{"title":"用蒙特卡罗树搜索求解Nurikabe","authors":"Ehsan Futuhi, Shayan Karimi","doi":"10.1109/ICCIA49625.2020.00014","DOIUrl":null,"url":null,"abstract":"Puzzle solving with AI is becoming one of the hot topic fields in computer science. The algorithmic challenges that are laid behind this topic , make it more attractive. One of these NP-complete puzzles that is hard to solve for human being is Nurikabe Puzzle . few methods have been developed for solving this puzzle that have a poor performance in time and memory. Monte-Carlo Tree Search(MCTS) is a famous reinforcement algorithm that have been used in many Logical games .In this article we use Monte-Carlo Tree Search method for creating the efficient method that performs well on time that it takes for solving the puzzle .no one have ever used this method for solving this problem and also we test our algorithm with a wide range of test cases from easy to hardest ones.","PeriodicalId":237536,"journal":{"name":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Solving Nurikabe with Monte-Carlo Tree Serach\",\"authors\":\"Ehsan Futuhi, Shayan Karimi\",\"doi\":\"10.1109/ICCIA49625.2020.00014\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Puzzle solving with AI is becoming one of the hot topic fields in computer science. The algorithmic challenges that are laid behind this topic , make it more attractive. One of these NP-complete puzzles that is hard to solve for human being is Nurikabe Puzzle . few methods have been developed for solving this puzzle that have a poor performance in time and memory. Monte-Carlo Tree Search(MCTS) is a famous reinforcement algorithm that have been used in many Logical games .In this article we use Monte-Carlo Tree Search method for creating the efficient method that performs well on time that it takes for solving the puzzle .no one have ever used this method for solving this problem and also we test our algorithm with a wide range of test cases from easy to hardest ones.\",\"PeriodicalId\":237536,\"journal\":{\"name\":\"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)\",\"volume\":\"79 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCIA49625.2020.00014\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 5th International Conference on Computational Intelligence and Applications (ICCIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCIA49625.2020.00014","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Puzzle solving with AI is becoming one of the hot topic fields in computer science. The algorithmic challenges that are laid behind this topic , make it more attractive. One of these NP-complete puzzles that is hard to solve for human being is Nurikabe Puzzle . few methods have been developed for solving this puzzle that have a poor performance in time and memory. Monte-Carlo Tree Search(MCTS) is a famous reinforcement algorithm that have been used in many Logical games .In this article we use Monte-Carlo Tree Search method for creating the efficient method that performs well on time that it takes for solving the puzzle .no one have ever used this method for solving this problem and also we test our algorithm with a wide range of test cases from easy to hardest ones.