바둑은 적어도 2,500년 이상의 역사를 지녔고 그동안 인간 고유의 게임 영역으로 여겨왔으나, 2016년 컴퓨터 바둑인 알파고에 의해 제압된 마지막 보드게임이 되었다. 바둑에서의 사활문제는 컴퓨터 바둑을 구축 시 반 드시 해결해야 되는 기본 문제 영역이 된다. 연역적 추론은 이미 알고 있는 판단을 근거로 새로운 사실을 추 론하는 논리학의 용어이다. 본 논문에서는 연역적 추론을 위해 제약 충족 방법을 활용하여 사활문제와 직결 되는 3궁, 4궁, 5궁, 6궁의 원형 안형을 표현하는 4-튜플의 형식을 찾고자 했다. 이후 생성된 4-튜플의 형식 을 갖고 점 패턴 매칭을 활용하여 각 궁도의 원형 안형의 갯수를 파악하고자 했다. 실험 결과에 따른 4-튜플 형식의 갯수는 3궁 1개, 4궁 3개, 5궁 4개, 6궁 8개가 있음을 알 수 있었다. 또한 각 궁도의 원형 안형의 갯 수는 3궁 2개, 4궁 5개, 5궁 12개, 6궁 35개가 존재함을 찾아냈다. 마지막으로 컴퓨터 바둑에서의 사활문제 해결을 위해 원형 안형들을 4-튜플 형식의 변형인 5-튜플 형식으로도 제시하였다.

바둑게임은 중국에서 적어도 2,500년 전에 창안되었으며, 게임을 이기기 위해 상대방보다 더 많은 영역을 둘러싸는 것을 목표로 한다. 간단한 규칙에도 불구하고 바둑은 인공지능(AI) 분야에서 아주 복잡한 전략적인 보드게임이다. 몬테카를로 트리탐색(MCTS)은 국면 평가의 어려움을 극복하고 게임트리 내의 엄청난 분기수를 줄여주는 최상우선탐색 알고리즘이다. 컴퓨터바둑 게임에서 MCTS는 수많은 플레이아웃을 수행한 후, 게임트리 내에 있는 현재노드로부터 단말노드까지의 임의의 수순을 표본 추출하여 다음 후보 착수에 대한 승률을 근사적으로 계산해낸다. AlphaGo를 포함한 모든 강력한 컴퓨터바둑 프로그램은 컴퓨터바둑 게임 진행에 있어 MCTS를 이용하여 가장 유망한 착수를 구해왔다. 본 연구는 소형바둑 컴퓨터게임에 있어 순수 MCTS를 이용하여 가장 유망한 일련의 수순을 찾고자 했다. 실험결과에 의하면 순수 MCTS는 소형바둑에서 19줄바둑게임에서 벌어지는 포석, 중반전, 끝내기라는 3단계가 아닌 중반전과 끝내기라는 단지 2단계를 진행하였으며, 아울러 순수 MCTS는 맥과 연단수와 같은 하위개념의 지식을 이해 못하는 것을 보였다.

Monte-Carlo Tree Search (MCTS) is a best-first search algorithm to evaluate states of the game tree in game playing, and has been successfully applied to various games, especially to the game of Go. Upper Confidence Bounds for Trees (UCT), which is a variant of MCTS, uses the UCB1 formula as selection policy, and balances exploitation and exploration of the states. Rapid Action-Value Estimation (RAVE), which is a All-Moves-As-First (AMAF) heuristic, treats all moves in a simulation as the first move, and therefore updates the statistics of all children of the root node. In this paper, we evaluate the performance of RAVE and UCT playing against each other in the game of Tic-Tac-Toe. The experimental results show that the first player RAVE is much inferior to the second player UCT (13.0±0.7%); on the other hand, the first player UCT is far superior to RAVE (99.9±0.1%).

Go is an extremely complex strategic board game despite its simple rules and is the great challenging classic game for AI due to its enormous search space. The computer program AlphaGo finally defeated Fan Hui, the European Go champion, without handicaps on a full-sized 19 ×19 board in October 2015. Monte-Carlo Tree Search (MCTS) is a widely-used algorithm for game-tree search in game playing. MCTS based on statistical sampling is a best-first tree search technique to evaluate states; UCT which is a variant of MCTS uses the UCB1 formula as selection policy. In this paper, we evaluate the performance of MCTS and UCT playing against each other in the game of Tic-Tac-Toe. The experimental results show that the first player UCT is slightly superior to the second player MCTS (54.3±1.0%), the first player is always advantageous to the second player regardless of the MCTS and UCT players, and the result of each game should be a tie if both players do their best in Tic-Tac-Toe.

Go is an extremely complex strategic board game despite its simple rules. Recently computer Go based on MCTS plays at human-master level and also has defeated top professional players with handicap games in 19×19 Go. Before implementing computer Go, in this paper we show weakness of pure MC algorithm for playing robust Tic-Tac-Toe game and present alternative method to make up the weakness. Furthermore we show how UCB algorithm works for balancing exploration and exploitation in game tree and discuss the need of a hybrid algorithm combined with UCB and strategy based MCTS, for implementing an enhanced computer Go.

Evolutionary computation is a powerful tool for developing computer games. Back-propagation neural network(BPNN) was proved to be a universal approximator and genetic algorithm(GA) a global searcher. The game of Tic-Tac-Toe, also known as Naughts and Crosses, is often used as a test bed for testing new AI algorithms. We tried to recognize the strategic fitness of a finished Tic-Tac-Toe game when the parameters, such as a sequence of moves, its game depth and result, are provided. To implement this, we've constructed an evolutionary model using GA with back-propagation NNs(GANN). The experimental results revealed that GANN, in the very long training time, converges very slowly; however, performance of recognizing the strategic fitness does not meet we expected and, further, increase of the population size does not significantly contribute to the performance of GANN.

The game of Go is an oriental strategic board game originated from China at least more than 2,500 years ago. The Monte-Carlo Tree Search (MCTS) algorithm in Go is a method that uses a large number of simulations to approximately estimate the winning rate of candidate moves by sampling the game. The two computer Go programs called Crazy Stone and Mogo defeated human Go professionals on the 9⨯9 board in 2006. Prior to our implementing MCTS into computer Go, we tried to find out the best move sequence in playing Tic-Tac-Toe game as a test bed. The experimental results revealed that the first player should play the center to ensure the highest winning rate, and the game result becomes a draw if two players do their best.

One of the oldest board games in the world is the game of Go which is originated at least more than 2,500 years ago. In spite of its long history, the theoretical studies concerning to Go openings are still insufficient. We firstly used related-samples t-test using SPSS to the three countries' Go mean openings to find out their similarities and differences. Experimental result shows that there are no significant differences (p=.959) between Korean and Chinese mean openings, but meanwhile, there are just some slight similarities (p=.061) between Korean and Japanese mean openings. We secondly applied PCA and LDA classifiers with Euclidean distance to correctly classify a pro player's opening into his/her class obtained from the training openings. Result shows that the recognition rate (42.1%) of dependent LDA classifier is much better than that (27.9%) of PCA classifier; and also that dependent LDA classifier outperforms independent LDA classifier with the recognition rate of 35.0% .

Although the history of the game of Go is more than 2,500 years, the theoretical studies of Go are still insufficient. In recent years a lot of studies using Artificial Intelligent (AI) have been conducted, but they do not provide the prominent theoretical reality. We applied traditional Principal Component Analysis (PCA) algorithm to the Go openings, which are the early stage in Go, to analyze them especially focused on the Go game records of the Korean top 10 professional Go players. We firstly analyzed the number of most significant eigenvectors capturing most of variance. Experimental result shows that among the 361 eigenvectors the eight most significant eigenvectors capture most of the variance (96.2%). We secondly used PCA classifier with Euclidean distance to recognize a pro player's opening to a class obtained from the training openings. Result shows that the best average recognition rate of 22% is so much lower than the recognition rates reported in face recognition research.

바둑에 있어 사활 문제는 컴퓨터 바둑을 구현하기 위하여 반드시 극복되어져야 하는 기본적인 문제이다. 사활 문제와 같은 국부적인 문제를 풀기 위하여, 중요하게 고려되어야 할 사항은 어떻게 하면 게임 트리의 분기수와 그 깊이를 줄일 수 있느냐는 것이다. 본 논문에서는 게임 트리를 위한 첫 수들을 생성하기 위하여 휴리스틱 세력 함수로 눈 모양 분석이라는 초유의 방법을 적용하였다. 휴리스틱 세력 함수로 둘러싸인 돌들의 눈 모양을 분석하는 주요 목적은 아주 짧은 시간내에 둘러싸인 돌들이 살았는지, 미생(未生)인지 아니면 죽었는지를 판단하는 것이다. 만약 둘러싸인 돌들이 죽거나 미생일 경우가 높으면, 완전 게임 트리 내에서 최선의 수순을 찾아내기 위해 소요되는 엄청난 계산 시간을 절약할 수 있는 가능한 급소 점(첫 수)들로 사용될 수가 있다. 비록 눈 모양 분석기는 40% 미만의 정확도를 보였지만, 단순한 휴리스틱 세력함수로 된 눈 모양 분석기는 짧은 시간 내에 둘러싸인 돌들의 생사 여부를 판단하는 데 상당한 도움이 됨을 발견했다.

Korea has an agreement for cooperation with 31 countries, including the United States, Canada, Australia, and Japan. Under the agreement, the obligated items must be used for peaceful purposes, comply with nuclear non-proliferation and international safeguards, and obtain prior consent of shipment in case of enrichment, reprocessing, retransfer. Among them, the United States, Canada, and Australia have signed Administrative Arrangements of Cooperation Agreements (Supplementary Arrangements in Canada) for the international transfer and annual reports of obligated items. When operators submit an annual report, the government compiles and make the annual report based on the data. Ideally, the final report is submitted by the operator should be the national annual report, but in practice, discrepancies occur between sum of the operator’s and goverment’s. In order to resolve these problems and strengthen the linkage between exports contrpol and safeguards, our institute has begun the project to develop an ‘Obligation Tracking System for internationally controlled items (OTS)’. It is believed that obligated items which are unnecessarily included or omitted in annual report could be managed properly by developing OTS for life cycle of the items such as import, disposal/ termination or transfer to other countries. In case of nuclear material, especially, the characteristics of the facilities (e.g., bulk-handling facilities) must be considered and principles of fungibility, equivalence, and proportionality should be applied to materials. In order to computerize these procedures, we would like to propose to adopt the format of Code 10 for obligated item management. Code 10 is the form of the annex to the Korea-IAEA safeguards agreement which includes all records of inventory changes, import/export, and domestic movement of nuclear materials. It is expected to minimize discrepancies between operators’ annual reporting data and national annual reporting and further contribute to enhancing national trust and nuclear transparency.

In addition to Korea, various countries such as the United States, the United Kingdom, France, and China are designing small module-type reactors. In particular, a small modular reactor is the power of 300 MWe or less, in which the main equipment constituting the nuclear reactor is integrated into a single container. Depending on the purpose, small modular reactors are being developed to help daily life such as power, heating supply, and seawater desalination, or for power supply such as icebreakers, nuclear submarines, and spacecraft propellants. Small modular reactors are classified according to form. It can be classified into light-water reactors/ pressurized light-water reactors based on technology proven in commercial reactors, and non-lightwater reactors based on fuel and coolant type such as Sodium-cooled Fast Reactor, High temperature gas-cooled reactor, Very high temperature reactor and Moltenn salt reactor. SMRs, which are designed for various purposes, have the biggest difference from commercial nuclear reactors. The size of SMRs is as small as 1/5 of that of the commercial reactors. Several modules may be installed to generate the same power as commercial reactors. Because of the individually operation for each module, load follow is possible. Also, The reactor can be cooled by natural convection because the size is small enough. It is manufactured as a module, the construction period can be reduced. Depending on the characteristics of these SMRs, application for safeguards is considered. There are many things to consider in terms of safeguards. Therefore, it is IAEA inspection or other approaches for SMRs installed and remotely operated in isolated areas, data integrity for remote monitoring equipment to prevent the diversion of nuclear materials, verification method and material accountancy and control for new fuel types and reactors. Since SMR is more compact and technical intensive, safeguards should be considered at the design stage so that safeguards can be efficiently and effectively implemented, which is called the Safeguards by design (SBD) in the IAEA. In this paper, according to the characteristics of SMR, we will analyze the advantages/disadvantages from the point of view of safeguards and explain what should be considered.