Using Category Theory to Facilitate Multiple Manufacturing Service Database Integration
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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). -
Category Theory and Cyber Physical Systems
Category theory and Cyber physical systems Eswaran Subrahmanian (CMU/NIST) Spencer Breiner (NIST) July 22, 2017 CPS workshop Robert Bosch Center for Cyber Physical Systems IISC Bangalore, India Talk outline • Basic elements of CPS • CPS as composition of different systems • Category theory • A formalism for representing different formalisms • A formalism for composing system from from formalisms. • Ologs • A CT based knowledge representation scheme • Examples of database intergration • Cyber and Physical system and composition. • String diagram for Process composition • Basic elements • Antilock brakes - Top level • Antilock brakes – Expanding The modulator • Redesign for traction control + stability control • Incorporating semantics • Conclusion Cyber physical system: A definition Cyber Physical Systems Interconnected Systems & Control Internet of Things Sensing and Acting Physical Environment Things Person Network Physical World 3 Basic elements and composition of CPS Basic elements • Perceptual devices: Identification and Measurements • Actuating devices: activation results in action • Physical devices: transmission, amplification of power, • Logical devices: computational/logical • Humans devices: mental model Multiple Modeling formalisms: logic, state machines, differential equations, stochastic models, etc. Requires composition and compositionality to ensure desired behavior Category theory • Category Theory (CT) is a potential solution. • CT is the mathematical theory of abstract processes and composition • CT could be thought of as the conceptual operating system. Categories & Composition • A category is a universe of resources (objects) �, �, �, … and processes (arrows) �, �, ℎ, … • Every process has input and output resources, indicated �:�→�. • The main property of categorical processes is that they compose: Category theory: relationship to domains Category Theory as a universal Modeling Language (Spivak, 2015*) The Category Theory (CT) view of modeling – two postulates: 1. -
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. -
20170910-Full
ELECTROTECHNICA & ELECTRONICA E+E Vol. 52. No 9-10/2017 Monthly scientific and technical journal Published by: The Union of Electronics, Electrical Engineering and Telecommunications /CEEC/, BULGARIA Editor-in-chief: C O N T E N T S Prof. Ivan Yatchev, Bulgaria TELECOMMUNICATIONS SCIENCE Deputy Editor-in-chief: Assoc. Prof. Seferin Mirtchev, Bulgaria Zdravka Tchobanova Editorial Board: Cooperative spectrum sensing - overview 1 Prof. Anatoliy Aleksandrov, Bulgaria Acad. Prof. Chavdar Rumenin, Bulgaria Stanimir Sadinov Prof. Christian Magele, Austria Simulation study and analysis in transmitting Prof. Georgi Stoyanov, Bulgaria RZ and NRZ coded signals into 10 Gbps optical line Assoc. Prof. Evdokia Sotirova, Bulgaria with optical amplifying sections 9 Prof. Ewen Ritchie, Denmark Prof. Hannes Toepfer, Germany ELECTRONICS Dr. Hartmut Brauer, Germany Prof. Marin Hristov, Bulgaria Kiril Ivanov Prof. Maurizio Repetto, Italy Plasma sterilization – special features Prof. Mihail Antchev, Bulgaria and new approaches in medical applications 15 Prof. Nikolay Mihailov, Bulgaria Prof. Radi Romansky, Bulgaria INNOVATIVE TECHNOLOGIES Prof. Rosen Vasilev, Bulgaria Prof. Takeshi Tanaka, Japan Elena Shoikova, Anatoly Peshev Prof. Ventsislav Valchev, Bulgaria Best practices for designing user experience Dr. Vladimir Shelyagin, Ukraine for Internet of Things and virtual reality 22 Acad. Prof. Yuriy I. Yakymenko, Ukraine Assoc. Prof. Zahari Zarkov, Bulgaria APPLICATION IN PRACTICE Advisory Board: Prof. Dimitar Rachev, Bulgaria Milan Stankov Prof. Emil Sokolov, Bulgaria From electrica to invariant automatic Corr. Member Prof. Georgi Mladenov, Bulgaria (Or how to use the knowledge about Theory of electricity Prof. Ivan Dotsinski, Bulgaria for enter into Theory of invariant automatic control). Assoc. Prof. Ivan Vassilev, Bulgaria Part two: Electromechanical dualism. Assoc. Prof. Ivan Shishkov, Bulgaria Universality of energetic equations. -
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 -
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. -
Category Theory and Model-Driven Engineering: from Formal Semantics to Design Patterns and Beyond
Category Theory and Model-Driven Engineering: From Formal Semantics to Design Patterns and Beyond Zinovy Diskin1;2 Tom Maibaum1 1Network for Engineering of Complex Software-Intensive Systems for Automotive Systems (NECSIS), McMaster University, Canada 2Generative Software Development Lab, University of Waterloo, Canada [email protected] [email protected] There is a hidden intrigue in the title. CT is one of the most abstract mathematical disciplines, some- times nicknamed ”abstract nonsense”. MDE is a recent trend in software development, industrially supported by standards, tools, and the status of a new ”silver bullet”. Surprisingly, categorical pat- terns turn out to be directly applicable to mathematical modeling of structures appearing in everyday MDE practice. Model merging, transformation, synchronization, and other important model man- agement scenarios can be seen as executions of categorical specifications. Moreover, the paper aims to elucidate a claim that relationships between CT and MDE are more complex and richer than is normally assumed for ”applied mathematics”. CT provides a toolbox of design patterns and structural principles of real practical value for MDE. We will present examples of how an elementary categorical arrangement of a model management scenario reveals deficiencies in the architecture of modern tools automating the scenario. Keywords: Model-driven engineering, mathematical modeling, category theory 1 Introduction There are several well established applications of category theory (CT) in theoretical computer science; typical examples are programming language semantics and concurrency. Modern software engineering (SE) seems to be an essentially different domain, not obviously suitable for theoretical foundations based on abstract algebra. Too much in this domain appears to be ad hoc and empirical, and the rapid progress of open source and collaborative software development, service-oriented programming, and cloud com- puting far outpaces their theoretical support.