• Journal of Korea Game Society
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• v.2 no.2
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• pp.37-45
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• 2002

Computer games could be regarded as simulation of the real world. Control problems of software agents have long been studied in the field of Artificial Intelligence (AI), resulting in giving a birth to the behavior-based approach. three main approaches might be categorized out of the history of AI study. First, Cognitivists propose that intelligence could be represented and manipulated in terms of symbols. Second, Connectionists claim that symbols could not be isolated but they are embedded in the body structure. Third, the behavior-based approach is an approach to AI which suggests that intelligence is dynamic property that exists nowhere but emerges in the relationship of an agent and the world including observers while the agent performs behavior. This paper explains and compares the three approaches to AI, then discusses the plausibility of the behavior-based approach and problems. Finally, this paper proposes application of behavior-based approach to computer games in terms of agent control.

• Journal of Korea Game Society
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• v.13 no.6
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• pp.43-52
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• 2013

Path finder is one of the very important algorithm of artificial intelligence and is a process generally used in many game fields. Path finder requires many calculation, so it exerts enormous influences on performances. To solve this, many researches on the ways to reduce the amount of calculate operations have been made, and the typical example is A* algorithm but it has unnecessary computing process, reducing efficiency. In this paper, to reduce the amount of calculate operations such as node search with costly arithmetic operations, we proposes the weight based pre-processing A* algorithm. The simulation was materialized to measure the efficiency of the weight based pre-process A* algorithm, and the results of the experiments showed that the weight based method was approximately 1~2 times more efficient than the general methods.

• Journal of Korea Multimedia Society
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• v.10 no.5
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• pp.631-641
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• 2007

The domestic game market is developmental in the form which is strange produces only the MMORPG. But the level of the intelligence elder brother character is coming to a standstill as ever. It uses a gene algorithm and the neural network from the dissertation which it sees and embodies the character which has a more superior intelligence the plan which to sleep and it presents it does. When also currently it is used complaring different artificial intelligence technologies and this algorism from the MMORPG, the efficiency proves is not turned over and explains the concrete algorithm it will be able to apply in the MMORPG and an embodiment method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.12
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• pp.4625-4647
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• 2020

The Generative Adversarial Networks, as one of the most creative deep learning models in recent years, has achieved great success in computer vision and natural language processing. It uses the game theory to generate the best sample in generator and discriminator. Recently, many deep learning models have been applied to the security field. Along with the idea of "generative" and "adversarial", researchers are trying to apply Generative Adversarial Networks to the security field. This paper presents the development of Generative Adversarial Networks. We review traditional generation models and typical Generative Adversarial Networks models, analyze the application of their models in natural language processing and computer vision. To emphasize that Generative Adversarial Networks models are feasible to be used in security, we separately review the contributions that their defenses in information security, cyber security and artificial intelligence security. Finally, drawing on the reviewed literature, we provide a broader outlook of this research direction.

• Journal of Science and Technology Studies
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• v.17 no.1
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• pp.5-39
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• 2017

In March 2016, the computer Go program, AlphaGo, defeated Sedol Lee, a Korean professional Go player of 9-dan rank. This victory by AlphaGo shows the rise in popularity of artificial intelligence (AI). Not only was this game a testament to machine performance, it was the type of game that extended the Turing test. When the interrogator cannot differentiate between human being and machine, the machine has passed the test. This article examines the interactions between AI and human beings and studies the social nature of intelligence through the AlphaGo case. Collins insists that knowledge or intelligence is social and embodied, and the interrogators in the Turing test can identify the difference between native members and non-members through their knowledge only. Applying this concept, AlphaGo, as subject A of this test, fulfilled its role of stirring up the classical "truth of human." Meanwhile, Lee as subject B, played to speak the truth by revealing his own qualities. Here, it is also important role that interrogators judge what it is. Many spectators, as interrogators, have intervened to confirm the border between human beings and machines by using their embodied and social knowledge.

• Journal of Korea Game Society
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• v.17 no.1
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• pp.7-16
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• 2017

The 3D game graphic technology has become an important factor in the contents field with the game contents development. In particular, game character technology provides a realistic technique and visual pleasure, as well as an intermediate step in the immersion of the game in which the game might create an optical illusion that enables the player to enjoy heroic adventure in the game. The high expression level of characters in 3D games is a key factor in the development process, with details and carefulness of the character setting work [3]. In this paper, we propose a character representative technique applied to mobile games using mathematical model of radiosity energy, spectral radiance model, and ray tracing model method using 3D unity game engine with sensible AI algorithm for game implementation. As a practical application to the game contents, it was found that the projection of the surface in the rendering process and the game simulation might change according to the lighting condition of the game content environment, so that the high quality of game characters was simulated.

• Journal of Korea Game Society
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• v.18 no.5
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• pp.23-30
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• 2018

With the development of ICT technology, the game industry is growing rapidly. However, due to the excessive play of the game, there are cases where normal life is difficult. It is necessary to study the diagnosis and countermeasures against such game addiction. This paper study a system for diagnosing game addiction based on game usage information of game users. In order to develop a game addiction diagnostic system, this study classifies game addiction and abuse users and collects and models log information in real game environment. In addition, the addiction and good use model of game users was used as a knowledge to diagnose the addiction of new game users. Through the experiment, we could confirm the meaningful results. Also, according to the result of the diagnosis, the service such as SMS and reporting was suggested.

• Journal of the Semiconductor & Display Technology
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• v.21 no.3
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• pp.110-113
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• 2022

Non-playable game character plays an important role in improving the concentration of the game and the interest of the user, and recently implementation of NPC with reinforcement learning has been in the spotlight. In this paper, we estimate an AI target tracking method via reinforcement learning, and implement an AI-based tracking agency of specific target object with avoiding traps through Unity ML-Agents Toolkit. The implementation is built in Unity game engine, and simulations are conducted through a number of experiments. The experimental results show that outstanding performance of the tracking target with avoiding traps is shown with good enough results.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.432-439
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• 2022

This paper introduces deliberative behavior tree using utility theory. The proposed approach combine the strengths of behavior trees and utility theory to implement complex behavior of AI agents in an easier and more concise way. To achieve this goal, we devised and implemented three types of additional behavior tree nodes, which evaluate utility values of its own node or its subtree while traversing and selecting its child nodes based on the evaluated values. In order to validate our approach, we implemented a sample scenario using conventional behavior tree and our proposed deliberative tree respectively. And then we compared and analyzed the simulation results.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.277-278
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• 2023

본 논문은 머신러닝 학습 도구인 Teachable Machine을 활용하여 모션 인식 러닝 액션 게임인 Dino Run Game을 개발하는 것을 목표로 한다. JavaScript, HTML, CSS를 사용하여 기본적인 게임 프레임워크를 구현하고, Google에서 개발한 Teachable Machine의 이미지 인식 모델을 활용하여 웹캠을 통해 사용자의 손 이미지를 인식한다. 이를 기반으로 게임 캐릭터를 제어함으로써 키보드를 사용하지 않고도 게임을 즐길 수 있도록 구현한다.