• Journal of Korea Game Society
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• v.13 no.2
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• pp.39-48
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• 2013

In MMORPGs(Massively Multi-player Online Role-Playing Games) a large number of players actively interact with one another in a virtual world. Therefore MMORGs must be able to quickly process real-time access requests and process requests from numerous gaming users. A key challenge is that the workload of the game server increases as the number of gaming users increases. To address this workload problem, many developers apply with distributed server architectures which use dynamic map partitioning and load balancing according to the server function. Therefore most MMORPG servers partition a virtual world into zones and each zone runs on multiple game servers. These methods cause of players frequently move between game servers, which imposes high overhead for data updates. In this paper, we propose a new architecture that apply with an arithmetic server dedicated to data operation. This architecture enables the existing game servers to process more access and job requests by reducing the load. Through mathematical modeling and experimental results, we show that our scheme yields higher efficiency than the existing ones.

• Information Systems Review
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• v.19 no.1
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• pp.123-145
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• 2017

This study empirically examines the effects of regulation on online gaming. Going beyond ad hoc heuristic approaches on individual behavior, we investigate the effects of regulation on dynamic changes of games or service providers. In particular, we propose three theoretical perspectives: social influence to investigate the regulation effect, the role of prior experience to determine the difference in the regulation effect size through users' prior experience, and network externalities to discover the difference in the regulation effect size according to the number of users on an online gaming platform. We use the vector autoregression methodology to model patterns of the co-movement of online games and to forecast game usage. We find that online gamers are heterogeneous. Therefore, policy makers should make suitable regulations for each heterogeneous group to effectively avoid generating gaming addicts without interrupting the economic growth of the online gaming industry.

• Journal of Korea Game Society
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• v.6 no.3
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• pp.3-12
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• 2006

Path-finding, one of the traditional Game A.I. problems, becomes an important issue to make games more realistic. Due to the limited resources in the computer system, path-finding systems sometimes produce a simplified and unrealistic path. The most relent researches have been focused on the path-finding avoiding only static obstacles. Various moving obstacles are however deployed in real games, a method avoiding those obstacles and producing a smooth path is necessary. In this paper, navigation mesh is used to represent 3D space and its topological characteristics are used for path-finding. Intellectual repulser and attractor are also used to avoid moving obstacles and to find an optimal path. We have evaluated the path produced by the method proposed in this paper and verified its usability in real game.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.41-50
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• 2021

Many game and financial apps have emulator detection functionality to defend against dynamic reverse engineering attacks. However, existing Android emulator detection methods have limitations in detecting the latest mobile game emulators that are similar to actual devices. Therefore, in this paper, we propose a method to effectively detect Android emulators for mobile games based on Houdini module and strings of a library. The proposed method detects the two emulators, Nox and LD Player through specific strings included in libc.so of bionic, and an analysis of the system call execution process and memory mapping associated with the Houdini module.

• Journal of Korea Game Society
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• v.16 no.2
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• pp.27-40
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• 2016

Predicting stealthy behaviors plays an important role in designing stealth games. It is, however, difficult to automate this task because human players interact with dynamic environments in real time. In this paper, we present a reinforcement learning (RL) method for simulating stealthy movements in dynamic environments, in which an integrated model of Q-learning with Artificial Neural Networks (ANN) is exploited as an action classifier. Experiment results show that our simulation agent responds sensitively to dynamic situations and thus is useful for game level designer to determine various parameters for game.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.3
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• pp.327-332
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• 2015

Educational robot was introduced as an effective educational tool is to foster scientific creativity and learn the basic principles of science are applied to change the configuration of the educational after-school learning kits for science education. SMEs as a tool to foster scientific creativity center and a variety of educational robot technology and the wide range of games for students and robotic technology development, existing e-Learning by downloading mp3 music or learning content for the robot, such as the provision of specialized content Although the technology is still being developed to take advantage of the professional community formation is insufficient side. Currently, one-point linkage drag Smart Touch control dynamic motor development does not need this motor development is possible for users to easily.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.137-149
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• 2006

In this paper, we suggest a message-based communication protocol and a dynamic role assignment mechanism for efficient cooperation and teamwork of agents in computer game environments. This role assignment mechanism is a new one different from both existing static and dynamic mechanisms, in which all decisions related with role assignment are made at once in design phase or execution phase. According to our mechanism, all possible role sets are determined in design phase. Detail decisions regarding which agent takes what role, however, are made in execution phase. This mechanism for role assignment can minimize the negotiation effort in execution phase. Therefore, this mechanism is quite effective especially in real-time multiagent environments. Through experiments, we show the superiority of the new dynamic role assignment mechanism.

• Proceedings of the Korea Society for Simulation Conference
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• 2001.10a
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• pp.321-324
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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 Beaming is the machine learning in which an agent learns from indirect, delayed reward an optimal policy to choose sequences of actions that produce the greatest cumulative reward. Therefore the reinforcement loaming is different from supervised teaming in the sense that there is no presentation of input-output pairs as training examples. Furthermore, model-free reinforcement loaming algorithms like Q-learning do not require defining or loaming 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 space 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 Korea Game Society
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• v.15 no.5
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• pp.99-108
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• 2015

To identify the location of the object and improve the realism in 3D game, shadow mapping is widely used to compute the depth values of vertices in view of the light position. Since the depth value of the shadow map is calculated by the world coordinate, the depth values of the static object don't need to be updated. In this paper, (1) in order to improve the rendering speed, using multiple render targets the depth values of static objects stored only once are separated from those of dynamic objects stored each time. And (2) in order to improve the shadow quality in the quarter view 3D game, the position of the light is located close to dynamic objects traveled along the camera each time. The effectiveness of the proposed method is verified by the experiments according to the different static and dynamics object configuration in 3D game.

• The KIPS Transactions:PartA
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• v.13A no.3 s.100
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• pp.223-230
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• 2006

A MMORPG(Massively Multiplayer Online Role-Playing Game) is an online role-playing game in which a large number of players can interact with each other in the same world at the same time. Most of them require significant hardware requirements(e.g., servers and bandwidth), and dedicated support staff. Despite the efforts of developers, users often cite overpopulation, lag, and poor support as problems of games. In this paper, a dynamic load balancing method for MMORPGS is proposed. It tries to adapt to dynamic change of population by using dynamic map-partition method with VML(Virtual Map Layer) which consists of fields, sector groups, sectors, and cells. From the experimental results, our approach achieves about $23^{\sim}67%$ lower loads for each field server. By the modification to Virtual Area Layer, we can easily manage problems that come from changes of map data, resources' status, and users' behavior pattern.