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The Modal Logic of Potential Infinity, with an Application to Free Choice
The Modal Logic of Potential Infinity, With an Application to Free Choice Sequences Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Ethan Brauer, B.A. ∼6 6 Graduate Program in Philosophy The Ohio State University 2020 Dissertation Committee: Professor Stewart Shapiro, Co-adviser Professor Neil Tennant, Co-adviser Professor Chris Miller Professor Chris Pincock c Ethan Brauer, 2020 Abstract This dissertation is a study of potential infinity in mathematics and its contrast with actual infinity. Roughly, an actual infinity is a completed infinite totality. By contrast, a collection is potentially infinite when it is possible to expand it beyond any finite limit, despite not being a completed, actual infinite totality. The concept of potential infinity thus involves a notion of possibility. On this basis, recent progress has been made in giving an account of potential infinity using the resources of modal logic. Part I of this dissertation studies what the right modal logic is for reasoning about potential infinity. I begin Part I by rehearsing an argument|which is due to Linnebo and which I partially endorse|that the right modal logic is S4.2. Under this assumption, Linnebo has shown that a natural translation of non-modal first-order logic into modal first- order logic is sound and faithful. I argue that for the philosophical purposes at stake, the modal logic in question should be free and extend Linnebo's result to this setting. I then identify a limitation to the argument for S4.2 being the right modal logic for potential infinity. -
The Rise and Fall of LTL
The Rise and Fall of LTL Moshe Y. Vardi Rice University Monadic Logic Monadic Class: First-order logic with = and monadic predicates – captures syllogisms. • (∀x)P (x), (∀x)(P (x) → Q(x)) |=(∀x)Q(x) [Lowenheim¨ , 1915]: The Monadic Class is decidable. • Proof: Bounded-model property – if a sentence is satisfiable, it is satisfiable in a structure of bounded size. • Proof technique: quantifier elimination. Monadic Second-Order Logic: Allow second- order quantification on monadic predicates. [Skolem, 1919]: Monadic Second-Order Logic is decidable – via bounded-model property and quantifier elimination. Question: What about <? 1 Nondeterministic Finite Automata A = (Σ,S,S0,ρ,F ) • Alphabet: Σ • States: S • Initial states: S0 ⊆ S • Nondeterministic transition function: ρ : S × Σ → 2S • Accepting states: F ⊆ S Input word: a0, a1,...,an−1 Run: s0,s1,...,sn • s0 ∈ S0 • si+1 ∈ ρ(si, ai) for i ≥ 0 Acceptance: sn ∈ F Recognition: L(A) – words accepted by A. 1 - - Example: • • – ends with 1’s 6 0 6 ¢0¡ ¢1¡ Fact: NFAs define the class Reg of regular languages. 2 Logic of Finite Words View finite word w = a0,...,an−1 over alphabet Σ as a mathematical structure: • Domain: 0,...,n − 1 • Binary relation: < • Unary relations: {Pa : a ∈ Σ} First-Order Logic (FO): • Unary atomic formulas: Pa(x) (a ∈ Σ) • Binary atomic formulas: x < y Example: (∃x)((∀y)(¬(x < y)) ∧ Pa(x)) – last letter is a. Monadic Second-Order Logic (MSO): • Monadic second-order quantifier: ∃Q • New unary atomic formulas: Q(x) 3 NFA vs. MSO Theorem [B¨uchi, Elgot, Trakhtenbrot, 1957-8 (independently)]: MSO ≡ NFA • Both MSO and NFA define the class Reg. -
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). -
Logic-Sensitivity of Aristotelian Diagrams in Non-Normal Modal Logics
axioms Article Logic-Sensitivity of Aristotelian Diagrams in Non-Normal Modal Logics Lorenz Demey 1,2 1 Center for Logic and Philosophy of Science, KU Leuven, 3000 Leuven, Belgium; [email protected] 2 KU Leuven Institute for Artificial Intelligence, KU Leuven, 3000 Leuven, Belgium Abstract: Aristotelian diagrams, such as the square of opposition, are well-known in the context of normal modal logics (i.e., systems of modal logic which can be given a relational semantics in terms of Kripke models). This paper studies Aristotelian diagrams for non-normal systems of modal logic (based on neighborhood semantics, a topologically inspired generalization of relational semantics). In particular, we investigate the phenomenon of logic-sensitivity of Aristotelian diagrams. We distin- guish between four different types of logic-sensitivity, viz. with respect to (i) Aristotelian families, (ii) logical equivalence of formulas, (iii) contingency of formulas, and (iv) Boolean subfamilies of a given Aristotelian family. We provide concrete examples of Aristotelian diagrams that illustrate these four types of logic-sensitivity in the realm of normal modal logic. Next, we discuss more subtle examples of Aristotelian diagrams, which are not sensitive with respect to normal modal logics, but which nevertheless turn out to be highly logic-sensitive once we turn to non-normal systems of modal logic. Keywords: Aristotelian diagram; non-normal modal logic; square of opposition; logical geometry; neighborhood semantics; bitstring semantics MSC: 03B45; 03A05 Citation: Demey, L. Logic-Sensitivity of Aristotelian Diagrams in Non-Normal Modal Logics. Axioms 2021, 10, 128. https://doi.org/ 1. Introduction 10.3390/axioms10030128 Aristotelian diagrams, such as the so-called square of opposition, visualize a number Academic Editor: Radko Mesiar of formulas from some logical system, as well as certain logical relations holding between them. -
On Constructive Linear-Time Temporal Logic
Replace this file with prentcsmacro.sty for your meeting, or with entcsmacro.sty for your meeting. Both can be found at the ENTCS Macro Home Page. On Constructive Linear-Time Temporal Logic Kensuke Kojima1 and Atsushi Igarashi2 Graduate School of Informatics Kyoto University Kyoto, Japan Abstract In this paper we study a version of constructive linear-time temporal logic (LTL) with the “next” temporal operator. The logic is originally due to Davies, who has shown that the proof system of the logic corre- sponds to a type system for binding-time analysis via the Curry-Howard isomorphism. However, he did not investigate the logic itself in detail; he has proved only that the logic augmented with negation and classical reasoning is equivalent to (the “next” fragment of) the standard formulation of classical linear-time temporal logic. We give natural deduction and Kripke semantics for constructive LTL with conjunction and disjunction, and prove soundness and completeness. Distributivity of the “next” operator over disjunction “ (A ∨ B) ⊃ A ∨ B” is rejected from a computational viewpoint. We also give a formalization by sequent calculus and its cut-elimination procedure. Keywords: constructive linear-time temporal logic, Kripke semantics, sequent calculus, cut elimination 1 Introduction Temporal logic is a family of (modal) logics in which the truth of propositions may depend on time, and is useful to describe various properties of state transition systems. Linear-time temporal logic (LTL, for short), which is used to reason about properties of a fixed execution path of a system, is temporal logic in which each time has a unique time that follows it. -
A Unifying Field in Logics: Neutrosophic Logic
University of New Mexico UNM Digital Repository Faculty and Staff Publications Mathematics 2007 A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS - 6th ed. Florentin Smarandache University of New Mexico, [email protected] Follow this and additional works at: https://digitalrepository.unm.edu/math_fsp Part of the Algebra Commons, Logic and Foundations Commons, Other Applied Mathematics Commons, and the Set Theory Commons Recommended Citation Florentin Smarandache. A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS - 6th ed. USA: InfoLearnQuest, 2007 This Book is brought to you for free and open access by the Mathematics at UNM Digital Repository. It has been accepted for inclusion in Faculty and Staff Publications by an authorized administrator of UNM Digital Repository. For more information, please contact [email protected], [email protected], [email protected]. FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (sixth edition) InfoLearnQuest 2007 FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (sixth edition) This book can be ordered in a paper bound reprint from: Books on Demand ProQuest Information & Learning (University of Microfilm International) 300 N. Zeeb Road P.O. Box 1346, Ann Arbor MI 48106-1346, USA Tel.: 1-800-521-0600 (Customer Service) http://wwwlib.umi.com/bod/basic Copyright 2007 by InfoLearnQuest. Plenty of books can be downloaded from the following E-Library of Science: http://www.gallup.unm.edu/~smarandache/eBooks-otherformats.htm Peer Reviewers: Prof. M. Bencze, College of Brasov, Romania. -
A Unifying Field in Logics: Neutrosophic Logic. Neutrosophy, Neutrosophic Set, Neutrosophic Probability and Statistics
FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 FLORENTIN SMARANDACHE A UNIFYING FIELD IN LOGICS: NEUTROSOPHIC LOGIC. NEUTROSOPHY, NEUTROSOPHIC SET, NEUTROSOPHIC PROBABILITY AND STATISTICS (fourth edition) NL(A1 A2) = ( T1 ({1}T2) T2 ({1}T1) T1T2 ({1}T1) ({1}T2), I1 ({1}I2) I2 ({1}I1) I1 I2 ({1}I1) ({1} I2), F1 ({1}F2) F2 ({1} F1) F1 F2 ({1}F1) ({1}F2) ). NL(A1 A2) = ( {1}T1T1T2, {1}I1I1I2, {1}F1F1F2 ). NL(A1 A2) = ( ({1}T1T1T2) ({1}T2T1T2), ({1} I1 I1 I2) ({1}I2 I1 I2), ({1}F1F1 F2) ({1}F2F1 F2) ). ISBN 978-1-59973-080-6 American Research Press Rehoboth 1998, 2000, 2003, 2005 1 Contents: Preface by C. Le: 3 0. Introduction: 9 1. Neutrosophy - a new branch of philosophy: 15 2. Neutrosophic Logic - a unifying field in logics: 90 3. Neutrosophic Set - a unifying field in sets: 125 4. Neutrosophic Probability - a generalization of classical and imprecise probabilities - and Neutrosophic Statistics: 129 5. Addenda: Definitions derived from Neutrosophics: 133 2 Preface to Neutrosophy and Neutrosophic Logic by C. -
Aristotelian Temporal Logic: the Sea Battle
Aristotelian temporal logic: the sea battle. According to the square of oppositions, exactly one of “it is the case that p” and “it is not the case that p” is true. Either “it is the case that there will be a sea battle tomorrow” or “it is not the case that there will be a sea battle tomorrow”. Problematic for existence of free will, and for Aristotelian metaphysics. Core Logic – 2005/06-1ab – p. 3/34 The Master argument. Diodorus Cronus (IVth century BC). Assume that p is not the case. In the past, “It will be the case that p is not the case” was true. In the past, “It will be the case that p is not the case” was necessarily true. Therefore, in the past, “It will be the case that p” was impossible. Therefore, p is not possible. Ergo: Everything that is possible is true. Core Logic – 2005/06-1ab – p. 4/34 Megarians and Stoics. Socrates (469-399 BC) WWW WWWWW WWWWW WWWWW WW+ Euclides (c.430-c.360 BC) Plato (c.427-347 BC) WWW WWWWW WWWWW WWWWW WW+ Eubulides (IVth century) Stilpo (c.380-c.300 BC) Apollonius Cronus Zeno of Citium (c.335-263 BC) gg3 ggggg ggggg ggggg ggg Diodorus Cronus (IVth century) Cleanthes of Assos (301-232 BC) Chrysippus of Soli (c.280-207 BC) Core Logic – 2005/06-1ab – p. 5/34 Eubulides. Strongly opposed to Aristotle. Source of the “seven Megarian paradoxes”, among them the Liar. The Liar is attributed to Epimenides the Cretan (VIIth century BC); (Titus 1:12). -
Artificial Intelligence Dynamic Reasoning with Qualified Syllogisms
Artificial Intelligence ELSEVIER Artificial Intelligence 93 ( 1997 ) 105 167 Dynamic reasoning with qualified syllogisms Daniel G. Schwartz’ Department of Computer Science, Florida State University, Tallahassee. FL 32306-4019, USA Received January 1996: revised January 1997 Abstract A gualij%e~ syllogism is a classical Aristoteiean syllogism that has been “qualified” through the use of fuzzy quantifiers, likelihood modifiers, and usuality modifiers, e.g., “Most birds can Ry; Tweety is a bird; therefore, it is likely that Tweety can fly.” This paper introduces a formal logic Q of such syllogisms and shows how this may be employed in a system of nonmonotonj~ reasoning. In process are defined the notions of path logic and dynamic reasoning system (DRS) The former is an adaptation of the conventional formal system which explicitly portrays reasoning as an activity that takes place in time. The latter consists of a path logic together with a multiple- inhe~tance hierarchy. The hierarchy duplicates some of the info~ation recorded in the path logic, but additionally provides an extralogical spec#icity relation. The system uses typed predicates to formally distinguish between properties and kinds of things. The effectiveness of the approach is demonstrated through analysis of several “puzzles” that have appeared previously in the literature, e.g., Tweety the Bird, Clyde the Elephant, and the Nixon Diamond. It is also outlined how the DRS framework accommodates other reasoning techniques-in particular, predicate circumscription, a “localized” version of default logic, a variant of nonmonotonic logic, and reason maintenance. Furthermore it is seen that the same framework accomodates a new formulation of the notion of unless. -
Boxes and Diamonds: an Open Introduction to Modal Logic
Boxes and Diamonds An Open Introduction to Modal Logic F19 Boxes and Diamonds The Open Logic Project Instigator Richard Zach, University of Calgary Editorial Board Aldo Antonelli,y University of California, Davis Andrew Arana, Université de Lorraine Jeremy Avigad, Carnegie Mellon University Tim Button, University College London Walter Dean, University of Warwick Gillian Russell, Dianoia Institute of Philosophy Nicole Wyatt, University of Calgary Audrey Yap, University of Victoria Contributors Samara Burns, Columbia University Dana Hägg, University of Calgary Zesen Qian, Carnegie Mellon University Boxes and Diamonds An Open Introduction to Modal Logic Remixed by Richard Zach Fall 2019 The Open Logic Project would like to acknowledge the gener- ous support of the Taylor Institute of Teaching and Learning of the University of Calgary, and the Alberta Open Educational Re- sources (ABOER) Initiative, which is made possible through an investment from the Alberta government. Cover illustrations by Matthew Leadbeater, used under a Cre- ative Commons Attribution-NonCommercial 4.0 International Li- cense. Typeset in Baskervald X and Nimbus Sans by LATEX. This version of Boxes and Diamonds is revision ed40131 (2021-07- 11), with content generated from Open Logic Text revision a36bf42 (2021-09-21). Free download at: https://bd.openlogicproject.org/ Boxes and Diamonds by Richard Zach is licensed under a Creative Commons At- tribution 4.0 International License. It is based on The Open Logic Text by the Open Logic Project, used under a Cre- ative Commons Attribution 4.0 Interna- tional License. Contents Preface xi Introduction xii I Normal Modal Logics1 1 Syntax and Semantics2 1.1 Introduction.................... -
Accepting a Logic, Accepting a Theory
1 To appear in Romina Padró and Yale Weiss (eds.), Saul Kripke on Modal Logic. New York: Springer. Accepting a Logic, Accepting a Theory Timothy Williamson Abstract: This chapter responds to Saul Kripke’s critique of the idea of adopting an alternative logic. It defends an anti-exceptionalist view of logic, on which coming to accept a new logic is a special case of coming to accept a new scientific theory. The approach is illustrated in detail by debates on quantified modal logic. A distinction between folk logic and scientific logic is modelled on the distinction between folk physics and scientific physics. The importance of not confusing logic with metalogic in applying this distinction is emphasized. Defeasible inferential dispositions are shown to play a major role in theory acceptance in logic and mathematics as well as in natural and social science. Like beliefs, such dispositions are malleable in response to evidence, though not simply at will. Consideration is given to the Quinean objection that accepting an alternative logic involves changing the subject rather than denying the doctrine. The objection is shown to depend on neglect of the social dimension of meaning determination, akin to the descriptivism about proper names and natural kind terms criticized by Kripke and Putnam. Normal standards of interpretation indicate that disputes between classical and non-classical logicians are genuine disagreements. Keywords: Modal logic, intuitionistic logic, alternative logics, Kripke, Quine, Dummett, Putnam Author affiliation: Oxford University, U.K. Email: [email protected] 2 1. Introduction I first encountered Saul Kripke in my first term as an undergraduate at Oxford University, studying mathematics and philosophy, when he gave the 1973 John Locke Lectures (later published as Kripke 2013). -
Explaining Multi-Stage Tasks by Learning Temporal Logic Formulas from Suboptimal Demonstrations
Robotics: Science and Systems 2020 Corvalis, Oregon, USA, July 12-16, 2020 Explaining Multi-stage Tasks by Learning Temporal Logic Formulas from Suboptimal Demonstrations Glen Chou, Necmiye Ozay, and Dmitry Berenson Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109 Email: gchou, necmiye, dmitryb @umich.edu f g Abstract—We present a method for learning to perform multi- stage tasks from demonstrations by learning the logical structure and atomic propositions of a consistent linear temporal logic (LTL) formula. The learner is given successful but potentially suboptimal demonstrations, where the demonstrator is optimizing a cost function while satisfying the LTL formula, and the cost function is uncertain to the learner. Our algorithm uses Fig. 1. Multi-stage manipulation: first fill the cup, then grasp it, and then the Karush-Kuhn-Tucker (KKT) optimality conditions of the deliver it. To avoid spills, a pose constraint is enforced after the cup is grasped. demonstrations together with a counterexample-guided falsifi- In this paper, our insight is that by assuming that demonstra- cation strategy to learn the atomic proposition parameters and tors are goal-directed (i.e. approximately optimize an objective logical structure of the LTL formula, respectively. We provide function that may be uncertain to the learner), we can regu- theoretical guarantees on the conservativeness of the recovered atomic proposition sets, as well as completeness in the search larize the LTL learning problem without being given