difficult. This study applies non-cooperative game theory to analyze eight cases of renewable energy projects where conflicts between developers and residents were resolved through resident's investment participation. By accepting investments from local stakeholders, residents achieved returns ranging from a maximum of 25 % to a minimum of 4.1 %. It was found through game theory analysis that a dominant strategy involves residents agreeing to the development of the project and the developers sharing a portion of the profits with the residents. The analysis results show that the point where dominant strategy meet forms a Nash equilibrium, and at the same time becomes the Pareto optimal point, benefiting both power generation operators and residents.