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Ambiguity and Incomplete Information in Categorical Models of Language
Ambiguity and Incomplete Information in Categorical Models of Language Dan Marsden University of Oxford [email protected] We investigate notions of ambiguity and partial information in categorical distributional models of natural language. Probabilistic ambiguity has previously been studied in [27, 26, 16] using Selinger’s CPM construction. This construction works well for models built upon vector spaces, as has been shown in quantum computational applications. Unfortunately, it doesn’t seem to provide a satis- factory method for introducing mixing in other compact closed categories such as the category of sets and binary relations. We therefore lack a uniform strategy for extending a category to model imprecise linguistic information. In this work we adopt a different approach. We analyze different forms of ambiguous and in- complete information, both with and without quantitative probabilistic data. Each scheme then cor- responds to a suitable enrichment of the category in which we model language. We view different monads as encapsulating the informational behaviour of interest, by analogy with their use in mod- elling side effects in computation. Previous results of Jacobs then allow us to systematically construct suitable bases for enrichment. We show that we can freely enrich arbitrary dagger compact closed categories in order to capture all the phenomena of interest, whilst retaining the important dagger compact closed structure. This allows us to construct a model with real convex combination of binary relations that makes non-trivial use of the scalars. Finally we relate our various different enrichments, showing that finite subconvex algebra enrichment covers all the effects under consideration. -
Partial Mal'tsevness and Partial Protomodularity
PARTIAL MAL’TSEVNESS AND PARTIAL PROTOMODULARITY DOMINIQUE BOURN Abstract. We introduce the notion of Mal’tsev reflection which allows us to set up a partial notion of Mal’tsevness with respect to a class Σ of split epimorphisms stable under pullback and containing the isomorphisms, and we investigate what is remaining of the properties of the global Mal’tsev context. We introduce also the notion of partial protomodularity in the non-pointed context. Introduction A Mal’tsev category is a category in which any reflexive relation is an equivalence relation, see [9] and [10]. The categories Gp of groups and K-Lie of Lie K-algebras are major examples of Mal’tsev categories. The terminology comes from the pi- oneering work of Mal’tsev in the varietal context [16] which was later on widely developped in [18]. In [3], Mal’tsev categories were characterized in terms of split epimorphisms: a finitely complete category D is a Mal’tsev one if and only if any pullback of split epimorphisms in D: t¯ X′ o X O g¯ / O ′ ′ f s f s t Y ′ o Y g / is such that the pair (s′, t¯) is jointly extremally epic. More recently the same kind of property was observed, but only for a certain class Σ of split epimorphisms (f,s) which is stable under pullback and contains arXiv:1507.02886v1 [math.CT] 10 Jul 2015 isomorphisms. By the classes of Schreier or homogeneous split epimorphisms in the categories Mon of monoids and SRng of semi-rings [8], by the classes of puncturing or acupuncturing split epimorphims in the category of quandles [6], by the class of split epimorphic functors with fibrant splittings in the category CatY of categories with a fixed set of objects Y [5]. -
Lecture 10. Functors and Monads Functional Programming
Lecture 10. Functors and monads Functional Programming [Faculty of Science Information and Computing Sciences] 0 Goals I Understand the concept of higher-kinded abstraction I Introduce two common patterns: functors and monads I Simplify code with monads Chapter 12 from Hutton’s book, except 12.2 [Faculty of Science Information and Computing Sciences] 1 Functors [Faculty of Science Information and Computing Sciences] 2 Map over lists map f xs applies f over all the elements of the list xs map :: (a -> b) -> [a] -> [b] map _ [] = [] map f (x:xs) = f x : map f xs > map (+1)[1,2,3] [2,3,4] > map even [1,2,3] [False,True,False] [Faculty of Science Information and Computing Sciences] 3 mapTree _ Leaf = Leaf mapTree f (Node l x r) = Node (mapTree f l) (f x) (mapTree f r) Map over binary trees Remember binary trees with data in the inner nodes: data Tree a = Leaf | Node (Tree a) a (Tree a) deriving Show They admit a similar map operation: mapTree :: (a -> b) -> Tree a -> Tree b [Faculty of Science Information and Computing Sciences] 4 Map over binary trees Remember binary trees with data in the inner nodes: data Tree a = Leaf | Node (Tree a) a (Tree a) deriving Show They admit a similar map operation: mapTree :: (a -> b) -> Tree a -> Tree b mapTree _ Leaf = Leaf mapTree f (Node l x r) = Node (mapTree f l) (f x) (mapTree f r) [Faculty of Science Information and Computing Sciences] 4 Map over binary trees mapTree also applies a function over all elements, but now contained in a binary tree > t = Node (Node Leaf 1 Leaf) 2 Leaf > mapTree (+1) t Node -
1. Language of Operads 2. Operads As Monads
OPERADS, APPROXIMATION, AND RECOGNITION MAXIMILIEN PEROUX´ All missing details can be found in [May72]. 1. Language of operads Let S = (S; ⊗; I) be a (closed) symmetric monoidal category. Definition 1.1. An operad O in S is a collection of object fO(j)gj≥0 in S endowed with : • a right-action of the symmetric group Σj on O(j) for each j, such that O(0) = I; • a unit map I ! O(1) in S; • composition operations that are morphisms in S : γ : O(k) ⊗ O(j1) ⊗ · · · ⊗ O(jk) −! O(j1 + ··· + jk); defined for each k ≥ 0, j1; : : : ; jk ≥ 0, satisfying natural equivariance, unit and associativity relations. 0 0 A morphism of operads : O ! O is a sequence j : O(j) ! O (j) of Σj-equivariant morphisms in S compatible with the unit map and γ. Example 1.2. ⊗j Let X be an object in S. The endomorphism operad EndX is defined to be EndX (j) = HomS(X ;X), ⊗j with unit idX , and the Σj-right action is induced by permuting on X . Example 1.3. Define Assoc(j) = ` , the associative operad, where the maps γ are defined by equivariance. Let σ2Σj I Com(j) = I, the commutative operad, where γ are the canonical isomorphisms. Definition 1.4. Let O be an operad in S. An O-algebra (X; θ) in S is an object X together with a morphism of operads ⊗j θ : O ! EndX . Using adjoints, this is equivalent to a sequence of maps θj : O(j) ⊗ X ! X such that they are associative, unital and equivariant. -
Categories of Coalgebras with Monadic Homomorphisms Wolfram Kahl
Categories of Coalgebras with Monadic Homomorphisms Wolfram Kahl To cite this version: Wolfram Kahl. Categories of Coalgebras with Monadic Homomorphisms. 12th International Workshop on Coalgebraic Methods in Computer Science (CMCS), Apr 2014, Grenoble, France. pp.151-167, 10.1007/978-3-662-44124-4_9. hal-01408758 HAL Id: hal-01408758 https://hal.inria.fr/hal-01408758 Submitted on 5 Dec 2016 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. Distributed under a Creative Commons Attribution| 4.0 International License Categories of Coalgebras with Monadic Homomorphisms Wolfram Kahl McMaster University, Hamilton, Ontario, Canada, [email protected] Abstract. Abstract graph transformation approaches traditionally con- sider graph structures as algebras over signatures where all function sym- bols are unary. Attributed graphs, with attributes taken from (term) algebras over ar- bitrary signatures do not fit directly into this kind of transformation ap- proach, since algebras containing function symbols taking two or more arguments do not allow component-wise construction of pushouts. We show how shifting from the algebraic view to a coalgebraic view of graph structures opens up additional flexibility, and enables treat- ing term algebras over arbitrary signatures in essentially the same way as unstructured label sets. -
Algebraic Structures Lecture 18 Thursday, April 4, 2019 1 Type
Harvard School of Engineering and Applied Sciences — CS 152: Programming Languages Algebraic structures Lecture 18 Thursday, April 4, 2019 In abstract algebra, algebraic structures are defined by a set of elements and operations on those ele- ments that satisfy certain laws. Some of these algebraic structures have interesting and useful computa- tional interpretations. In this lecture we will consider several algebraic structures (monoids, functors, and monads), and consider the computational patterns that these algebraic structures capture. We will look at Haskell, a functional programming language named after Haskell Curry, which provides support for defin- ing and using such algebraic structures. Indeed, monads are central to practical programming in Haskell. First, however, we consider type constructors, and see two new type constructors. 1 Type constructors A type constructor allows us to create new types from existing types. We have already seen several different type constructors, including product types, sum types, reference types, and parametric types. The product type constructor × takes existing types τ1 and τ2 and constructs the product type τ1 × τ2 from them. Similarly, the sum type constructor + takes existing types τ1 and τ2 and constructs the product type τ1 + τ2 from them. We will briefly introduce list types and option types as more examples of type constructors. 1.1 Lists A list type τ list is the type of lists with elements of type τ. We write [] for the empty list, and v1 :: v2 for the list that contains value v1 as the first element, and v2 is the rest of the list. We also provide a way to check whether a list is empty (isempty? e) and to get the head and the tail of a list (head e and tail e). -
The Expectation Monad in Quantum Foundations
The Expectation Monad in Quantum Foundations Bart Jacobs and Jorik Mandemaker Institute for Computing and Information Sciences (iCIS), Radboud University Nijmegen, The Netherlands. fB.Jacobs,[email protected] The expectation monad is introduced abstractly via two composable adjunctions, but concretely cap- tures measures. It turns out to sit in between known monads: on the one hand the distribution and ultrafilter monad, and on the other hand the continuation monad. This expectation monad is used in two probabilistic analogues of fundamental results of Manes and Gelfand for the ultrafilter monad: algebras of the expectation monad are convex compact Hausdorff spaces, and are dually equivalent to so-called Banach effect algebras. These structures capture states and effects in quantum foundations, and the duality between them. Moreover, the approach leads to a new re-formulation of Gleason’s theorem, expressing that effects on a Hilbert space are free effect modules on projections, obtained via tensoring with the unit interval. 1 Introduction Techniques that have been developed over the last decades for the semantics of programming languages and programming logics gain wider significance. In this way a new interdisciplinary area has emerged where researchers from mathematics, (theoretical) physics and (theoretical) computer science collabo- rate, notably on quantum computation and quantum foundations. The article [6] uses the phrase “Rosetta Stone” for the language and concepts of category theory that form an integral part of this common area. The present article is also part of this new field. It uses results from programming semantics, topology and (convex) analysis, category theory (esp. monads), logic and probability, and quantum foundations. -
Universality of Multiplicative Infinite Loop Space Machines
UNIVERSALITY OF MULTIPLICATIVE INFINITE LOOP SPACE MACHINES DAVID GEPNER, MORITZ GROTH AND THOMAS NIKOLAUS Abstract. We establish a canonical and unique tensor product for commutative monoids and groups in an ∞-category C which generalizes the ordinary tensor product of abelian groups. Using this tensor product we show that En-(semi)ring objects in C give rise to En-ring spectrum objects in C. In the case that C is the ∞-category of spaces this produces a multiplicative infinite loop space machine which can be applied to the algebraic K-theory of rings and ring spectra. The main tool we use to establish these results is the theory of smashing localizations of presentable ∞-categories. In particular, we identify preadditive and additive ∞-categories as the local objects for certain smashing localizations. A central theme is the stability of algebraic structures under basechange; for example, we show Ring(D ⊗ C) ≃ Ring(D) ⊗ C. Lastly, we also consider these algebraic structures from the perspective of Lawvere algebraic theories in ∞-categories. Contents 0. Introduction 1 1. ∞-categories of commutative monoids and groups 4 2. Preadditive and additive ∞-categories 6 3. Smashing localizations 8 4. Commutative monoids and groups as smashing localizations 11 5. Canonical symmetric monoidal structures 13 6. More functoriality 15 7. ∞-categories of semirings and rings 17 8. Multiplicative infinite loop space theory 19 Appendix A. Comonoids 23 Appendix B. Algebraic theories and monadic functors 23 References 26 0. Introduction The Grothendieck group K0(M) of a commutative monoid M, also known as the group completion, is the universal abelian group which receives a monoid map from M. -
Monads of Effective Descent Type and Comonadicity
Theory and Applications of Categories, Vol. 16, No. 1, 2006, pp. 1–45. MONADS OF EFFECTIVE DESCENT TYPE AND COMONADICITY BACHUKI MESABLISHVILI Abstract. We show, for an arbitrary adjunction F U : B→Awith B Cauchy complete, that the functor F is comonadic if and only if the monad T on A induced by the adjunction is of effective descent type, meaning that the free T-algebra functor F T : A→AT is comonadic. This result is applied to several situations: In Section 4 to give a sufficient condition for an exponential functor on a cartesian closed category to be monadic, in Sections 5 and 6 to settle the question of the comonadicity of those functors whose domain is Set,orSet, or the category of modules over a semisimple ring, in Section 7 to study the effectiveness of (co)monads on module categories. Our final application is a descent theorem for noncommutative rings from which we deduce an important result of A. Joyal and M. Tierney and of J.-P. Olivier, asserting that the effective descent morphisms in the opposite of the category of commutative unital rings are precisely the pure monomorphisms. 1. Introduction Let A and B be two (not necessarily commutative) rings related by a ring homomorphism i : B → A. The problem of Grothendieck’s descent theory for modules with respect to i : B → A is concerned with the characterization of those (right) A-modules Y for which there is X ∈ ModB andanisomorphismY X⊗BA of right A-modules. Because of a fun- damental connection between descent and monads discovered by Beck (unpublished) and B´enabou and Roubaud [6], this problem is equivalent to the problem of the comonadicity of the extension-of-scalars functor −⊗BA :ModB → ModA. -
Beck's Theorem Characterizing Algebras
BECK'S THEOREM CHARACTERIZING ALGEBRAS SOFI GJING JOVANOVSKA Abstract. In this paper, I will construct a proof of Beck's Theorem char- acterizing T -algebras. Suppose we have an adjoint pair of functors F and G between categories C and D. It determines a monad T on C. We can associate a T -algebra to the monad, and Beck's Theorem demonstrates when the catego- ry of T -algebras is equivalent to the category D. We will arrive at this result by rst de ning categories, and a few relevant concepts and theorems that will be useful for proving our result; these will include natural tranformations, adjoints, monads and more. Contents 1. Introduction 1 2. Categories 2 3. Adjoints 4 3.1. Isomorphisms and Natural Transformations 4 3.2. Adjoints 5 3.3. Triangle Identities 5 4. Monads and Algebras 7 4.1. Monads and Adjoints 7 4.2. Algebras for a monad 8 4.3. The Comparison with Algebras 9 4.4. Coequalizers 11 4.5. Beck's Threorem 12 Acknowledgments 15 References 15 1. Introduction Beck's Theorem characterizing algebras is one direction of Beck's Monadicity Theorem. Beck's Monadicity Theorem is most useful in studying adjoint pairs of functors. Adjunction is a type of relation between two functors that has some very important properties, such as preservation of limits or colimits, which, unfortunate- ly, we will not touch upon in this paper. However, we need to know that it is indeed a topic of interest, and therefore worth studying. Here, we state Beck's Monadicity Theorem. -
Monads and Side Effects in Haskell
Monads and Side Effects in Haskell Alan Davidson October 2, 2013 In this document, I will attempt to explain in simple terms what monads are, how they work, and how they are used to perform side effects in the Haskell programming language. I assume you already have some familiarity with Haskell syntax. I will start from relatively simple, familiar ideas, and work my way up to our actual goals. In particular, I will start by discussing functors, then applicative functors, then monads, and finally how to have side effects in Haskell. I will finish up by discussing the functor and monad laws, and resources to learn more details. 1 Functors A functor is basically a data structure that can be mapped over: class Functor f where fmap :: (a -> b) -> f a -> f b This is to say, fmap takes a function that takes an a and returns a b, and a data structure full of a’s, and it returns a data structure with the same format but with every piece of data replaced with the result of running it through that function. Example 1. Lists are functors. instance Functor [] where fmap _ [] = [] fmap f (x : xs) = (f x) : (fmap f xs) We could also have simply made fmap equal to map, but that would hide the implemen- tation, and this example is supposed to illustrate how it all works. Example 2. Binary trees are functors. data BinaryTree t = Empty | Node t (BinaryTree t) (BinaryTree t) instance Functor BinaryTree where fmap _ Empty = Empty fmap f (Node x left right) = Node (f x) (fmap f left) (fmap f right) 1 Note that these are not necessarily binary search trees; the elements in a tree returned from fmap are not guaranteed to be in sorted order (indeed, they’re not even guaranteed to hold sortable data). -
1 Category Theory
{-# LANGUAGE RankNTypes #-} module AbstractNonsense where import Control.Monad 1 Category theory Definition 1. A category consists of • a collection of objects • and a collection of morphisms between those objects. We write f : A → B for the morphism f connecting the object A to B. • Morphisms are closed under composition, i.e. for morphisms f : A → B and g : B → C there exists the composed morphism h = f ◦ g : A → C1. Furthermore we require that • Composition is associative, i.e. f ◦ (g ◦ h) = (f ◦ g) ◦ h • and for each object A there exists an identity morphism idA such that for all morphisms f : A → B: f ◦ idB = idA ◦ f = f Many mathematical structures form catgeories and thus the theorems and con- structions of category theory apply to them. As an example consider the cate- gories • Set whose objects are sets and morphisms are functions between those sets. • Grp whose objects are groups and morphisms are group homomorphisms, i.e. structure preserving functions, between those groups. 1.1 Functors Category theory is mainly interested in relationships between different kinds of mathematical structures. Therefore the fundamental notion of a functor is introduced: 1The order of the composition is to be read from left to right in contrast to standard mathematical notation. 1 Definition 2. A functor F : C → D is a transformation between categories C and D. It is defined by its action on objects F (A) and morphisms F (f) and has to preserve the categorical structure, i.e. for any morphism f : A → B: F (f(A)) = F (f)(F (A)) which can also be stated graphically as the commutativity of the following dia- gram: F (f) F (A) F (B) f A B Alternatively we can state that functors preserve the categorical structure by the requirement to respect the composition of morphisms: F (idC) = idD F (f) ◦ F (g) = F (f ◦ g) 1.2 Natural transformations Taking the construction a step further we can ask for transformations between functors.