• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.59-64
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• 2001

The robot soccer simulation game is a dynamic multi-agent environment. In this paper we suggest a new reinforcement learning approach to each agent's dynamic positioning in such dynamic environment. Reinforcement learning is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to chose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement learning is different from supervised learning in the sense that there is no presentation of input pairs as training examples. Furthermore, model-free reinforcement learning algorithms like Q-learning do not require defining or learning any models of the surrounding environment. Nevertheless it can learn the optimal policy if the agent can visit every state- action pair infinitely. However, the biggest problem of monolithic reinforcement learning is that its straightforward applications do not successfully scale up to more complex environments due to the intractable large space of states. In order to address this problem. we suggest Adaptive Mediation-based Modular Q-Learning (AMMQL)as an improvement of the existing Modular Q-Learning (MQL). While simple modular Q-learning combines the results from each learning module in a fixed way, AMMQL combines them in a more flexible way by assigning different weight to each module according to its contribution to rewards. Therefore in addition to resolving the problem of large state effectively, AMMQL can show higher adaptability to environmental changes than pure MQL. This paper introduces the concept of AMMQL and presents details of its application into dynamic positioning of robot soccer agents.

• Journal of the Korea Society of Computer and Information
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• v.25 no.8
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• pp.111-117
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• 2020

Recently, with the high interest of machine learning, the need for educational controllers to interface with physical devices has increased. However, existing controllers are limited in terms of high cost and area of utilization for educational purposes. In this paper, motion control controllers using brain waves are proposed for the purpose of students' machine learning applications. The brain motion that occurs when imagining a specific action is measured and sampled, then the sample values were learned through Tensor Flow and the motion was recognized in contents such as games. Movement variation for motion recognition consists of directionality and jump motion. The identification of the recognition behavior is sent to a game produced by an Unreal Engine to operate the character in the game. In addition to brain waves, the implemented controller can be used in various fields depending on the input signal and can be used for educational purposes such as machine learning applications.

• Journal of Digital Convergence
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• v.14 no.9
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• pp.447-452
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• 2016

Designers need to manage their copyrights. Designers be placed in both situations. The two situations is sometimes the case that infringes their copyrights and infringes the copyrights of others. But most designers do not know what to do to deal with this situation. Designers have to judge a lot of things for themselves. Designers should inform the user that you have infringed my copyright. And they will have to think about the legal proceedings. This paper was written based on the legal process, conducted from 2012 to 2014. Copyright infringement countermeasures for designers through this case were investigated. And to organize a correspondence course was organized personal correspondence, legal action, ruling process. The study of the processes for copyright holders themselves to respond to the piracy situation is needed.

• Journal of Korea Game Society
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• v.11 no.6
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• pp.115-125
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• 2011

Recently, a sharp increases of users of smartphone is not only cause an rapid growth smartphone-games market, but also secured it's position as a high value market. thus have to begets a multilateral study to the smartphone of newly-rising. however the earlier studies were researched previous smartphone, despite extended research is needed for smartphone-games. therefore the study's purpose is to draw a main factors it has a decisive effect for recommendation and sustainable-usage through recognizing the cause-and-effect relationship with purchase intention, purchase action, satisfaction, recommendation, and sustainable usage that based purchase-effect-factors of smartphone-games. for this study the questionnaire of 293 was taken. and structural equation model was adopted to analyze this study.

• The KIPS Transactions:PartB
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• v.10B no.1
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• pp.1-12
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• 2003

In this paper, we Introduce the Unreal Tournament (UT) game and the Gamebots system. The former it a well-known 3D first-person action game and the latter is an intelligent agent research testbed based on UT And then we explain the design and implementation of KGBot, which is an intelligent non-player character deploying effectively within the 3D virtual environment provided by UT and the Gamebots system. KGBot is a bot client within the Gamebots System. KGBot accomplishes its own task to find out and dominate several domination points pro-located on the complex surface map of 3D virtual environment KGBot adopts UM-PRS as its control engine, which is a general BDI agent architecture. KGBot contains a hierarchical knowledge base representing its complex behaviors in multiple layers. In this paper, we explain details of KGBot's Intelligent behaviors, tuck af locating the hidden domination points by exploring the unknown world effectively. constructing a path map by collecting the waypoints and paths distributed over the world, and finding an optimal path to certain destination based on this path graph. Finally we analyze the performance of KGBot exploring strategy and control engine through some experiments on different 3D maps.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.83-90
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• 2024

In this paper, we propose a solution to apply a proximity voice dialog system to voice dialog technology, one of the interaction systems in multimedia environments. A voice dialog between multiple users in a multimedia space is designed by adjusting the volume of the voice according to the distance between the user avatars and muting the user who is beyond the audible distance. The main feature of this research is a reliable UDP-based active server system that delivers low-quality voice data to users who are far away based on distance and does not transmit voice data to users who enter the inaudible area for economic development. The performance of the proposed system was measured in a previously completed project based on the Unity game engine, and it is expected that the system proposed in this research will be actively used in environments that provide interaction between multiple users such as met averse content and real-time battle action games.

• Journal of Information Processing Systems
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• v.8 no.3
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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.

• Cartoon and Animation Studies
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• s.20
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• pp.75-86
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• 2010

Recently, as the number of female players has increased rapidly, the electronic gaming industry has begun to look at ways to appeal to the largely untapped female market. According to the latest game market investigative report by China Internet Network Information Center (CNNIC), the total number of game players in China increased by 24.8% in 2009, reached 69,130,000 people, and 38.9% of them are female players. This growth in the number of female player is corroborated by a series of investigative reports from IResearch Company in Shanghai, China: from 2003 to 2009, the number of female players grew from 8% to more than 49%. Therefore, no matter how much attention the game production companies have given to male players or how they have ignored the female players before, the companies would be sensible to face up this reality and adjust their marketing policy a bit more. This article analyzes gender preferences in video games which shows that male players are more likely to be attracted to elements of aggression, violence, competition and fast action in electronic game-playing, while female players are drawn to emotional and social aspects of the games such as an understanding of character relationships. The literatures cited indicates that female players also show apparent preference for games with familiar environments, games that allow players to work together, games that have more than one way to win, and games in which characters do not die. It also discusses the characteristics of female-friendly games from the aspect of emotion, pointing out that the simulation games involving pet, dressing-up, and social simulation games are very popular with female players. Because these are the most suitable game types to fill with emotions of love, share, jealousy, superiority, mystery, these are absolutely attractive to female players. Finally, in accord with the above, I propose some principles of designing female-oriented games, including presenting a good-looking leading character, making the story interesting with "live" NPCs(Non-Playing Characters), and finding ways to satisfy female nature instincts such as taking care of others and the inborn interest of classifying and selecting.

• Archives of design research
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• v.17 no.2
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• pp.463-470
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• 2004

This paper studied tangible interaction design of VR platform and its applications that are economic In development process and cost, flexible by contents and installation conditions, and that has business potential for consumer market. The design solution uses video based virtual world and tangible interaction by motion tracking. Our platform enables a user to monitor their action and to collaborate with other users of remote place within attractive interaction feedback. We developed two design applications, Glass Xylophone 2003 and VR Class, in our platform. Glass Xylophone 2003 provides interactive music performance and helps self practice of glass xylophone. VR Class gives more serious distance learning experience with tutoring and group collaboration. They are presented in public exhibitions and tested by exhibition visitors. They showed application potential of this design solution in interactive game, distance learning, and entertainment field.

• Journal of Energy Engineering
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• v.26 no.2
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• pp.93-98
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• 2017

This paper aims to examine how gamification strategies lead to the changes in consumers' perspectives and behaviors on energy savings. Since gamification strategies began to be widely used in the late 2010s, the strategies have been extensively applied to a variety of industries and applications, including the field of energy savings. As energy saving practices adopting gamification strategies reflect the attributes of game, citizens can be pleased to participate in energy saving activities. Also, the gamification strategies are expected to raise citizens' awareness to the necessity of reducing energy consumption. Therefore, considering the subjects and specific objectives, the action plans for applying gamification strategies to energy saving programs are required to be established to meet the demand of new services on energy savings.