DOCSLIB.ORG

Syllogistic Reasoning with Intermediate Quantifiers

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Syllogistic Reasoning with Intermediate Quantifiers Syllogistic reasoning with intermediate quantifiers Niki Pfeifer ([email protected]) Department of Psychology; Hellbrunnerstrasse 34 5020 Salzburg, Austria Gernot D. Kleiter ([email protected]) Department of Psychology; Hellbrunnerstrasse 34 5020 Salzburg, Austria Abstract The present paper tries to exploit a not so well known non-standard development in syllogistic infer- A system of intermediate quantifiers (\Most S are P", m ence, namely intermediate quantifiers, for psychologi- \ n S are P") is proposed for evaluating the rational- cal purposes. The classical universal and the existential ity of human syllogistic reasoning. Some relations be- quantifiers in syllogisms are either too strict or too weak, tween intermediate quantifiers and probabilistic inter- pretations are discussed. The paper concludes by the respectively. On the one hand, the universal quantifier is generalization of the atmosphere, matching and conver- too strict because it does not allow for exceptions. One sion hypothesis to syllogisms with intermediate quanti- simple counterexample falsifies an all-assertion. In ev- fiers. Since our experiments are currently still running, eryday contexts exceptions are the rule, we reason with most of the paper is theoretical and intended to stimu- late psychological studies. defaults or rules of thumb that hold normally or most of the time. Nonmonotonic reasoning formalizes reasoning with exceptions and withdrawing conclusions in the light Introduction of new evidence. Experiments in which nonmonotonic reasoning is investigated are reported in Pfeifer & Kleiter In 1908, St¨orring published a psychological study on sim- (2003, 2005, in press). On the other hand, the existen- ple inference processes. The last part of his paper was tial quantifier is too weak because it quantifies only over devoted to syllogistic reasoning (St¨orring, 1908; Politzer, at least one individual. Such quantifiers hardly ever oc- 2004). He presented syllogism tasks like the following cur in everyday life reasoning. Quantifiers that|at least one to his subjects: implicitly|actually occur in everyday life reasoning like All p belong to class a,1 \most . ", \almost-all . ", or \90 percent . " are All a belong to class d. not expressible in classical syllogistics. Such quantifiers Therefore . that lie \in-between" the existential and the universal quantifier are called intermediate quantifiers 2. The subjects had to complete the conclusion. In 1935, the well known study of Woodworth & Sells (1935) was published. Most theoretical and empirical research work on syllogistic reasoning, though, was published during Table 1: The universal (A) and particular (I) affirmative, the last decades (Johnson-Laird & Byrne, 1994; Bacon and the universal (E) and particular (O) non-affirmative et al., 2003; Newstead, 2003; Morley et al., 2004). Syllo- moods of classical syllogisms and their predicate-logical gisms build a prototypical task to investigate human rea- (PL) form. soning in the field of monadic predicate calculus. Com- Mood Read PL-Formula parable prototypical tasks are Wasons's selection task in the field of propositional calculus and, more recently, also A All S are P 8x(Sx ! P x) in modal logic. Similarly, classical modus-ponens-type I At least one S is P 9x(Sx ^ P x) tasks investigate parts of propositional calculus. Syllo- E All S are not P 8x(Sx ! :P x) gisms are well-defined in standard logic and were studied O At least one S is not P 9x(Sx ^ :P x) in philosophy for more than two millennia. No wonder that they are considered as one of the benchmarks of human rationality. 2Also known as \generalized quantifiers”. Historically, the During the last 50 years many new approaches to old first system was proposed by Sir William Hamilton, his dis- logical problems were developed in philosophy, artificial pute with De Morgan is reprinted in (De Morgan, 1847). intelligence, and linguistics. These non-standard ap- Generalized quantifiers have been developed in mathematics proaches are often of special interest to psychology as and logics (Mostowski, 1957; Lindstr¨om, 1966; V¨a¨an¨anen, they try to do more justice to practical reasoning than 2004), artificial intelligence and computer science (Schwartz, 1997; Liu & Kerre, 1998; Nov´ak, 2001), linguistics (Barwise & classical logic. Typical examples are nonmonotonic rea- Cooper, 1981; van Bentham & ter Meulen, 1985; G¨ardenfors, soning or the probabilistic treatment of conditionals. 1987; van der Does & van Eijck, 1991; Keenan & Westerst˚ahl, 1997). Peterson's work is an improvement of Finch (1957) 1\Alle p geh¨oren zur Gattung a" (St¨orring, 1908, p.78) and is situated in the philosophy of language tradition. Table 2: The four figures of syllogisms. S, M, and P are Table 3: Classical syllogisms that are predicate-logically the subject, middle, and predicate term, respectively. (PL) and not predicate-logically valid. PL-valid Not PL-valid Fig. I Fig. II Fig. III Fig. IV Figure I AAA Barbara AAI Barbari Major Prem. MP P M MP P M AII Darii EAO Celaront Minor Prem. SM SM MS MS EAE Celarent Concl. SP SP SP SP EIO Ferio Figure II AEE Camestres AEO Camestrop AOO Baroco EAO Cesaro In the present paper we propose intermediate quanti- EAE Cesare fiers as developed by Peterson (1985, 2000) as a promis- EIO Festino ing candidate for investigating and evaluating human Figure III AII Datisi AAI Darapti syllogistic reasoning. After a short introduction to classi- cal syllogisms, we sketch the formal system of intermedi- EIO Ferison EAO Felapton ate quantifiers and formulate for this system some (clas- IAI Disamis sical) hypothesis of human syllogistic reasoning. The OAO Bocardo discussion of some relations between intermediate quan- Figure IV AEE Camenes AAI Bramantip tifiers and probabilistic interpretations concludes the pa- EIO Fresison AEO Camenop per. Since we are presently running experiments, we IAI Dimaris EAO Fesapo cannot provide empirical data yet. Classical Syllogisms Syllogisms with intermediate quantifiers The classical syllogism is a two-premise-one-conclusion argument made by three of four sentence types, or moods Intermediate quantifiers are quantifiers \between" the all (Table 1). The order of the predicates involved is reg- quantifier and the existential quantifier. Examples of in- termediate quantifiers are Almost-all S are P, Most S are imented by the four figures (Table 2). This leads to m 3 P Many S are P fractions S are 256 possible syllogisms, of which 24 are syllogistically , or quantifiers with , n valid. From a predicate logical point of view, only 15 P. As stated in the introduction, the universal quanti- syllogisms are predicate-logically valid (Table 3). All 15 fier is too strict and the existential quantifier is too weak a pri- predicate logically valid syllogisms are also syllogistically and not appropriate to model human reasoning on valid. The reason is that in syllogistics All S are P im- ori grounds. We therefore suggest to prefer intermediate plies At least one S is P (Some S are P ), because it is im- quantifiers for modeling human syllogistic reasoning. plicitly assumed that the subject term Sx is not empty. Intermediate quantifiers have hardly been investigated This assumption is called \existential import". In pred- by psychologists. Exceptions are the logical rule-based icate logic, 8x(Sx ! P x) does not entail 9x(Sx ^ P x). approach by Guerts (2003) and Chater & Oaksford's The reason is well known: In predicate logic, formulae (1999) Probability Heuristics Model. We will not dis- like 8x(Sx ! P x) can be \vacuously true". This is the cuss these approaches here. Studies on probability judg- case when there is no x such that x has the property S. ment as well can be close to studies on quantifiers with Then, clearly 9x(Sx ^ P x) is false (since :9xSx is as- fractions. sumed). However, if the existential assumption is made Peterson (2000) provides algorithms to evaluate syl- explicit, 9x(Sx ^ P x) is a predicate-logically valid con- logisms with intermediate quantifiers. These algorithms are correct and complete with respect to arbitrarily many clusion, 1 2 intermediate quantifier syllogisms ( 5 S are P, 5 S are P, m 8x(Sx ! P x) ^ 9xSx ` 9x(Sx ^ P x) : n S are P, . ). For his interpretation of intermediate quantifiers consider the Venn diagram in Figure 1 and The valid syllogisms got names like \Barbara" for Table 4. Figures 2, 3, and Figure 4 list the valid syllo- mnemotechnic reasons.4 The vowels in these names indi- gisms with the intermediate quantifiers Almost-all S are cate the moods of the first and second premise, and the P (P), Most S are P (T), and Many S are P (K) and mood of the conclusion of the respective syllogism (in their non-affirmative versions Almost-all S are :P (B), the order just stated) (Hughes & Londey, 1965). A list Most S are :P (D), and Many S are :P (G), respec- of valid syllogisms with their traditional names is given tively. Syllogism ATK of Figure I, e.g., is, All M are P in Table 3. (major premise), Most S are M (minor premise), there- Many S are P 3 3 fore (conclusion). The validity of figures 4 = 64 ways of constituting a two-premise argument (2 I, II, and IV can be directly inspected, since the interme- for the premises, 1 for the conclusion) by four moods (A, I, diate quantifiers strengthen the premises or weaken the E, O). Multiply 64 by the four figures gives 64 × 4 = 256 possible syllogisms. conclusion (solid or dashed arrows, respectively). Valid 4The first mnemotechnic verses of valid syllogisms ap- syllogisms of Figure III in the shaded boxes of Figure 3 peared in William of Sherwood's Introductiones Logicam are not derived trivially by strengthening or weakening. (Summulae), 13th Century (Kneale & Kneale, 1984, p. 231f.) Consider, e.g., syllogism TTI of Figure III: Most M are .................................
Load more

Recommended publications
  • Chapter 2 Introduction to Classical Propositional
    CHAPTER 2 INTRODUCTION TO CLASSICAL PROPOSITIONAL LOGIC 1 Motivation and History The origins of the classical propositional logic, classical propositional calculus, as it was, and still often is called, go back to antiquity and are due to Stoic school of philosophy (3rd century B.C.), whose most eminent representative was Chryssipus. But the real development of this calculus began only in the mid-19th century and was initiated by the research done by the English math- ematician G. Boole, who is sometimes regarded as the founder of mathematical logic. The classical propositional calculus was ¯rst formulated as a formal ax- iomatic system by the eminent German logician G. Frege in 1879. The assumption underlying the formalization of classical propositional calculus are the following. Logical sentences We deal only with sentences that can always be evaluated as true or false. Such sentences are called logical sentences or proposi- tions. Hence the name propositional logic. A statement: 2 + 2 = 4 is a proposition as we assume that it is a well known and agreed upon truth. A statement: 2 + 2 = 5 is also a proposition (false. A statement:] I am pretty is modeled, if needed as a logical sentence (proposi- tion). We assume that it is false, or true. A statement: 2 + n = 5 is not a proposition; it might be true for some n, for example n=3, false for other n, for example n= 2, and moreover, we don't know what n is. Sentences of this kind are called propositional functions. We model propositional functions within propositional logic by treating propositional functions as propositions.
    [Show full text]
  • Aristotle's Assertoric Syllogistic and Modern Relevance Logic*
    Aristotle’s assertoric syllogistic and modern relevance logic* Abstract: This paper sets out to evaluate the claim that Aristotle’s Assertoric Syllogistic is a relevance logic or shows significant similarities with it. I prepare the grounds for a meaningful comparison by extracting the notion of relevance employed in the most influential work on modern relevance logic, Anderson and Belnap’s Entailment. This notion is characterized by two conditions imposed on the concept of validity: first, that some meaning content is shared between the premises and the conclusion, and second, that the premises of a proof are actually used to derive the conclusion. Turning to Aristotle’s Prior Analytics, I argue that there is evidence that Aristotle’s Assertoric Syllogistic satisfies both conditions. Moreover, Aristotle at one point explicitly addresses the potential harmfulness of syllogisms with unused premises. Here, I argue that Aristotle’s analysis allows for a rejection of such syllogisms on formal grounds established in the foregoing parts of the Prior Analytics. In a final section I consider the view that Aristotle distinguished between validity on the one hand and syllogistic validity on the other. Following this line of reasoning, Aristotle’s logic might not be a relevance logic, since relevance is part of syllogistic validity and not, as modern relevance logic demands, of general validity. I argue that the reasons to reject this view are more compelling than the reasons to accept it and that we can, cautiously, uphold the result that Aristotle’s logic is a relevance logic. Keywords: Aristotle, Syllogism, Relevance Logic, History of Logic, Logic, Relevance 1.
    [Show full text]
  • Theorem Proving in Classical Logic
    MEng Individual Project Imperial College London Department of Computing Theorem Proving in Classical Logic Supervisor: Dr. Steffen van Bakel Author: David Davies Second Marker: Dr. Nicolas Wu June 16, 2021 Abstract It is well known that functional programming and logic are deeply intertwined. This has led to many systems capable of expressing both propositional and first order logic, that also operate as well-typed programs. What currently ties popular theorem provers together is their basis in intuitionistic logic, where one cannot prove the law of the excluded middle, ‘A A’ – that any proposition is either true or false. In classical logic this notion is provable, and the_: corresponding programs turn out to be those with control operators. In this report, we explore and expand upon the research about calculi that correspond with classical logic; and the problems that occur for those relating to first order logic. To see how these calculi behave in practice, we develop and implement functional languages for propositional and first order logic, expressing classical calculi in the setting of a theorem prover, much like Agda and Coq. In the first order language, users are able to define inductive data and record types; importantly, they are able to write computable programs that have a correspondence with classical propositions. Acknowledgements I would like to thank Steffen van Bakel, my supervisor, for his support throughout this project and helping find a topic of study based on my interests, for which I am incredibly grateful. His insight and advice have been invaluable. I would also like to thank my second marker, Nicolas Wu, for introducing me to the world of dependent types, and suggesting useful resources that have aided me greatly during this report.
    [Show full text]
  • John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected]
    John P. Burgess Department of Philosophy Princeton University Princeton, NJ 08544-1006, USA [email protected] LOGIC & PHILOSOPHICAL METHODOLOGY Introduction For present purposes “logic” will be understood to mean the subject whose development is described in Kneale & Kneale [1961] and of which a concise history is given in Scholz [1961]. As the terminological discussion at the beginning of the latter reference makes clear, this subject has at different times been known by different names, “analytics” and “organon” and “dialectic”, while inversely the name “logic” has at different times been applied much more broadly and loosely than it will be here. At certain times and in certain places — perhaps especially in Germany from the days of Kant through the days of Hegel — the label has come to be used so very broadly and loosely as to threaten to take in nearly the whole of metaphysics and epistemology. Logic in our sense has often been distinguished from “logic” in other, sometimes unmanageably broad and loose, senses by adding the adjectives “formal” or “deductive”. The scope of the art and science of logic, once one gets beyond elementary logic of the kind covered in introductory textbooks, is indicated by two other standard references, the Handbooks of mathematical and philosophical logic, Barwise [1977] and Gabbay & Guenthner [1983-89], though the latter includes also parts that are identified as applications of logic rather than logic proper. The term “philosophical logic” as currently used, for instance, in the Journal of Philosophical Logic, is a near-synonym for “nonclassical logic”. There is an older use of the term as a near-synonym for “philosophy of language”.
    [Show full text]
  • A Quasi-Classical Logic for Classical Mathematics
    Theses Honors College 11-2014 A Quasi-Classical Logic for Classical Mathematics Henry Nikogosyan University of Nevada, Las Vegas Follow this and additional works at: https://digitalscholarship.unlv.edu/honors_theses Part of the Logic and Foundations Commons Repository Citation Nikogosyan, Henry, "A Quasi-Classical Logic for Classical Mathematics" (2014). Theses. 21. https://digitalscholarship.unlv.edu/honors_theses/21 This Honors Thesis is protected by copyright and/or related rights. It has been brought to you by Digital Scholarship@UNLV with permission from the rights-holder(s). You are free to use this Honors Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/or on the work itself. This Honors Thesis has been accepted for inclusion in Theses by an authorized administrator of Digital Scholarship@UNLV. For more information, please contact [email protected]. A QUASI-CLASSICAL LOGIC FOR CLASSICAL MATHEMATICS By Henry Nikogosyan Honors Thesis submitted in partial fulfillment for the designation of Departmental Honors Department of Philosophy Ian Dove James Woodbridge Marta Meana College of Liberal Arts University of Nevada, Las Vegas November, 2014 ABSTRACT Classical mathematics is a form of mathematics that has a large range of application; however, its application has boundaries. In this paper, I show that Sperber and Wilson’s concept of relevance can demarcate classical mathematics’ range of applicability by demarcating classical logic’s range of applicability.
    [Show full text]
  • The Development of Mathematical Logic from Russell to Tarski: 1900–1935
    The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu Richard Zach Calixto Badesa The Development of Mathematical Logic from Russell to Tarski: 1900–1935 Paolo Mancosu (University of California, Berkeley) Richard Zach (University of Calgary) Calixto Badesa (Universitat de Barcelona) Final Draft—May 2004 To appear in: Leila Haaparanta, ed., The Development of Modern Logic. New York and Oxford: Oxford University Press, 2004 Contents Contents i Introduction 1 1 Itinerary I: Metatheoretical Properties of Axiomatic Systems 3 1.1 Introduction . 3 1.2 Peano’s school on the logical structure of theories . 4 1.3 Hilbert on axiomatization . 8 1.4 Completeness and categoricity in the work of Veblen and Huntington . 10 1.5 Truth in a structure . 12 2 Itinerary II: Bertrand Russell’s Mathematical Logic 15 2.1 From the Paris congress to the Principles of Mathematics 1900–1903 . 15 2.2 Russell and Poincar´e on predicativity . 19 2.3 On Denoting . 21 2.4 Russell’s ramified type theory . 22 2.5 The logic of Principia ......................... 25 2.6 Further developments . 26 3 Itinerary III: Zermelo’s Axiomatization of Set Theory and Re- lated Foundational Issues 29 3.1 The debate on the axiom of choice . 29 3.2 Zermelo’s axiomatization of set theory . 32 3.3 The discussion on the notion of “definit” . 35 3.4 Metatheoretical studies of Zermelo’s axiomatization . 38 4 Itinerary IV: The Theory of Relatives and Lowenheim’s¨ Theorem 41 4.1 Theory of relatives and model theory . 41 4.2 The logic of relatives .
    [Show full text]
  • Introduction to Formal Logic II (3 Credit
    PHILOSOPHY 115 INTRODUCTION TO FORMAL LOGIC II BULLETIN INFORMATION PHIL 115 – Introduction to Formal Logic II (3 credit hrs) Course Description: Intermediate topics in predicate logic, including second-order predicate logic; meta-theory, including soundness and completeness; introduction to non-classical logic. SAMPLE COURSE OVERVIEW Building on the material from PHIL 114, this course introduces new topics in logic and applies them to both propositional and first-order predicate logic. These topics include argument by induction, duality, compactness, and others. We will carefully prove important meta-logical results, including soundness and completeness for both propositional logic and first-order predicate logic. We will also learn a new system of proof, the Gentzen-calculus, and explore first-order predicate logic with functions and identity. Finally, we will discuss potential motivations for alternatives to classical logic, and examine how those motivations lead to the development of intuitionistic logic, including a formal system for intuitionistic logic, comparing the features of that formal system to those of classical first-order predicate logic. ITEMIZED LEARNING OUTCOMES Upon successful completion of PHIL 115, students will be able to: 1. Apply, as appropriate, principles of analytical reasoning, using as a foundation the knowledge of mathematical, logical, and algorithmic principles 2. Recognize and use connections among mathematical, logical, and algorithmic methods across disciplines 3. Identify and describe problems using formal symbolic methods and assess the appropriateness of these methods for the available data 4. Effectively communicate the results of such analytical reasoning and problem solving 5. Explain and apply important concepts from first-order logic, including duality, compactness, soundness, and completeness 6.
    [Show full text]
  • Common Sense for Concurrency and Strong Paraconsistency Using Unstratified Inference and Reflection
    Published in ArXiv http://arxiv.org/abs/0812.4852 http://commonsense.carlhewitt.info Common sense for concurrency and strong paraconsistency using unstratified inference and reflection Carl Hewitt http://carlhewitt.info This paper is dedicated to John McCarthy. Abstract Unstratified Reflection is the Norm....................................... 11 Abstraction and Reification .............................................. 11 This paper develops a strongly paraconsistent formalism (called Direct Logic™) that incorporates the mathematics of Diagonal Argument .......................................................... 12 Computer Science and allows unstratified inference and Logical Fixed Point Theorem ........................................... 12 reflection using mathematical induction for almost all of Disadvantages of stratified metatheories ........................... 12 classical logic to be used. Direct Logic allows mutual Reification Reflection ....................................................... 13 reflection among the mutually chock full of inconsistencies Incompleteness Theorem for Theories of Direct Logic ..... 14 code, documentation, and use cases of large software systems Inconsistency Theorem for Theories of Direct Logic ........ 15 thereby overcoming the limitations of the traditional Tarskian Consequences of Logically Necessary Inconsistency ........ 16 framework of stratified metatheories. Concurrency is the Norm ...................................................... 16 Gödel first formalized and proved that it is not possible
    [Show full text]
  • Traditional Logic and Computational Thinking
    philosophies Article Traditional Logic and Computational Thinking J.-Martín Castro-Manzano Faculty of Philosophy, UPAEP University, Puebla 72410, Mexico; [email protected] Abstract: In this contribution, we try to show that traditional Aristotelian logic can be useful (in a non-trivial way) for computational thinking. To achieve this objective, we argue in favor of two statements: (i) that traditional logic is not classical and (ii) that logic programming emanating from traditional logic is not classical logic programming. Keywords: syllogistic; aristotelian logic; logic programming 1. Introduction Computational thinking, like critical thinking [1], is a sort of general-purpose thinking that includes a set of logical skills. Hence logic, as a scientific enterprise, is an integral part of it. However, unlike critical thinking, when one checks what “logic” means in the computational context, one cannot help but be surprised to find out that it refers primarily, and sometimes even exclusively, to classical logic (cf. [2–7]). Classical logic is the logic of Boolean operators, the logic of digital circuits, the logic of Karnaugh maps, the logic of Prolog. It is the logic that results from discarding the traditional, Aristotelian logic in order to favor the Fregean–Tarskian paradigm. Classical logic is the logic that defines the standards we typically assume when we teach, research, or apply logic: it is the received view of logic. This state of affairs, of course, has an explanation: classical logic works wonders! However, this is not, by any means, enough warrant to justify the absence or the abandon of Citation: Castro-Manzano, J.-M. traditional logic within the computational thinking literature.
    [Show full text]
  • On Bar Recursive Interpretations of Analysis. Powell, Thomas Rhidian John
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Queen Mary Research Online On Bar Recursive Interpretations of Analysis. Powell, Thomas Rhidian John. The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the author For additional information about this publication click this link. http://qmro.qmul.ac.uk/jspui/handle/123456789/8637 Information about this research object was correct at the time of download; we occasionally make corrections to records, please therefore check the published record when citing. For more information contact [email protected] On Bar Recursive Interpretations of Analysis A Dissertation Submitted in Partial Fulfillment of the Requirements of the Degree of Doctor of Philosophy, Queen Mary University of London By Thomas Rhidian John Powell August 2013 ii Abstract This dissertation concerns the computational interpretation of analysis via proof interpre- tations, and examines the variants of bar recursion that have been used to interpret the axiom of choice. It consists of an applied and a theoretical component. The applied part contains a series of case studies which address the issue of understand- ing the meaning and behaviour of bar recursive programs extracted from proofs in analysis. Taking as a starting point recent work of Escard´oand Oliva on the product of selection functions, solutions to G¨odel'sfunctional interpretation of several well known theorems of mathematics are given, and the semantics of the extracted programs described. In particular, new game-theoretic computational interpretations are found for weak K¨onig's 0 lemma for Σ1-trees and for the minimal-bad-sequence argument.
    [Show full text]
  • Classical Logic, Argument and Dialectic
    Classical Logic, Argument and Dialectic M. D’Agostino1 and S. Modgil2 1. Department of Philosophy, University of Milan 2. Department of Informatics, King’s College London Abstract A well studied instantiation of Dung’s abstract theory of argumentation yields argumentation- based characterisations of non-monotonic inference over possibly inconsistent sets of classical formulae. This provides for single-agent reasoning in terms of argument and counter-argument, and distributed non-monotonic reasoning in the form of dialogues between computational and/or human agents. However, features of existing formali- sations of classical logic argumentation (Cl-Arg) that ensure satisfaction of rationality postulates, preclude applications of Cl-Arg that account for real-world dialectical uses of arguments by resource-bounded agents. This paper formalises dialectical classical logic argumentation that both satisfies these practical desiderata and is provably ratio- nal. In contrast to standard approaches to Cl-Arg we: 1) draw an epistemic distinction between an argument’s premises accepted as true, and those assumed true for the sake of argument, so formalising the dialectical move whereby arguments’ premises are shown to be inconsistent, and avoiding the foreign commitment problem that arises in dialogical applications; 2) provide an account of Cl-Arg suitable for real-world use by eschewing the need to check that an argument’s premises are subset minimal and con- sistent, and identifying a minimal set of assumptions as to the arguments that must be constructed from a set of formulae in order to ensure that the outcome of evaluation is rational. We then illustrate our approach with a natural deduction proof theory for propositional classical logic that allows measurement of the ‘depth’ of an argument, such that the construction of depth-bounded arguments is a tractable problem, and each increase in depth naturally equates with an increase in the inferential capabilities of real-world agents.
    [Show full text]
  • Some Basics of Classical Logic
    Some Basics of Classical Logic Theodora Achourioti AUC/ILLC, University of Amsterdam [email protected] PWN Vakantiecursus 2014 Eindhoven, August 22 Amsterdam, August 29 Theodora Achourioti (AUC/ILLC, UvA) Some Basics of Classical Logic PWN Vakantiecursus 2014 1 / 47 Intro Classical Logic Propositional and first order predicate logic. A way to think about a logic (and no more than that) is as consisting of: Expressive part: Syntax & Semantics Normative part: Logical Consequence (Validity) Derivability (Syntactic Validity) Entailment (Semantic Validity) Theodora Achourioti (AUC/ILLC, UvA) Some Basics of Classical Logic PWN Vakantiecursus 2014 2 / 47 Outline 1 Intro 2 Syntax 3 Derivability (Syntactic Validity) 4 Semantics 5 Entailment (Semantic Validity) 6 Meta-theory 7 Further Reading Theodora Achourioti (AUC/ILLC, UvA) Some Basics of Classical Logic PWN Vakantiecursus 2014 3 / 47 Syntax Propositional Logic The language of classical propositional logic consists of: Propositional variables: p; q; r::: Logical operators: :, ^, _, ! Parentheses: ( , ) Theodora Achourioti (AUC/ILLC, UvA) Some Basics of Classical Logic PWN Vakantiecursus 2014 4 / 47 Syntax Propositional Logic Recursive definition of a well-formed formula (wff) in classical propositional logic: Definition 1 A propositional variable is a wff. 2 If φ and are wffs, then :φ,(φ ^ ), (φ _ ), (φ ! ) are wffs. 3 Nothing else is a wff. The recursive nature of the above definition is important in that it allows inductive proofs on the entire logical language. Exercise: Prove that all wffs have an even number of brackets. Theodora Achourioti (AUC/ILLC, UvA) Some Basics of Classical Logic PWN Vakantiecursus 2014 5 / 47 Syntax Predicate Logic The language of classical predicate logic consists of: Terms: a) constants (a; b; c:::) , b) variables (x; y; z:::)1 n-place predicates P; Q; R::: Logical operators: a) propositional connectives, b) quantifiers 8, 9 Parentheses: ( , ) 1Functions are also typically included in first order theories.
    [Show full text]