{"title":"Homomorphisms and Embeddings of STRIPS Planning Models","authors":"Arnaud Lequen, Martin C. Cooper, Frédéric Maris","doi":"10.1111/coin.70013","DOIUrl":null,"url":null,"abstract":"<p>Determining whether two STRIPS planning instances are isomorphic is the simplest form of comparison between planning instances. It is also a particular case of the problem concerned with finding an isomorphism between a planning instance <span></span><math>\n <semantics>\n <mrow>\n <mi>P</mi>\n </mrow>\n <annotation>$$ P $$</annotation>\n </semantics></math> and a sub-instance of another instance <span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mrow>\n <mi>P</mi>\n </mrow>\n <mrow>\n <mo>′</mo>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {P}^{\\prime } $$</annotation>\n </semantics></math>. One application of such a mapping is to efficiently produce a compiled form containing all solutions to <span></span><math>\n <semantics>\n <mrow>\n <mi>P</mi>\n </mrow>\n <annotation>$$ P $$</annotation>\n </semantics></math> from a compiled form containing all solutions to <span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mrow>\n <mi>P</mi>\n </mrow>\n <mrow>\n <mo>′</mo>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {P}^{\\prime } $$</annotation>\n </semantics></math>. We also introduce the notion of <i>embedding</i> from an instance <span></span><math>\n <semantics>\n <mrow>\n <mi>P</mi>\n </mrow>\n <annotation>$$ P $$</annotation>\n </semantics></math> to another instance <span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mrow>\n <mi>P</mi>\n </mrow>\n <mrow>\n <mo>′</mo>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {P}^{\\prime } $$</annotation>\n </semantics></math>, which allows us to deduce that <span></span><math>\n <semantics>\n <mrow>\n <msup>\n <mrow>\n <mi>P</mi>\n </mrow>\n <mrow>\n <mo>′</mo>\n </mrow>\n </msup>\n </mrow>\n <annotation>$$ {P}^{\\prime } $$</annotation>\n </semantics></math> has no solution-plan if <span></span><math>\n <semantics>\n <mrow>\n <mi>P</mi>\n </mrow>\n <annotation>$$ P $$</annotation>\n </semantics></math> is unsolvable. In this paper, we study the complexity of these problems. We show that the first is GI-complete and can thus be solved, in theory, in quasi-polynomial time. While we prove the remaining problems to be NP-complete, we propose an algorithm to build an isomorphism when possible. We report extensive experimental trials on benchmark problems that demonstrate conclusively that applying constraint propagation in preprocessing can greatly improve the efficiency of a SAT solver.</p>","PeriodicalId":55228,"journal":{"name":"Computational Intelligence","volume":"40 6","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/coin.70013","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Intelligence","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/coin.70013","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Determining whether two STRIPS planning instances are isomorphic is the simplest form of comparison between planning instances. It is also a particular case of the problem concerned with finding an isomorphism between a planning instance and a sub-instance of another instance . One application of such a mapping is to efficiently produce a compiled form containing all solutions to from a compiled form containing all solutions to . We also introduce the notion of embedding from an instance to another instance , which allows us to deduce that has no solution-plan if is unsolvable. In this paper, we study the complexity of these problems. We show that the first is GI-complete and can thus be solved, in theory, in quasi-polynomial time. While we prove the remaining problems to be NP-complete, we propose an algorithm to build an isomorphism when possible. We report extensive experimental trials on benchmark problems that demonstrate conclusively that applying constraint propagation in preprocessing can greatly improve the efficiency of a SAT solver.
期刊介绍:
This leading international journal promotes and stimulates research in the field of artificial intelligence (AI). Covering a wide range of issues - from the tools and languages of AI to its philosophical implications - Computational Intelligence provides a vigorous forum for the publication of both experimental and theoretical research, as well as surveys and impact studies. The journal is designed to meet the needs of a wide range of AI workers in academic and industrial research.