{"title":"基于树的非编码节点语法演化","authors":"Marina de la Cruz López, O. Garnica, J. Hidalgo","doi":"10.1145/3583133.3596944","DOIUrl":null,"url":null,"abstract":"Grammar-guided genetic programming is a type of genetic programming that uses a grammar to restrict the solutions in the exploration of the search space. Different representations of grammar-guided genetic programming exist, each with specific properties that affect how the evolutionary process is developed. We propose a new representation that uses a tree structure with non-encoding nodes for the individuals in the population, a.k.a. Tree-Based Grammatical Evolution with Non-Encoding Nodes. Each tree's node has a set of children nodes and an associated number that determines which are used in decoding the solution and which are non-encoding nodes. This representation increases the size and complexity of the individuals while performing a more exhaustive exploration of the solution space. We compare the performance of our proposal with state-of-the-art genetic programming algorithms for the 11-multiplexer benchmark, showing encouraging results.","PeriodicalId":422029,"journal":{"name":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Tree-Based Grammatical Evolution with Non-Encoding Nodes\",\"authors\":\"Marina de la Cruz López, O. Garnica, J. Hidalgo\",\"doi\":\"10.1145/3583133.3596944\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Grammar-guided genetic programming is a type of genetic programming that uses a grammar to restrict the solutions in the exploration of the search space. Different representations of grammar-guided genetic programming exist, each with specific properties that affect how the evolutionary process is developed. We propose a new representation that uses a tree structure with non-encoding nodes for the individuals in the population, a.k.a. Tree-Based Grammatical Evolution with Non-Encoding Nodes. Each tree's node has a set of children nodes and an associated number that determines which are used in decoding the solution and which are non-encoding nodes. This representation increases the size and complexity of the individuals while performing a more exhaustive exploration of the solution space. We compare the performance of our proposal with state-of-the-art genetic programming algorithms for the 11-multiplexer benchmark, showing encouraging results.\",\"PeriodicalId\":422029,\"journal\":{\"name\":\"Proceedings of the Companion Conference on Genetic and Evolutionary Computation\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the Companion Conference on Genetic and Evolutionary Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3583133.3596944\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Companion Conference on Genetic and Evolutionary Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3583133.3596944","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Tree-Based Grammatical Evolution with Non-Encoding Nodes
Grammar-guided genetic programming is a type of genetic programming that uses a grammar to restrict the solutions in the exploration of the search space. Different representations of grammar-guided genetic programming exist, each with specific properties that affect how the evolutionary process is developed. We propose a new representation that uses a tree structure with non-encoding nodes for the individuals in the population, a.k.a. Tree-Based Grammatical Evolution with Non-Encoding Nodes. Each tree's node has a set of children nodes and an associated number that determines which are used in decoding the solution and which are non-encoding nodes. This representation increases the size and complexity of the individuals while performing a more exhaustive exploration of the solution space. We compare the performance of our proposal with state-of-the-art genetic programming algorithms for the 11-multiplexer benchmark, showing encouraging results.