Topos Semantics for Higher-Order Modal Logic
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Semantical Investigations
Bulletin of the Section of Logic Volume 49/3 (2020), pp. 231{253 http://dx.doi.org/10.18778/0138-0680.2020.12 Satoru Niki EMPIRICAL NEGATION, CO-NEGATION AND THE CONTRAPOSITION RULE I: SEMANTICAL INVESTIGATIONS Abstract We investigate the relationship between M. De's empirical negation in Kripke and Beth Semantics. It turns out empirical negation, as well as co-negation, corresponds to different logics under different semantics. We then establish the relationship between logics related to these negations under unified syntax and semantics based on R. Sylvan's CC!. Keywords: Empirical negation, co-negation, Beth semantics, Kripke semantics, intuitionism. 1. Introduction The philosophy of Intuitionism has long acknowledged that there is more to negation than the customary, reduction to absurdity. Brouwer [1] has al- ready introduced the notion of apartness as a positive version of inequality, such that from two apart objects (e.g. points, sequences) one can learn not only they are unequal, but also how much or where they are different. (cf. [19, pp.319{320]). He also introduced the notion of weak counterexample, in which a statement is reduced to a constructively unacceptable principle, to conclude we cannot expect to prove the statement [17]. Presented by: Andrzej Indrzejczak Received: April 18, 2020 Published online: August 15, 2020 c Copyright for this edition by UniwersytetL´odzki, L´od´z2020 232 Satoru Niki Another type of negation was discussed in the dialogue of Heyting [8, pp. 17{19]. In it mathematical negation characterised by reduction to absurdity is distinguished from factual negation, which concerns the present state of our knowledge. -
Introduction Nml:Syn:Int: Modal Logic Deals with Modal Propositions and the Entailment Relations Among Sec Them
syn.1 Introduction nml:syn:int: Modal logic deals with modal propositions and the entailment relations among sec them. Examples of modal propositions are the following: 1. It is necessary that 2 + 2 = 4. 2. It is necessarily possible that it will rain tomorrow. 3. If it is necessarily possible that ' then it is possible that '. Possibility and necessity are not the only modalities: other unary connectives are also classified as modalities, for instance, \it ought to be the case that '," \It will be the case that '," \Dana knows that '," or \Dana believes that '." Modal logic makes its first appearance in Aristotle's De Interpretatione: he was the first to notice that necessity implies possibility, but not vice versa; that possibility and necessity are inter-definable; that If ' ^ is possibly true then ' is possibly true and is possibly true, but not conversely; and that if ' ! is necessary, then if ' is necessary, so is . The first modern approach to modal logic was the work of C. I. Lewis,cul- minating with Lewis and Langford, Symbolic Logic (1932). Lewis & Langford were unhappy with the representation of implication by means of the mate- rial conditional: ' ! is a poor substitute for \' implies ." Instead, they proposed to characterize implication as \Necessarily, if ' then ," symbolized as ' J . In trying to sort out the different properties, Lewis identified five different modal systems, S1,..., S4, S5, the last two of which are still in use. The approach of Lewis and Langford was purely syntactical: they identified reasonable axioms and rules and investigated what was provable with those means. -
On the Logic of Two-Dimensional Semantics
Matrices and Modalities: On the Logic of Two-Dimensional Semantics MSc Thesis (Afstudeerscriptie) written by Peter Fritz (born March 4, 1984 in Ludwigsburg, Germany) under the supervision of Dr Paul Dekker and Prof Dr Yde Venema, and submitted to the Board of Examiners in partial fulfillment of the requirements for the degree of MSc in Logic at the Universiteit van Amsterdam. Date of the public defense: Members of the Thesis Committee: June 29, 2011 Dr Paul Dekker Dr Emar Maier Dr Alessandra Palmigiano Prof Dr Frank Veltman Prof Dr Yde Venema Abstract Two-dimensional semantics is a theory in the philosophy of language that pro- vides an account of meaning which is sensitive to the distinction between ne- cessity and apriority. Usually, this theory is presented in an informal manner. In this thesis, I take first steps in formalizing it, and use the formalization to present some considerations in favor of two-dimensional semantics. To do so, I define a semantics for a propositional modal logic with operators for the modalities of necessity, actuality, and apriority that captures the relevant ideas of two-dimensional semantics. I use this to show that some criticisms of two- dimensional semantics that claim that the theory is incoherent are not justified. I also axiomatize the logic, and compare it to the most important proposals in the literature that define similar logics. To indicate that two-dimensional semantics is a plausible semantic theory, I give an argument that shows that all theorems of the logic can be philosophically justified independently of two-dimensional semantics. Acknowledgements I thank my supervisors Paul Dekker and Yde Venema for their help and encour- agement in preparing this thesis. -
Probabilistic Semantics for Modal Logic
Probabilistic Semantics for Modal Logic By Tamar Ariela Lando A dissertation submitted in partial satisfaction of the requirements for the degree of Doctor of Philosophy in Philosophy in the Graduate Division of the University of California, Berkeley Committee in Charge: Paolo Mancosu (Co-Chair) Barry Stroud (Co-Chair) Christos Papadimitriou Spring, 2012 Abstract Probabilistic Semantics for Modal Logic by Tamar Ariela Lando Doctor of Philosophy in Philosophy University of California, Berkeley Professor Paolo Mancosu & Professor Barry Stroud, Co-Chairs We develop a probabilistic semantics for modal logic, which was introduced in recent years by Dana Scott. This semantics is intimately related to an older, topological semantics for modal logic developed by Tarski in the 1940’s. Instead of interpreting modal languages in topological spaces, as Tarski did, we interpret them in the Lebesgue measure algebra, or algebra of measurable subsets of the real interval, [0, 1], modulo sets of measure zero. In the probabilistic semantics, each formula is assigned to some element of the algebra, and acquires a corresponding probability (or measure) value. A formula is satisfed in a model over the algebra if it is assigned to the top element in the algebra—or, equivalently, has probability 1. The dissertation focuses on questions of completeness. We show that the propo- sitional modal logic, S4, is sound and complete for the probabilistic semantics (formally, S4 is sound and complete for the Lebesgue measure algebra). We then show that we can extend this semantics to more complex, multi-modal languages. In particular, we prove that the dynamic topological logic, S4C, is sound and com- plete for the probabilistic semantics (formally, S4C is sound and complete for the Lebesgue measure algebra with O-operators). -
The Category of Sheaves Is a Topos Part 2
The category of sheaves is a topos part 2 Patrick Elliott Recall from the last talk that for a small category C, the category PSh(C) of presheaves on C is an elementary topos. Explicitly, PSh(C) has the following structure: • Given two presheaves F and G on C, the exponential GF is the presheaf defined on objects C 2 obC by F G (C) = Hom(hC × F; G); where hC = Hom(−;C) is the representable functor associated to C, and the product × is defined object-wise. • Writing 1 for the constant presheaf of the one object set, the subobject classifier true : 1 ! Ω in PSh(C) is defined on objects by Ω(C) := fS j S is a sieve on C in Cg; and trueC : ∗ ! Ω(C) sends ∗ to the maximal sieve t(C). The goal of this talk is to refine this structure to show that the category Shτ (C) of sheaves on a site (C; τ) is also an elementary topos. To do this we must make use of the sheafification functor defined at the end of the first talk: Theorem 0.1. The inclusion functor i : Shτ (C) ! PSh(C) has a left adjoint a : PSh(C) ! Shτ (C); called sheafification, or the associated sheaf functor. Moreover, this functor commutes with finite limits. Explicitly, a(F) = (F +)+, where + F (C) := colimS2τ(C)Match(S; F); where Match(S; F) is the set of matching families for the cover S of C, and the colimit is taken over all covering sieves of C, ordered by reverse inclusion. -
Notes on Categorical Logic
Notes on Categorical Logic Anand Pillay & Friends Spring 2017 These notes are based on a course given by Anand Pillay in the Spring of 2017 at the University of Notre Dame. The notes were transcribed by Greg Cousins, Tim Campion, L´eoJimenez, Jinhe Ye (Vincent), Kyle Gannon, Rachael Alvir, Rose Weisshaar, Paul McEldowney, Mike Haskel, ADD YOUR NAMES HERE. 1 Contents Introduction . .3 I A Brief Survey of Contemporary Model Theory 4 I.1 Some History . .4 I.2 Model Theory Basics . .4 I.3 Morleyization and the T eq Construction . .8 II Introduction to Category Theory and Toposes 9 II.1 Categories, functors, and natural transformations . .9 II.2 Yoneda's Lemma . 14 II.3 Equivalence of categories . 17 II.4 Product, Pullbacks, Equalizers . 20 IIIMore Advanced Category Theoy and Toposes 29 III.1 Subobject classifiers . 29 III.2 Elementary topos and Heyting algebra . 31 III.3 More on limits . 33 III.4 Elementary Topos . 36 III.5 Grothendieck Topologies and Sheaves . 40 IV Categorical Logic 46 IV.1 Categorical Semantics . 46 IV.2 Geometric Theories . 48 2 Introduction The purpose of this course was to explore connections between contemporary model theory and category theory. By model theory we will mostly mean first order, finitary model theory. Categorical model theory (or, more generally, categorical logic) is a general category-theoretic approach to logic that includes infinitary, intuitionistic, and even multi-valued logics. Say More Later. 3 Chapter I A Brief Survey of Contemporary Model Theory I.1 Some History Up until to the seventies and early eighties, model theory was a very broad subject, including topics such as infinitary logics, generalized quantifiers, and probability logics (which are actually back in fashion today in the form of con- tinuous model theory), and had a very set-theoretic flavour. -
Kripke Semantics for Basic Sequent Systems
Kripke Semantics for Basic Sequent Systems Arnon Avron and Ori Lahav? School of Computer Science, Tel Aviv University, Israel {aa,orilahav}@post.tau.ac.il Abstract. We present a general method for providing Kripke seman- tics for the family of fully-structural multiple-conclusion propositional sequent systems. In particular, many well-known Kripke semantics for a variety of logics are easily obtained as special cases. This semantics is then used to obtain semantic characterizations of analytic sequent sys- tems of this type, as well as of those admitting cut-admissibility. These characterizations serve as a uniform basis for semantic proofs of analyt- icity and cut-admissibility in such systems. 1 Introduction This paper is a continuation of an on-going project aiming to get a unified semantic theory and understanding of analytic Gentzen-type systems and the phenomenon of strong cut-admissibility in them. In particular: we seek for gen- eral effective criteria that can tell in advance whether a given system is analytic, and whether the cut rule is (strongly) admissible in it (instead of proving these properties from scratch for every new system). The key idea of this project is to use semantic tools which are constructed in a modular way. For this it is es- sential to use non-deterministic semantics. This was first done in [6], where the family of propositional multiple-conclusion canonical systems was defined, and it was shown that the semantics of such systems is provided by two-valued non- deterministic matrices { a natural generalization of the classical truth-tables. The sequent systems of this family are fully-structural (i.e. -
SHEAVES, TOPOSES, LANGUAGES Acceleration Based on A
Chapter 7 Logic of behavior: Sheaves, toposes, and internal languages 7.1 How can we prove our machine is safe? Imagine you are trying to design a system of interacting components. You wouldn’t be doing this if you didn’t have a goal in mind: you want the system to do something, to behave in a certain way. In other words, you want to restrict its possibilities to a smaller set: you want the car to remain on the road, you want the temperature to remain in a particular range, you want the bridge to be safe for trucks to pass. Out of all the possibilities, your system should only permit some. Since your system is made of components that interact in specified ways, the possible behavior of the whole—in any environment—is determined by the possible behaviors of each of its components in their local environments, together with the precise way in which they interact.1 In this chapter, we will discuss a logic wherein one can describe general types of behavior that occur over time, and prove properties of a larger-scale system from the properties and interaction patterns of its components. For example, suppose we want an autonomous vehicle to maintain a distance of some safe R from other objects. To do so, several components must interact: a 2 sensor that approximates the real distance by an internal variable S0, a controller that uses S0 to decide what action A to take, and a motor that moves the vehicle with an 1 The well-known concept of emergence is not about possibilities, it is about prediction. -
VII Sheaf Theory
VII Sheaf Theory Claudia Centazzo and Enrico M. Vitale 1. Introduction To write a few lines of introduction to a few pages of work on a real corner stone of mathematics like sheaf theory is not an easy task. So, let us try with . two introductions. 1.1. First introduction: for students (and everybody else). In the study of ordinary differential equations, when you face a Cauchy problem of the form n (n) 0 (n¡1) (i) (i) y = f(x; y; y ; : : : ; y ) ; y (x0) = y0 you know that the continuity of f is enough to get a local solution, i.e. a solution defined on an open neighborhood Ux0 of x0: But, to guarantee the existence of a global solution, the stronger Lipschitz condition on f is required. P n In complex analysis, we know that a power series an(z ¡ z0) uniformly converges on any compact space strictly contained in the interior of the convergence disc. This is equivalent to the local uniform convergence: for any z in the open disc, there is an open neighborhood Uz of z on which the series converges uniformly. But local uniform convergence does not imply uniform convergence on the whole disc. This gap between local uniform convergence and global uniform convergence is the reason why the theory of Weierstrass analytic functions exists. These are only two simple examples, which are part of everybody’s basic knowl- edge in mathematics, of the passage from local to global. Sheaf theory is precisely meant to encode and study such a passage. Sheaf theory has its origin in complex analysis (see, for example, [18]) and in the study of cohomology of spaces [8] (see also [26] for a historical survey of sheaf theory). -
Toposes Toposes and Their Logic
Building up to toposes Toposes and their logic Toposes James Leslie University of Edinurgh [email protected] April 2018 James Leslie Toposes Building up to toposes Toposes and their logic Overview 1 Building up to toposes Limits and colimits Exponenetiation Subobject classifiers 2 Toposes and their logic Toposes Heyting algebras James Leslie Toposes Limits and colimits Building up to toposes Exponenetiation Toposes and their logic Subobject classifiers Products Z f f1 f2 X × Y π1 π2 X Y James Leslie Toposes Limits and colimits Building up to toposes Exponenetiation Toposes and their logic Subobject classifiers Coproducts i i X 1 X + Y 2 Y f f1 f2 Z James Leslie Toposes e : E ! X is an equaliser if for any commuting diagram f Z h X Y g there is a unique h such that triangle commutes: f E e X Y g h h Z Limits and colimits Building up to toposes Exponenetiation Toposes and their logic Subobject classifiers Equalisers Suppose we have the following commutative diagram: f E e X Y g James Leslie Toposes Limits and colimits Building up to toposes Exponenetiation Toposes and their logic Subobject classifiers Equalisers Suppose we have the following commutative diagram: f E e X Y g e : E ! X is an equaliser if for any commuting diagram f Z h X Y g there is a unique h such that triangle commutes: f E e X Y g h h Z James Leslie Toposes The following is an equaliser diagram: f ker G i G H 0 Given a k such that following commutes: f K k G H ker G i G 0 k k K k : K ! ker(G), k(g) = k(g). -
Kripke Semantics a Semantic for Intuitionistic Logic
Kripke Semantics A Semantic for Intuitionistic Logic By Jonathan Prieto-Cubides Updated: 2016/11/18 Supervisor: Andr´esSicard-Ram´ırez Logic and Computation Research Group EAFIT University Medell´ın,Colombia History Saul Kripke He was born on November # 13, 1940 (age 75) Philosopher and Logician # Emeritus Professor at # Princeton University In logic, his major # contributions are in the field of Modal Logic Saul Kripke In Modal Logic, we # attributed to him the notion of Possible Worlds Its notable ideas # ◦ Kripke structures ◦ Rigid designators ◦ Kripke semantics Kripke Semantics The study of semantic is the study of the truth Kripke semantics is one of many (see for instance # (Moschovakis, 2015)) semantics for intuitionistic logic It tries to capture different possible evolutions of the world # over time The abstraction of a world we call a Kripke structure # Proof rules of intuitionistic logic are sound with respect to # krikpe structures Intuitionistic Logic Derivation (proof) rules of the ^ connective Γ ` ' ^ ^-elim Γ ` ' 1 Γ ` ' Γ ` ^-intro Γ ` ' ^ Γ ` ' ^ ^-elim Γ ` 2 Intuitionistic Logic Derivation (proof) rules of the _ connective Γ ` ' _-intro1 Γ ` ' _ Γ ` ' _ Γ;' ` σ Γ; ` σ _-elim Γ ` σ Γ ` _-intro Γ ` ' _ 2 Intuitionistic Logic Derivation (proof) rules of the ! connective Γ;' ` Γ ` ' Γ ` ' ! !-intro !-elim Γ ` ' ! Γ ` Intuitionistic Logic Derivation (proof) rules of the : connective where :' ≡ ' !? Γ;' ` ? Γ ` ? :-intro explosion Γ ` :' Γ ` ' Intuitionistic Logic Other derivation (proof) rules Γ ` ' unit assume weaken Γ ` > Γ;' ` ' Γ; ` ' Classical Logic The list of derivation rules are the same above plus the following rule Γ; :' ` ? RAA Γ ` ' Kripke Model Def. -
1. Kripke's Semantics for Modal Logic
Ted Sider Kripke Modality seminar 1. Kripke’s semantics for modal logic 2A “Necessarily, A” 3A “Possibly, A” Lewis’s system K: Rules of inference: modus ponens, plus the rule of necessitation, which lets · you infer 2A from A. Axioms: those of propositional logic, plus: · 2(A B) (2A 2B) (K) ! ! ! Lewis’s system S4: Rules of inference: same as K · Axioms: those of K, plus: · 2A A (T) ! 2A 22A (S4) ! Proof-theoretic approach A logically implies B iff you can reason, using speci ed axioms and rules of inference, from A to B Model-theoretic approach A logically implies B iff B is true in every model in which A is true propositional logic model: an assignment of truth-values to sentence letters. predicate logic model: a domain and an interpretation function that assigns denotations to names and extensions to predicates. modal logic model: a set of “possible worlds”, each one containing an entire model of the old sort. 1 2A is true at world w iff A is true at every world accessible from w 3A is true at world w iff A is true at some world accessible from w Promising features of Kripke semantics: • Explaining logical features of modal logic (duality of 2 and 3; logical truth of axiom K) • Correspondence of Lewis’s systems to formal features of accessibility A cautionary note: what good is all this if 2 doesn’t mean truth in all worlds? 2. Kripke’s Naming and Necessity Early defenders of modal logic, for example C. I. Lewis, thought of the 2 as meaning analyticity.