• 전자통신동향분석
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• 제37권4호
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• pp.70-80
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• 2022

With the rapid growth in media service platforms providing broadcast programs or content services, content production has become more important and competitive. As a strategy to meet the diverse needs of global consumers for a variety of content and to retain them as long-term repeat customers, global over-the-top service providers are increasing not only the number of content productions but also their production efficiency. Moreover, a considerable amount of scene composition in the flow of content production work appears to be combined with rendering technology from a game engine and converted to object-based computer programming, thereby enhancing the creativity, diversity, quality, and efficiency of content production. This study examines the latest technology trends in content production such as virtual studio technology, which has emerged as the center of content production, the use cases in various fields of artificial intelligence, and the metadata standards for content search or scene composition. This study also examines the possibility of using object-based computer programming as one of the future candidate technologies for content production.

• Asia Marketing Journal
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• 제16권1호
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• pp.35-69
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• 2014

The impact of competition on pricing has been studied in the context of counterfactual merger analyses where expected optimal prices in a hypothetical monopoly are compared with observed prices in an oligopolistic market. Such analyses would typically assume static decision making by consumers and firms and thus have been applied mostly to data obtained from consumer packed goods such as cereal and soft drinks. However such static modeling approach is not suitable when decision makers are forward looking. When it comes to the markets for durable products with indirect network effects, consumer purchase decisions and firm pricing decisions are inherently dynamic as they take into account future states when making purchase and pricing decisions. Researchers need to take into account the dynamic aspects of decision making both in the consumer side and in the supplier side for such markets. Firms in a two-sided market typically subsidize one side of the market to exploit the indirect network effect. Such pricing behaviors would be more prevalent in competitive markets where firms would try to win over the battle for standard. While such qualitative expectation on the relationship between pricing behaviors and competitive structures could be easily formed, little empirical studies have measured the extent to which the distinct pricing structure in two-sided markets depends on the competitive structure of the market. This paper develops an empirical model to measure the impact of competition on optimal pricing of durable products under indirect network effects. In order to measure the impact of exogenously determined competition among firms on pricing, we compare the equilibrium prices in the observed oligopoly market to those in a hypothetical monopoly market. In computing the equilibrium prices, we account for the forward looking behaviors of consumers and supplier. We first estimate a demand function that accounts for consumers' forward-looking behaviors and indirect network effects. And then, for the supply side, the pricing equation is obtained as an outcome of the Markov Perfect Nash Equilibrium in pricing. In doing so, we utilize numerical dynamic programming techniques. We apply our model to a data set obtained from the U.S. video game console market. The video game console market is considered a prototypical case of two-sided markets in which the platform typically subsidizes one side of market to expand the installed base anticipating larger revenues in the other side of market resulting from the expanded installed base. The data consist of monthly observations of price, hardware unit sales and the number of compatible software titles for Sony PlayStation and Nintendo 64 from September 1996 to August 2002. Sony PlayStation was released to the market a year before Nintendo 64 was launched. We compute the expected equilibrium price path for Nintendo 64 and Playstation for both oligopoly and for monopoly. Our analysis reveals that the price level differs significantly between two competition structures. The merged monopoly is expected to set prices higher by 14.8% for Sony PlayStation and 21.8% for Nintendo 64 on average than the independent firms in an oligopoly would do. And such removal of competition would result in a reduction in consumer value by 43.1%. Higher prices are expected for the hypothetical monopoly because the merged firm does not need to engage in the battle for industry standard. This result is attributed to the distinct property of a two-sided market that competing firms tend to set low prices particularly at the initial period to attract consumers at the introductory stage and to reinforce their own networks and eventually finally to dominate the market.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• Journal of Information Processing Systems
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• 제8권3호
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• pp.409-420
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• 2012

The decision-making by agents in games is commonly based on reinforcement learning. To improve the quality of agents, it is necessary to solve the problems of the time and state space that are required for learning. Such problems can be solved by Macro-Actions, which are defined and executed by a sequence of primitive actions. In this line of research, the learning time is reduced by cutting down the number of policy decisions by agents. Macro-Actions were originally defined as combinations of the same primitive actions. Based on studies that showed the generation of Macro-Actions by learning, Macro-Actions are now thought to consist of diverse kinds of primitive actions. However an enormous amount of learning time and state space are required to generate Macro-Actions. To resolve these issues, we can apply insights from studies on the learning of tasks through Programming by Demonstration (PbD) to generate Macro-Actions that reduce the learning time and state space. In this paper, we propose a method to define and execute Macro-Actions. Macro-Actions are learned from a human subject via PbD and a policy is learned by reinforcement learning. In an experiment, the proposed method was applied to a car simulation to verify the scalability of the proposed method. Data was collected from the driving control of a human subject, and then the Macro-Actions that are required for running a car were generated. Furthermore, the policy that is necessary for driving on a track was learned. The acquisition of Macro-Actions by PbD reduced the driving time by about 16% compared to the case in which Macro-Actions were directly defined by a human subject. In addition, the learning time was also reduced by a faster convergence of the optimum policies.

• 한국컴퓨터그래픽스학회논문지
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• 제12권4호
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• pp.1-5
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• 2006

본 논문에서는 하이트필드 맵을 이용한 회화적 질감 표현 방법을 제시한다. 회화적 렌더링된 결과물의 하이트필드 맵을 이용하면 회화작품의 질감을 표현할 수 있다. 이를 위해 하이트필드 맵을 바탕으로 노말 매핑과 디스플레이스먼트 매핑 방법을 이용하여 회화적 렌더링을 구현하였다. 제시된 방법은 GPU 프로그래밍을 이용하여 물체의 세부적인 표면을 실시간으로 회화적 렌더링할 수 있어 3차원 가시화나 게임엔진에 응용할 수 있다.

• 한국국방경영분석학회지
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• 제31권1호
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• pp.107-121
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• 2005

In this study, a new fictitious play (FP) procedure is presented to solve two-person zero-sum (TPZS) Blotto games. The FP solution procedure solves TPZS games by assuming that the two players take turns selecting optimal responses to the opponent's strategy observed so far. It is known that FP converges to an optimal solution, and it may be the only realistic approach to solve large games. The algorithm uses dynamic programming (DP) to solve FP subproblems. Efficiency is obtained by limiting the growth of the DP state space. Blotto games are frequently used to solve simple missile defense problems. While it may be unlikely that the models presented in this paper can be used directly to solve realistic offense and defense problems, it is hoped that they will provide insight into the basic structure of optimal and near-optimal solutions to these important, large games, and provide a foundation for solution of more realistic, and more complex, problem

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2005년도 춘계학술발표대회
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• pp.1657-1660
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• 2005

In this paper, we introduce a general method for constructing 3D models viewing, editing and synthesizing system, including the practical algorithms that are necessary in 3D animation and game programming. While at the same time, the user’s customized acquirements are considered in our system by providing a flexible and friendly interface. Also 3D objects file formats and the method for writing 3D file sparser and loader program are introduced.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 춘계학술발표논문집 (상)
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• pp.163-166
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• 2002

컴퓨터 게임의 발달은 오프라인 PC 게임에서 인터넷의 보급으로 인해 온라인 게임으로 발전하였다. 그 후 인터넷 환경은 유선 환경뿐만 아니라 무선 환경에서도 무선 단말기를 이용하여 게임 서비스가 가능한 수준에 이르렀다. 그러나 적은 메모리와 낮은 수준의 처리능력을 가지고 있는 제한적인 모바일 환경의 특성으로 유선 인터넷에서와 같이 멀티미디어를 포함한 다양한 형태의 정보제공 및 인터렉티브한 모바일 게임이 어려운 현실이다. 본 논문에서는 WAP(Wireless Application Protocol)을 기반으로 하여 다운로드 솔루션을 채택한 GVM(General Virtual Machine) 상에서 실행될 수 있는 모바일 게임을 설계하고 MobileC 언어를 사용하여 제작하였다. 또한, 모바일 게임을 설계하고 제작하는 과정을 통해서 단말기의 제한적인 실행환경에서 최대한의 효과를 나타낼 수 있는 개발 모델을 제시하고자 한다. GVM은 무선 단말기 상에서 동적인 응용프로그램을 실행할 수 있는 가상기계 플랫폼이다.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2017년도 제56차 하계학술대회논문집 25권2호
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• pp.307-308
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• 2017

본 논문에서는 Facebook 테트리스 게임에서 착안하여 모바일로도 실행시키고자 하였다. Facebook 테트리스와 같이 Hold, 미리보기, 줄 넘기기공격 등 세부 기능을 모두 구현하였다.Hold를 하면 다음에 나올 블록을 저장하여 필요할때 꺼내쓸수 있도록 한다. 미리보기를 하여 블록이 바닥에 도달했을시 예상위치를 나타내준다. 한 줄을 clear하였을 시 상대방바닥에 한줄이 올라오도록 한다. 안드로이드 프로그래밍으로 응용시 모바일 앱환경에서도 활용할수 있다.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2017년도 추계학술발표대회
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• pp.608-610
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• 2017

최근 프로그래밍 교육에 대한 요구가 그 어느때보다 높아지고 있다. 특히 프로그래밍교육이 초등학교때부터 의무화되는 2018년을 맞이하여, 수많은 프로그래밍 교육을 위한 연구가 진행되고 있다. 본 논문에서 제안하는 트라이코딩은 게임을 사용하여 학생 스스로가 프로그래밍 및 알고리즘을 학습할 수 있다. 트라이코딩은 기존의 블록기반 및 그림 기반의 프로그래밍 교육을 거친 학생 또는 처음 접하는 학생도 쉽게 게임을 통하여 프로그래밍에 대한 지식을 습득할 수 있게 설계를 하였다. 프로그래밍 언어는 기본적으로 영어를 기반으로 하고 있기 때문에 기초 영어에 대한 이해도가 없이는 이 게임을 진행하기는 힘들어, 추후 게임내에서 사용되는 기초영어 정도는 이 게임에서 학습할 수 있게 하는 시스템이 필요하다.