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A Category-Theoretic Approach to Representation and Analysis of Inconsistency in Graph-Based Viewpoints
A Category-Theoretic Approach to Representation and Analysis of Inconsistency in Graph-Based Viewpoints by Mehrdad Sabetzadeh A thesis submitted in conformity with the requirements for the degree of Master of Science Graduate Department of Computer Science University of Toronto Copyright c 2003 by Mehrdad Sabetzadeh Abstract A Category-Theoretic Approach to Representation and Analysis of Inconsistency in Graph-Based Viewpoints Mehrdad Sabetzadeh Master of Science Graduate Department of Computer Science University of Toronto 2003 Eliciting the requirements for a proposed system typically involves different stakeholders with different expertise, responsibilities, and perspectives. This may result in inconsis- tencies between the descriptions provided by stakeholders. Viewpoints-based approaches have been proposed as a way to manage incomplete and inconsistent models gathered from multiple sources. In this thesis, we propose a category-theoretic framework for the analysis of fuzzy viewpoints. Informally, a fuzzy viewpoint is a graph in which the elements of a lattice are used to specify the amount of knowledge available about the details of nodes and edges. By defining an appropriate notion of morphism between fuzzy viewpoints, we construct categories of fuzzy viewpoints and prove that these categories are (finitely) cocomplete. We then show how colimits can be employed to merge the viewpoints and detect the inconsistencies that arise independent of any particular choice of viewpoint semantics. Taking advantage of the same category-theoretic techniques used in defining fuzzy viewpoints, we will also introduce a more general graph-based formalism that may find applications in other contexts. ii To my mother and father with love and gratitude. Acknowledgements First of all, I wish to thank my supervisor Steve Easterbrook for his guidance, support, and patience. -
Knowledge Representation in Bicategories of Relations
Knowledge Representation in Bicategories of Relations Evan Patterson Department of Statistics, Stanford University Abstract We introduce the relational ontology log, or relational olog, a knowledge representation system based on the category of sets and relations. It is inspired by Spivak and Kent’s olog, a recent categorical framework for knowledge representation. Relational ologs interpolate between ologs and description logic, the dominant formalism for knowledge representation today. In this paper, we investigate relational ologs both for their own sake and to gain insight into the relationship between the algebraic and logical approaches to knowledge representation. On a practical level, we show by example that relational ologs have a friendly and intuitive—yet fully precise—graphical syntax, derived from the string diagrams of monoidal categories. We explain several other useful features of relational ologs not possessed by most description logics, such as a type system and a rich, flexible notion of instance data. In a more theoretical vein, we draw on categorical logic to show how relational ologs can be translated to and from logical theories in a fragment of first-order logic. Although we make extensive use of categorical language, this paper is designed to be self-contained and has considerable expository content. The only prerequisites are knowledge of first-order logic and the rudiments of category theory. 1. Introduction arXiv:1706.00526v2 [cs.AI] 1 Nov 2017 The representation of human knowledge in computable form is among the oldest and most fundamental problems of artificial intelligence. Several recent trends are stimulating continued research in the field of knowledge representation (KR). -
A Rewriting Calculus for Multigraphs with Ports Oana Andrei, Hélène Kirchner
A Rewriting Calculus for Multigraphs with Ports Oana Andrei, Hélène Kirchner To cite this version: Oana Andrei, Hélène Kirchner. A Rewriting Calculus for Multigraphs with Ports. [Technical Report] 2007, pp.18. inria-00139363v1 HAL Id: inria-00139363 https://hal.inria.fr/inria-00139363v1 Submitted on 30 Mar 2007 (v1), last revised 21 May 2007 (v2) HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Towards a Rewriting Calculus for Multigraphs with Ports Oana Andrei1 and H´el`ene Kirchner2 1 INRIA - LORIA 2 CNRS - LORIA Campus scientifique BP 239 F-54506 Vandoeuvre-l`es-Nancy Cedex, France [email protected] Abstract. In this paper, we define labeled multigraphs with ports, a graph model which makes explicit connection resources in each node, allows multiple edges and loops. Dynamic evolution of these structures is expressed with multigraph rewrite rules and a multigraph rewriting relation. Then we encode the multigraphs and multigraph rewriting using algebraic terms and term rewriting to provide a more operational semantics of the multigraph rewriting relation. This term version can be embedded in the rewriting calculus, thus providing for labeled multigraphs transfor- mations a high-level calculus, called ρmg -calculus, with good properties and expressive power. -
Logic and Categories As Tools for Building Theories
Logic and Categories As Tools For Building Theories Samson Abramsky Oxford University Computing Laboratory 1 Introduction My aim in this short article is to provide an impression of some of the ideas emerging at the interface of logic and computer science, in a form which I hope will be accessible to philosophers. Why is this even a good idea? Because there has been a huge interaction of logic and computer science over the past half-century which has not only played an important r^olein shaping Computer Science, but has also greatly broadened the scope and enriched the content of logic itself.1 This huge effect of Computer Science on Logic over the past five decades has several aspects: new ways of using logic, new attitudes to logic, new questions and methods. These lead to new perspectives on the question: What logic is | and should be! Our main concern is with method and attitude rather than matter; nevertheless, we shall base the general points we wish to make on a case study: Category theory. Many other examples could have been used to illustrate our theme, but this will serve to illustrate some of the points we wish to make. 2 Category Theory Category theory is a vast subject. It has enormous potential for any serious version of `formal philosophy' | and yet this has hardly been realized. We shall begin with introduction to some basic elements of category theory, focussing on the fascinating conceptual issues which arise even at the most elementary level of the subject, and then discuss some its consequences and philosophical ramifications. -
Categorical Databases
Categorical databases David I. Spivak [email protected] Mathematics Department Massachusetts Institute of Technology Presented on 2014/02/28 at Oracle David I. Spivak (MIT) Categorical databases Presented on 2014/02/28 1 / 1 Introduction Purpose of the talk Purpose of the talk There is an fundamental connection between databases and categories. Category theory can simplify how we think about and use databases. We can clearly see all the working parts and how they fit together. Powerful theorems can be brought to bear on classical DB problems. David I. Spivak (MIT) Categorical databases Presented on 2014/02/28 2 / 1 Introduction The pros and cons of relational databases The pros and cons of relational databases Relational databases are reliable, scalable, and popular. They are provably reliable to the extent that they strictly adhere to the underlying mathematics. Make a distinction between the system you know and love, vs. the relational model, as a mathematical foundation for this system. David I. Spivak (MIT) Categorical databases Presented on 2014/02/28 3 / 1 Introduction The pros and cons of relational databases You're not really using the relational model. Current implementations have departed from the strict relational formalism: Tables may not be relational (duplicates, e.g from a query). Nulls (and labeled nulls) are commonly used. The theory of relations (150 years old) is not adequate to mathematically describe modern DBMS. The relational model does not offer guidance for schema mappings and data migration. Databases have been intuitively moving toward what's best described with a more modern mathematical foundation. David I. -
Mathematics and the Brain: a Category Theoretical Approach to Go Beyond the Neural Correlates of Consciousness
entropy Review Mathematics and the Brain: A Category Theoretical Approach to Go Beyond the Neural Correlates of Consciousness 1,2,3, , 4,5,6,7, 8, Georg Northoff * y, Naotsugu Tsuchiya y and Hayato Saigo y 1 Mental Health Centre, Zhejiang University School of Medicine, Hangzhou 310058, China 2 Institute of Mental Health Research, University of Ottawa, Ottawa, ON K1Z 7K4 Canada 3 Centre for Cognition and Brain Disorders, Hangzhou Normal University, Hangzhou 310036, China 4 School of Psychological Sciences, Faculty of Medicine, Nursing and Health Sciences, Monash University, Melbourne, Victoria 3800, Australia; [email protected] 5 Turner Institute for Brain and Mental Health, Monash University, Melbourne, Victoria 3800, Australia 6 Advanced Telecommunication Research, Soraku-gun, Kyoto 619-0288, Japan 7 Center for Information and Neural Networks (CiNet), National Institute of Information and Communications Technology (NICT), Suita, Osaka 565-0871, Japan 8 Nagahama Institute of Bio-Science and Technology, Nagahama 526-0829, Japan; [email protected] * Correspondence: georg.northoff@theroyal.ca All authors contributed equally to the paper as it was a conjoint and equally distributed work between all y three authors. Received: 18 July 2019; Accepted: 9 October 2019; Published: 17 December 2019 Abstract: Consciousness is a central issue in neuroscience, however, we still lack a formal framework that can address the nature of the relationship between consciousness and its physical substrates. In this review, we provide a novel mathematical framework of category theory (CT), in which we can define and study the sameness between different domains of phenomena such as consciousness and its neural substrates. CT was designed and developed to deal with the relationships between various domains of phenomena. -
Category Theory for Dummies (I)
Category Theory for Dummies (I) James Cheney Programming Languages Discussion Group March 12, 2004 1 Not quite everything you’ve ever wanted to know... • You keep hearing about category theory. • Cool-sounding papers by brilliant researchers (e.g. Wadler’s “Theorems for free!”) • But it’s scary and incomprehensible. • And Category Theory is not even taught here. • Goal of this series: Familarity with basic ideas, not expertise 2 Outline • Categories: Why are they interesting? • Categories: What are they? Examples. • Some familiar properties expressed categorically • Some basic categorical constructions 3 Category theory • An abstract theory of “structured things” and “structure preserving function-like things”. • Independent of the concrete representation of the things and functions. • An alternative foundation for mathematics? (Lawvere) • Closely connected with computation, types and logic. • Forbiddingly complex notation for even simple ideas. 4 A mathematician’s eye view of the world Algebra Topology Logic Groups, Rings,... Topological Spaces Formulas Homomorphisms Continuous Functions Implication Set Theory 5 A category theorist’s eye view of the world Category Theory Objects Arrows Algebra Topology Logic Groups, Rings,... Topological Spaces Formulas Homomorphisms Continuous Functions Implication 6 My view (not authoritative): • Category theory helps organize thought about a collection of related things • and identify patterns that recur over and over. • It may suggest interesting ways of looking at them • but does not necessarily -
Matters of Model Transformation
Matters of Model Transformation Eugene Syriani January 2, 2009 Abstract Model transformation is at the center of current model-driven engineering research. The current state-of-the- art includes a plethora of techniques and tools for model transformations. One of the most popular approaches is based on graph rewriting. In this report, the most important foundations of graph transformation as well as some of the most efficient techniques for applying these transformations are reviewed. A comparison of the implementation of controlled or programmed graph transformation in various tools is also given. More declarative specifications of graph transformations are discussed. Finally, scalability of model transformation with non graph-based approaches is investigated. The goal of this literature review is to identify open problems and to serve as a starting point for new research. 1 Overview In model-driven engineering, models and transformations are first-class entities. A model represents an abstrac- tion of a real system, focusing on some of its properties. Models are used to specify, simulate, test, verify, and generate code for applications. In language engineering terms, a model conforms to a meta-model. A meta-model defines the abstract syntax and static semantics of a set (possibly infinite) of models. A model is thus typed by its meta-model that specifies its permissible syntax, often in the form of constraints. A common representation of meta-models uses the Unified Modelling Language (UML) Class Diagram notation [1] with Object Constraint Language (OCL) constraints [2]. Model transformation transforms a source model into a target model1, each conforming to their respective meta-model. -
Categories and Computability
Categories and Computability J.R.B. Cockett ∗ Department of Computer Science, University of Calgary, Calgary, T2N 1N4, Alberta, Canada February 22, 2010 Contents 1 Introduction 3 1.1 Categories and foundations . ........ 3 1.2 Categoriesandcomputerscience . ......... 4 1.3 Categoriesandcomputability . ......... 4 I Basic Categories 6 2 Categories and examples 7 2.1 Thedefinitionofacategory . ....... 7 2.1.1 Categories as graphs with composition . ......... 7 2.1.2 Categories as partial semigroups . ........ 8 2.1.3 Categoriesasenrichedcategories . ......... 9 2.1.4 The opposite category and duality . ....... 9 2.2 Examplesofcategories. ....... 10 2.2.1 Preorders ..................................... 10 2.2.2 Finitecategories .............................. 11 2.2.3 Categoriesenrichedinfinitesets . ........ 11 2.2.4 Monoids....................................... 13 2.2.5 Pathcategories................................ 13 2.2.6 Matricesoverarig .............................. 13 2.2.7 Kleenecategories.............................. 14 2.2.8 Sets ......................................... 15 2.2.9 Programminglanguages . 15 2.2.10 Productsandsumsofcategories . ....... 16 2.2.11 Slicecategories .............................. ..... 16 ∗Partially supported by NSERC, Canada. 1 3 Elements of category theory 18 3.1 Epics, monics, retractions, and sections . ............. 18 3.2 Functors........................................ 20 3.3 Natural transformations . ........ 23 3.4 Adjoints........................................ 25 3.4.1 Theuniversalproperty. -
Combinatorial Species and Labelled Structures Brent Yorgey University of Pennsylvania, [email protected]
University of Pennsylvania ScholarlyCommons Publicly Accessible Penn Dissertations 1-1-2014 Combinatorial Species and Labelled Structures Brent Yorgey University of Pennsylvania, [email protected] Follow this and additional works at: http://repository.upenn.edu/edissertations Part of the Computer Sciences Commons, and the Mathematics Commons Recommended Citation Yorgey, Brent, "Combinatorial Species and Labelled Structures" (2014). Publicly Accessible Penn Dissertations. 1512. http://repository.upenn.edu/edissertations/1512 This paper is posted at ScholarlyCommons. http://repository.upenn.edu/edissertations/1512 For more information, please contact [email protected]. Combinatorial Species and Labelled Structures Abstract The theory of combinatorial species was developed in the 1980s as part of the mathematical subfield of enumerative combinatorics, unifying and putting on a firmer theoretical basis a collection of techniques centered around generating functions. The theory of algebraic data types was developed, around the same time, in functional programming languages such as Hope and Miranda, and is still used today in languages such as Haskell, the ML family, and Scala. Despite their disparate origins, the two theories have striking similarities. In particular, both constitute algebraic frameworks in which to construct structures of interest. Though the similarity has not gone unnoticed, a link between combinatorial species and algebraic data types has never been systematically explored. This dissertation lays the theoretical groundwork for a precise—and, hopefully, useful—bridge bewteen the two theories. One of the key contributions is to port the theory of species from a classical, untyped set theory to a constructive type theory. This porting process is nontrivial, and involves fundamental issues related to equality and finiteness; the recently developed homotopy type theory is put to good use formalizing these issues in a satisfactory way. -
The 2-Category Theory of Quasi-Categories
Advances in Mathematics 280 (2015) 549–642 Contents lists available at ScienceDirect Advances in Mathematics www.elsevier.com/locate/aim The 2-category theory of quasi-categories Emily Riehl a,∗, Dominic Verity b a Department of Mathematics, Harvard University, Cambridge, MA 02138, USA b Centre of Australian Category Theory, Macquarie University, NSW 2109, Australia a r t i c l e i n f o a b s t r a c t Article history: In this paper we re-develop the foundations of the category Received 11 December 2013 theory of quasi-categories (also called ∞-categories) using Received in revised form 13 April 2-category theory. We show that Joyal’s strict 2-category of 2015 quasi-categories admits certain weak 2-limits, among them Accepted 22 April 2015 weak comma objects. We use these comma quasi-categories Available online xxxx Communicated by the Managing to encode universal properties relevant to limits, colimits, Editors of AIM and adjunctions and prove the expected theorems relating these notions. These universal properties have an alternate MSC: form as absolute lifting diagrams in the 2-category, which primary 18G55, 55U35, 55U40 we show are determined pointwise by the existence of certain secondary 18A05, 18D20, 18G30, initial or terminal vertices, allowing for the easy production 55U10 of examples. All the quasi-categorical notions introduced here are equiv- Keywords: alent to the established ones but our proofs are independent Quasi-categories and more “formal”. In particular, these results generalise 2-Category theory Formal category theory immediately to model categories enriched over quasi-cate- gories. © 2015 Elsevier Inc. -
A Strategy Language for Graph Rewriting Helene Kirchner, Olivier Namet, Maribel Fernandez
A Strategy Language for Graph Rewriting Helene Kirchner, Olivier Namet, Maribel Fernandez To cite this version: Helene Kirchner, Olivier Namet, Maribel Fernandez. A Strategy Language for Graph Rewriting. LOP- STR 2011 - 21st International Symposium on Logic-Based Program Synthesis and Transformation, Jul 2011, Odense, Denmark. hal-00684244 HAL Id: hal-00684244 https://hal.inria.fr/hal-00684244 Submitted on 31 Mar 2012 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A Strategy Language for Graph Rewriting Maribel Fernández1, Hélène Kirchner2, and Olivier Namet1 1 King’s College London, Department of Informatics, London WC2R 2LS, UK {maribel.fernandez, olivier.namet}@kcl.ac.uk 2 Inria, Domaine de Voluceau - Rocquencourt B.P. 105 - 78153 Le Chesnay France [email protected] Abstract. We give a formal semantics for a graph-based programming language, where a program consists of a collection of graph rewriting rules, a user-defined strategy to control the application of rules, and an initial graph to be rewritten. The traditional operators found in strategy languages for term rewriting have been adapted to deal with the more general setting of graph rewriting, and some new constructs have been included in the language to deal with graph traversal and management of rewriting positions in the graph.