• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.108-114
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• 2019

In this paper, we propose an intelligent vocabulary recommendation agent that automatically provides vocabulary corresponding to game-based learners' needs and requirements in the mobile education augmented reality game environment. The proposed agent reflects the characteristics of mobile technology and augmented reality technology as much as possible. In addition, this agent includes a vocabulary reasoning module, a single game vocabulary recommendation module, a battle game vocabulary recommendation module, a learning vocabulary list Module, and a thesaurus module. As a result, game-based learners' are generally satisfied. The precision of context vocabulary reasoning and thesaurus is 4.01 and 4.11, respectively, which shows that vocabulary related to situation of game-based learner is extracted. However, In the case of satisfaction, battle game vocabulary(3.86) is relatively low compared to single game vocabulary(3.94) because it recommends vocabulary that can be used jointly among recommendation vocabulary of individual learners.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.4
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• pp.538-544
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• 2009

As the world game marcket has been recording weak growth, the development of new gane concept is required to attract the gamer's attention from those who were fed up with the previous game paradigm. Recently, the game which can recognize the player's motions and provide new interaction between the game and user is more popular than ever before. In the games with somesthesia based on Virtual Reality, the sense of the reality is considered the most important factor for drawing immersion from the gamers. In this work, a new type of 3-axis accelerometer based interactive game interface which can effectively recognize the gamer' motion is suggested. Furthermore, various experiments are carried out to verify the effectiveness of the proposed scheme.

• Journal of Korea Game Society
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• v.9 no.4
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• pp.81-88
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• 2009

In this paper, I suggested a way for searching a path of the intelligent character in an action game by using a genetic algorithm. This realized the algorithm which enables not only to chose the nearest path but also to search the optimum path by using genetic algorithm. In this case, if the codes of chromosomes are applied as they are, a lot of lethal genes could occur. In order to solve such a problem, I used a splicing method, one of the DNA's behavior characteristics. The intelligent character searched out a optimum pass as well as a shortcut path with one treatment by using the characteristic of a genetic algorithm which generates multiple candidate solutions in the search process.

• Journal of the Korea Society of Computer and Information
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• v.11 no.4 s.42
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• pp.17-25
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• 2006

An intelligent game has been studied for some time, and the main purpose of the study was to win against human by enhancing game skills. But some commercial games rather focused on adaptation of the user's behavior in order to bring interests on the games. In this study, we are suggesting an adaptive reinforcement learning algorithm, which focuses on the adaptation of user behavior. We have designed and developed the Othello game, which provides large state spaces. The evaluation of the experiment was done by playing two reinforcement learning algorithms against Min-Max algorithm individually. And the results show that our approach is playing more improved learning rate, than the previous reinforcement learning algorithm.

• Journal of Korea Game Society
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• v.19 no.6
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• pp.5-14
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• 2019

In this paper, we propose a modeling and simulation of group behavioral movement of pedestrians using Agent based and Cellular Automata model in intelligent game environment. The social behaviors of the crowds are complex and important, and based on this, the prototype game-model was implemented to show the crowd interaction on AB and CA in the game environment. Our experiment revealed the promise of group behaviour as a cost-efficient, yet accurate platform for researching crowd behaviour in risk situations with real models.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.165-170
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• 2023

This study focuses on the development of intelligent combat robot systems for future warfare. The research is structured as follows: First, the introduction presents the rationale for researching intelligent combat robots and their potential to become game changers in future warfare. Second, in the context of the intelligent robot paradigm, this study proposes the need for military organizations to innovate their combat concepts and weapon systems through the effective utilization of Artificial Intelligence, Cognitive, Biometric, and Mechanical technologies. This forms the theoretical background of the study. Third, the analysis of intelligent robot systems considers five examples: humanoid robots, jumping robots, wheeled and quadrupedal pack robots, and tank robots. Finally, the discussion and conclusion propose that intelligent combat robots should be selected as game changers in military organizations for future warfare, and suggest further research in this area.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.4
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• pp.420-430
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• 2003

This paper presents an immersive multimodal Gumdo simulation game that allows a user to experience the whole body interaction with an intelligent cyber fencer. The proposed system consists of three modules: (i) a nondistracting multimodal interface with 3D vision and speech (ii) an intelligent cyber fencer and (iii) an immersive feedback by a big screen and sound. First, the multimodal Interface with 3D vision and speech allows a user to move around and to shout without distracting the user. Second, an intelligent cyber fencer provides the user with intelligent interactions by perception and reaction modules that are created by the analysis of real Gumdo game. Finally, an immersive audio-visual feedback by a big screen and sound effects helps a user experience an immersive interaction. The proposed system thus provides the user with an immersive Gumdo experience with the whole body movement. The suggested system can be applied to various applications such as education, exercise, art performance, etc.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.3
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• pp.363-368
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• 2005

Artificial life is a science studying artificial systems that implement various behavioral characteristics of lives as an attempt of applying some features found in living creatures to artificial intelligent objects in virtual worlds. Attempts and researches are actively being made to apply human needs to games and express them through artificial life. Human needs and the expression of the needs are extremely diverse and complicated, so they cannot be modeled in a specific way. Thus this study modeled game AI object needs using AHP, which is a useful model in solving problems quantitatively through basic observation of human nature, analytic thinking, measuring, etc. In addition, the modeled game AI object needs were examined through the analysis of performance sensitivity and their applicability to actual games was assessed with example.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2361-2368
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• 2009

Recently AI(Artificial Intelligence) is one of the issues in the on-line game, a research that a game character seems to be realistic and is progressing using AI technique. Especially NPC is an important part of the AI researches of on-line game, and it is concerned by a game player and an architect. We proposed an intelligent agent framework to implement the NPC technique after studying the NPC technique using context awareness that reacts to the PC(Player Character) actively. Also, it can be developed gradually, and apply to various application because it has the capability to of adding an agent or deleting an agent easily.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.1
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• pp.60-71
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• 2015

In this paper, a matrix game is considered in which the elements are represented as Z-numbers. The objective is to formalize the human capability for solving decision-making problems in uncertain situations. A ranking method of Z-numbers is proposed and used to define pure and mixed strategies. These strategies are then applied to find the optimal solution to the game problem with an induced pay off matrix using a min max, max min algorithm and the multi-section technique. Numerical examples are given in support of the proposed method.