{"title":"简单模型的空间逻辑","authors":"M. Loreti, M. Quadrini","doi":"10.46298/lmcs-19(3:8)2023","DOIUrl":null,"url":null,"abstract":"Collective Adaptive Systems often consist of many heterogeneous components\ntypically organised in groups. These entities interact with each other by\nadapting their behaviour to pursue individual or collective goals. In these\nsystems, the distribution of these entities determines a space that can be\neither physical or logical. The former is defined in terms of a physical\nrelation among components. The latter depends on logical relations, such as\nbeing part of the same group. In this context, specification and verification\nof spatial properties play a fundamental role in supporting the design of\nsystems and predicting their behaviour. For this reason, different tools and\ntechniques have been proposed to specify and verify the properties of space,\nmainly described as graphs. Therefore, the approaches generally use model\nspatial relations to describe a form of proximity among pairs of entities.\nUnfortunately, these graph-based models do not permit considering relations\namong more than two entities that may arise when one is interested in\ndescribing aspects of space by involving interactions among groups of entities.\nIn this work, we propose a spatial logic interpreted on simplicial complexes.\nThese are topological objects, able to represent surfaces and volumes\nefficiently that generalise graphs with higher-order edges. We discuss how the\nsatisfaction of logical formulas can be verified by a correct and complete\nmodel checking algorithm, which is linear to the dimension of the simplicial\ncomplex and logical formula. The expressiveness of the proposed logic is\nstudied in terms of the spatial variants of classical bisimulation and\nbranching bisimulation relations defined over simplicial complexes.","PeriodicalId":49904,"journal":{"name":"Logical Methods in Computer Science","volume":"19 1","pages":""},"PeriodicalIF":0.6000,"publicationDate":"2021-05-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Spatial Logic for Simplicial Models\",\"authors\":\"M. Loreti, M. Quadrini\",\"doi\":\"10.46298/lmcs-19(3:8)2023\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Collective Adaptive Systems often consist of many heterogeneous components\\ntypically organised in groups. These entities interact with each other by\\nadapting their behaviour to pursue individual or collective goals. In these\\nsystems, the distribution of these entities determines a space that can be\\neither physical or logical. The former is defined in terms of a physical\\nrelation among components. The latter depends on logical relations, such as\\nbeing part of the same group. In this context, specification and verification\\nof spatial properties play a fundamental role in supporting the design of\\nsystems and predicting their behaviour. For this reason, different tools and\\ntechniques have been proposed to specify and verify the properties of space,\\nmainly described as graphs. Therefore, the approaches generally use model\\nspatial relations to describe a form of proximity among pairs of entities.\\nUnfortunately, these graph-based models do not permit considering relations\\namong more than two entities that may arise when one is interested in\\ndescribing aspects of space by involving interactions among groups of entities.\\nIn this work, we propose a spatial logic interpreted on simplicial complexes.\\nThese are topological objects, able to represent surfaces and volumes\\nefficiently that generalise graphs with higher-order edges. We discuss how the\\nsatisfaction of logical formulas can be verified by a correct and complete\\nmodel checking algorithm, which is linear to the dimension of the simplicial\\ncomplex and logical formula. The expressiveness of the proposed logic is\\nstudied in terms of the spatial variants of classical bisimulation and\\nbranching bisimulation relations defined over simplicial complexes.\",\"PeriodicalId\":49904,\"journal\":{\"name\":\"Logical Methods in Computer Science\",\"volume\":\"19 1\",\"pages\":\"\"},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2021-05-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Logical Methods in Computer Science\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.46298/lmcs-19(3:8)2023\",\"RegionNum\":4,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Logical Methods in Computer Science","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.46298/lmcs-19(3:8)2023","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Collective Adaptive Systems often consist of many heterogeneous components
typically organised in groups. These entities interact with each other by
adapting their behaviour to pursue individual or collective goals. In these
systems, the distribution of these entities determines a space that can be
either physical or logical. The former is defined in terms of a physical
relation among components. The latter depends on logical relations, such as
being part of the same group. In this context, specification and verification
of spatial properties play a fundamental role in supporting the design of
systems and predicting their behaviour. For this reason, different tools and
techniques have been proposed to specify and verify the properties of space,
mainly described as graphs. Therefore, the approaches generally use model
spatial relations to describe a form of proximity among pairs of entities.
Unfortunately, these graph-based models do not permit considering relations
among more than two entities that may arise when one is interested in
describing aspects of space by involving interactions among groups of entities.
In this work, we propose a spatial logic interpreted on simplicial complexes.
These are topological objects, able to represent surfaces and volumes
efficiently that generalise graphs with higher-order edges. We discuss how the
satisfaction of logical formulas can be verified by a correct and complete
model checking algorithm, which is linear to the dimension of the simplicial
complex and logical formula. The expressiveness of the proposed logic is
studied in terms of the spatial variants of classical bisimulation and
branching bisimulation relations defined over simplicial complexes.
期刊介绍:
Logical Methods in Computer Science is a fully refereed, open access, free, electronic journal. It welcomes papers on theoretical and practical areas in computer science involving logical methods, taken in a broad sense; some particular areas within its scope are listed below. Papers are refereed in the traditional way, with two or more referees per paper. Copyright is retained by the author.
Topics of Logical Methods in Computer Science:
Algebraic methods
Automata and logic
Automated deduction
Categorical models and logic
Coalgebraic methods
Computability and Logic
Computer-aided verification
Concurrency theory
Constraint programming
Cyber-physical systems
Database theory
Defeasible reasoning
Domain theory
Emerging topics: Computational systems in biology
Emerging topics: Quantum computation and logic
Finite model theory
Formalized mathematics
Functional programming and lambda calculus
Inductive logic and learning
Interactive proof checking
Logic and algorithms
Logic and complexity
Logic and games
Logic and probability
Logic for knowledge representation
Logic programming
Logics of programs
Modal and temporal logics
Program analysis and type checking
Program development and specification
Proof complexity
Real time and hybrid systems
Reasoning about actions and planning
Satisfiability
Security
Semantics of programming languages
Term rewriting and equational logic
Type theory and constructive mathematics.