• Journal of Korea Game Society
• /
• v.14 no.6
• /
• pp.39-48
• /
• 2014

Go is an extremely complex strategy board game despite its simple rules. By using MCTS, the computer Go programs with handicap game have been defeated human Go professionals. MCTS is based on the winning rate estimated by MC simulation rather than strategy concept. Meanwhile Genetic algorithm equipped with an adequate fitness function can find out the best solutions in the game. The game of Tic-Tac-Toe, also known as Naughts and Crosses, is one of the most popular games. We tried to find out the best strategy in the game of Tic-Tac-Toe. The experimental result showed that Genetic algorithm enables to find efficient strategies and can be applied to other board games such as Go and chess.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2007.05a
• /
• pp.717-719
• /
• 2007

바둑판에 놓인 돌의 위치를 표기하기 위한 전통적인 방식은 좌상귀를 기점으로 삼는 것이다. 그러나 이 방식은 직관성과 편리성이 떨어지기 때문에 천원 기점 방식과 각 귀 기점 방식이 제안되 었다. 본 연구에서는 기존의 각 귀 기점 방식의 문제점을 개선하여 좀 더 직관적인 좌표 시스템을 제안한다.

• The Korean Publising Journal, Monthly
• /
• s.224
• /
• pp.12-12
• /
• 1997

생명공학 같은 과학이론에서부터 미술사.군사학.바둑.컴퓨터 등 다양한 영역의 전문가들이 소설을 출간, 색다른 재미와 참신한 소재를 제공하는 역할을 하고 있다.

• Journal of Korea Game Society
• /
• v.15 no.5
• /
• pp.109-118
• /
• 2015

The game of Go originated from ancient China is regarded as one of the most difficult challenges in the filed of AI. Over the past few years, the top computer Go programs based on MCTS have surprisingly beaten professional players with handicap. MCTS is an approach that simulates a random sequence of legal moves until the game is ended, and replaced the traditional knowledge-based approach. We applied the UCT algorithm which is a MCTS variant to the game of Tic-Tac-Toe for finding the best first move, and compared it with the result generated by a pure MCTS. Furthermore, we introduced and compared the performances of epsilon-Greedy algorithm and UCB algorithm for solving the Multi-Armed Bandit problem to understand the UCB.

• Journal of the Korea Society of Computer and Information
• /
• v.14 no.11
• /
• pp.31-40
• /
• 2009

The most common cleaning methods of cleaning robot can be divided into two categories: the random and the boustrophedon method. A cleaning robot using the random method moves straight until it bumps into an obstacle. If it collides with an obstacle, the cleaning robot turns a specific angle and continues moving straight. Therefore, the random method often tends to clean the already clean area repeatedly. In addition, it takes a long time to complete cleaning. A cleaning robot using the boustrophedon method moves straight until it collides with an obstacle. If it meets an obstacle, the cleaning robot moves to the next uncleaned space through turning and moving ahead. when resuming cleaning from the new region, a cleaning robot moves in the direction opposite to the direction of the previous cleaning. Because the boustrophedon method cleans a cleaning space more densely, its performance is excellent in an obstacle-free space or a small space. However, In a space with obstacles or a complex structure, it takes a long time to complete the cleaning work. Cleaning should be systematically approached with a good understanding of the work area. The virtual map-based cleaning robot proposed in this paper cleaned a work space efficiently. The efficiency of the proposed method was measured through simulation.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2013.01a
• /
• pp.17-18
• /
• 2013

이 논문에서는 저비용 고효율 청소 로봇을 구현하기 위한 효율적 주행 기법을 발굴하기 위하여 다양한 주행 기법들을 제안하고, 시뮬레이션 도구를 이용하여 실험한 후 그 결과를 비교, 분석하였다. 이 논문에서 저비용이라는 것은 전방에 하나의 근접 센서만을 갖는 단순한 구조의 청소 로봇을 의미하며, 이전 주행 경로나 장애물에 대한 영상 정보 등은 물론 좌우 상태에 대한 정보없이 진행 경로 상에 장애물의 존재 여부만으로 청소를 수행할 수 있는 청소 로봇을 의미한다. 이 논문에서 제안한 여러 주행기법들을 비교 분석한 결과, 바둑판식 주행 기법의 패턴에 주행 중 진행 방향을 0.05의 확률로 좌우 90도 방향으로 랜덤 변경하는 주행 기법이 가장 효율적인 주행 기법임을 확인할 수 있었다.

• Journal of Korea Game Society
• /
• v.9 no.1
• /
• pp.105-114
• /
• 2009

In the game of Go, the life-and-death problem is a fundamental problem to be definitely overcome when implementing a computer Go program. To solve local Go problems such as life-and-death problems, an important consideration is how to tackle the game tree's huge branching factor and its depth. The basic idea of the experiment conducted in this article is that we modelled the human behavior to get the recognized first moves to kill the surrounded group. In the game of Go, similar life-and-death problems(patterns) often have similar solutions. To categorize similar patterns, we implemented Kohonen Neural Network(KNN) based clustering and found that the experimental result is promising and thus can compete with a pattern matching method, that uses supervised learning with a neural network, for solving life-and-death problems.

• Journal of Korea Game Society
• /
• v.21 no.6
• /
• pp.31-40
• /
• 2021

Go has a history of more than 2,500 years, and the life-and-death problems in Go is a fundamental problem domain that must be solved when implementing a computer Go. We attempted to determine the numbers of prototypical eye shapes with 3, 4, 5, and 6 eyes that are directly related to the life-and-death problems, and to classify the prototypical eye shapes represented in 4-tuple forms. Experiment was conducted by Monte-Carlo method and point pattern matching. According to the experimental results, the numbers of prototypical eye shapes were 2 for 3-eye, 5 for 4-eye, 12 for 5-eye, and 35 for 6-eye shapes. Further, using a 4-tuple form, we classified prototypical eye shapes into 1 for 3-eye, 3 for 4-eye, 4 for 5-eye, and 8 for 6-eye shapes.

• The Korean Publising Journal, Monthly
• /
• s.172
• /
• pp.6-6
• /
• 1995

90년대 들어 지속적인 불황에 시달리던 출판사들이 총 4천억원이 넘는 만화출판물시장에 눈을 돌리기 시작했다. '적어도 손해는 보지 않는다'는 여론으로 발빠른 확산이 이뤄졌고 지금은 과학과 철학, 바둑이나 컴퓨터 역사에 이르기까지 다양한 교양만화들이 선보이고 있다. 변화의 벽에 부딪친 출판계에 만화출판은 새로운 가능성을 보여준다.

• TTA Journal
• /
• s.165
• /
• pp.58-59
• /
• 2016

세간의 화제가 되었던 이세돌 9단 vs 알파고 대결. 난공불락이라 여겼던 바둑에서조차 인공지능이 승리를 거두면서 전 세계는 과학기술 발전에 놀랐고, 인공지능의 무한한 가능성에 감탄했다. 컴퓨터가 사람처럼 정보를 이해 판단하고 더 나아가 추론에 창의성까지 발휘하면서 사람들은 인공지능이 인간의 생각을 뛰어넘을 거라 생각한다. 그런데 과연 그럴까?