• Journal of Information Technology Services
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• v.16 no.4
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• pp.137-148
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• 2017

Researches on the Artificial Intelligence has been explosively activated in various fields since the advent of AlphaGo. Particularly, researchers on the application of multi-layer neural network such as deep learning, and various machine learning algorithms are being focused actively. In this paper, we described a development of an artificial intelligence Janggi game based on reinforcement learning algorithm and MCTS (Monte Carlo Tree Search) algorithm with accumulated game data. The previous artificial intelligence games are mostly developed based on mini-max algorithm, which depends only on the results of the tree search algorithms. They cannot use of the real data from the games experts, nor cannot enhance the performance by learning. In this paper, we suggest our approach to overcome those limitations as follows. First, we collects Janggi expert's game data, which can reflect abundant real game results. Second, we create a graph structure by using the game data, which can remove redundant movement. And third, we apply the reinforcement learning algorithm and MCTS algorithm to select the best next move. In addition, the learned graph is stored by object serialization method to provide continuity of the game. The experiment of this study is done with two different types as follows. First, our system is confronted with other AI based system that is currently being served on the internet. Second, our system confronted with some Janggi experts who have winning records of more than 50%. Experimental results show that the rate of our system is significantly higher.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2616-2622
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• 2010

This paper implements the algorithm for Janggi game robot based on network for the disabled people. The movement of target on janggi for them is designed using wireless robot and voice recognition. To remove obstacles, we implement the algorithm for moving object based on $A^{\ast}$ algorithm. We test the janggi game and certify effectiveness of moving object through the implementation of algorithm for them.

• Journal of Korea Game Society
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• v.1 no.1
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• pp.61-67
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• 2001

This paper describes a program which learns good strategies for two-poison, deterministic, zero-sum board games of perfect information. The program learns by simply playing the game against either a human or computer opponent. The results of the program's teaming of a lot of games are reported. The program consists of search kernel and a move generator module. Only the move generator is modified to reflect the rules of the game to be played. The kernel uses a temporal difference procedure combined with a backpropagation neural network to team good evaluation functions for the game being played. Central to the performance of the program is the search procedure. This is a the capture tree search used in most successful janggi playing programs. It is based on the idea of using search to correct errors in evaluations of positions. This procedure is described, analyzed, tested, and implemented in the game-teaming program. Both the test results and the performance of the program confirm the results of the analysis which indicate that search improves game playing performance for sufficiently accurate evaluation functions.

• Proceedings of the Korea Multimedia Society Conference
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• 2002.05c
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• pp.308-314
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• 2002

본 논문은 2인용 보드게임의 정보에 대한 전략을 학습할 수 있는 방법을 유전자기반 역전파 신경회로망과 Temporal Difference학습알고리즘을 이용하여 제안하였다. 학습의 과정은 역전파에 의한 초기학습에 이어 국부해의 단점을 극복하기 위하여 미세학습으로 유전자알고리즘을 이용하였다. 시스템의 구성은 탐색을 담당하는 부분과 기물의 수를 발생하는 부분으로 구성되어 있다. 수의 발생부분은 보드의 상태에 따라서 갱신되고, 탐색커널은 αβ탐색을 기본으로 유전자알고리즘을 이용하여 가중치를 최적화하는 유전자기반 역전파 신경회로망과 TD학습을 결합하여 게임에 대해 양호한 평가함수를 학습하였다. 일반적으로 많은 학습을 통하여 평가함수의 정확도가 보장되면 승률이 학습의 양에 비례함을 알 수 있었다.

• Journal of Korea Game Society
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• v.21 no.1
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• pp.43-54
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• 2021

This study deals with the changes in negative emotions a player feels upon defeat according to the intensity of randomness. By changing the interface related to randomness, we checked how the interaction between the user and the game affects the user's experience. The subjects of this study were 30 students of the Dept. of Game Engineering. The research tool used randomness and negative emotion measurement tools. For the experiment, a board game called "12Janggi" was used, and randomness was added to the 'board' and 'piece' of the game. The analysis shows that proper randomness reduces negative emotions, but excessive randomness increases negative emotions. Although randomness can reduce the negative emotion of defeat, it can be seen that it should be applied to the context of the game.

• Journal of the Institute of Electronics Engineers of Korea TE
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• v.39 no.1
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• pp.83-90
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• 2002

This paper proposed the strategy learning method by means of the fusion of Back-Propagation neural network and Q learning algorithm for two-person, deterministic janggi board game. The learning process is accomplished simply through the playing each other. The system consists of two parts of move generator and search kernel. The one consists of move generator generating the moves on the board, the other consists of back-propagation and Q learning plus $\alpha$$\beta$ search algorithm in an attempt to learn the evaluation function. while temporal difference learns the discrepancy between the adjacent rewards, Q learning acquires the optimal policies even when there is no prior knowledge of effects of its moves on the environment through the learning of the evaluation function for the augmented rewards. Depended on the evaluation function through lots of games through the learning procedure it proved that the percentage won is linearly proportional to the portion of learning in general.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.405-408
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• 2016

Games like Go, Chess, Janggi have helped to brain development of the people. These games are developed by computer program. And many algorithms have been developed to allow myself to play. The person winning chess program was developed in the 1990s. But game of go is too large number of cases. So it was considered impossible to win professional go player. However, with the use of MCTS(Monte Carlo Tree Search) and CNN(Convolutional Neural Network), the performance of the go algorithm is greatly improved. In this paper, using CNN and MCTS were proceeding development of go algorithm. Using the manual of go learning CNN look for the best position, MCTS calculates the win probability in the game to proceed with simulation. In addition, extract pattern information of go using existing manual of go, plans to improve speed and performance by using it. This method is showed a better performance than general go algorithm. Also if it is receiving sufficient computing power, it seems to be even more improved performance.

• Sim-seong Yeon-gu
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• v.32 no.2
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• pp.122-168
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• 2017

I tried to understand a folk tale "The half-boy" in terms of analytical psychology. In the story, a lady without children prayed to the Buddha. The white old man came and gave three fishes, but the cat ate half of it. So, she ate two and a half. She gave birth to two perfect sons. The third son had one arm, one leg, and one eye. They grew well. Brothers went to take the civil service examinations, and the half-boy followed. But two brothers did not like the half-boy coming along. So, brothers tied the half-boy to the rocks and trees, and he picked them up with force and gave them down to the yard of the house. And the half-boy followed his brothers again, and brothers tied him with kudzu and put him in front of the tiger. The half-boy won the tiger by betting with cutting kudzu. The half-boy stripped off the tiger's skin. The host coveted the tiger skin and they played with janggi. The half-boy won the game and was permitted to take host's daughter. The half-boy went with a string, a drum, a flea, and a bedbug. He teased host's people with these. The half-boy brought a virgin and lived well. "The Half-Boy" folktale is an old story spread throughout the country. There are similar stories in India and Africa. Unilateral figures are universally distributed archetypal images. In numerous cultures gods and spirits are being portrayed as unilateral figures. In the creation mythology, half-figure beings have immortality. In Indonesian and African folk tales, the half-born boy goes to heaven and merges with its half and becomes perfect. Some of one-sided spirits are harmful to humans but some of one-sided birds, chickens, and spirits are helpful to people. Sometimes half being is a cultural hero who steals grain from heaven or gets some advice how to use bamboo. There are stories that half body becomes a whole body afterwards. But in this folktale and most of the similar folktales, half-figure does not change and maintains half-figure to the end. And as a half-figure he does various great things and marries a virgin. The half-boy symbolizes a psychic experience born in the unconscious. The unconscious contents may seem strange and weird at first and the collective consciousness does not want to accept them. But the unconscious exerts greater power and brings vitality and creativity to consciousness. This folk tale seems to have compensated for the stubborn collective consciousness of our society, which was a Confucian class society. It also allows people to change their attitude toward disabled people and recognize strengths and creativity of the handicapped.