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Formal Semantic of Natural Languages Focus: Vagueness

Formal Semantic of Natural Languages Focus: Vagueness. Introduction for TU-Wien / SS 2012 / 185.A53 / Fermüller Hilbert Heikenwälder / Werner Doubek. Content. Introducing reasoning about vagueness Phenomena of Vagueness Borderline cases Sorites paradoxa Multi-dimensional vagueness

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Formal Semantic of Natural Languages Focus: Vagueness

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  1. Formal Semantic of Natural LanguagesFocus: Vagueness Introduction for TU-Wien / SS 2012 / 185.A53 / Fermüller Hilbert Heikenwälder / Werner Doubek

  2. Content • Introducing reasoning about vagueness • Phenomena of Vagueness • Borderline cases • Sorites paradoxa • Multi-dimensional vagueness • Higher-order vagueness • Further notes to Vagueness • Vagueness is helpful • Not expected vagueness • Theories of Vagueness • Three-value logic • Infinite-value logic • Supervaluation • The epistemic/pragmatic approach • Persistency and elasticity of vagueness • Summary

  3. Introducing reasoning about vagueness • Precision is not ournature. Wearechildrenofvagueness. • Yetwelearnedtocreateislandsofprecisionwithintheoceanofvagueness. Thiswayweconquermathematics, logic, „hard“ science. But nowwedepend on precision. • Whentryingto understand ourorigins in vagueness, werequireprecision. • So now, mindsofvaguenesswholearnedtocreateprecisiongo back tovaguenessusingprecision. • Warning: Philosophymayharmyour mental stability!

  4. Phenomena of Vagueness (1) What is constituting vagueness, what is not ? What it isn’t: • Ambiguity: Example “bank”. • Undecidability: mathematical undecidability. • Uncertainity of a statement: Example “Next Monday it will rain in Vienna”. • (excessive) Generality:Example “coloured”. Generality is not always vague: Example ‘prime number’.

  5. Phenomena of Vagueness (2) What it is: • Borderline cases • Sorites paradoxa • Multi-dimensional vagueness • Higher-order vagueness

  6. Phenomena of Vagueness (3) Borderline cases • Questions: • What is the maximum height of a short man? • When develops a child to an adult? • Is this colour reddish or not? • Measurable Items: • Tallness: pygmy vs. Masai • Although borderline case: being tall or not being it for a Masai. • No simple measurement: • Hichcock’s: ‘All actors are children’ is not a borderline case. • A mothers statement: ‘My son is yet a child’, is a borderline-case.

  7. Phenomena of Vagueness (4) Sorites paradoxa • Eubulides of Milet (4. century b.C.) riddle of the heap of seeds (greek: soros) of a fern: • One single seed is not a heap. • If some seeds do not make a heap then one seed more does also not make a heap. • If you follow this, even 1 million of seeds build not a heap. • Reverse: • If there is a heap of sand-corns, • then it rests also a heap, if there is removed one single sand-corn. • So it follows that also as few as possible sand-corns are a heap. • Hints: • Sorites problems exist in great variety. • The introduction of borderlines does not always eliminate the problem (fuzzy boundaries).

  8. Phenomena of Vagueness (5) Multi-dimensional vagueness: • Questions: What makes a man interesting for a woman? What makes a women (or a scientific article) nice? • Properties can be: not single, not continuous, not measurable. • Bundle of parameters:The bundle can be varying in different directions.Two given ‘complex cases’ can be both ‘true’ (or both ‘false’),although the underlying parameters are quite different. • Vague predicates: Common used items (‘nice’ or ‘wonderful’) are often vague.In meaning: ‘the wonderful Greta Garbo’ vs. ‘the wonderful Kurt Gödel’.In quality: ‘the wonderful Greta Garbo’ vs. ‘the wonderful wife’ and ‘the wonderful Kurt Gödel’ vs. ‘the wonderful Hilbert Heikenwälder’.

  9. Phenomena of Vagueness (6) Higher-order vagueness: • Back to the borderline-case ‘Tallness’: • To decide, ‘this special case is a borderline case’ is a vague decision itself. • ‘The vagueness of the vagueness of . . . of vague’ is a given phenomenon. • A theory should be capable to model this. What we addressed in this chapter: • Ambiguity, uncertainity, undecidability and generality are not seen as phenomena of vagueness. • Borderline cases, sorites paradoxa, multi-dimensionality of vagueness and higher-order vagueness are phenomena of vagueness, which should be ‘managed’ by the theories of vagueness.

  10. Further Notes about Vagueness (1) Not expected vagueness The biologists definition of species: • First: ‘The individuals of a species are looking similarly’. • Second: ‘The individuals of a species are looking similarly and can interbreed and their offspring are fertile.’ Esatina Salamanders in California • Geographical: E1w E2w E3w central valley E4w E6w E5 • Interbreeding: Eachgroup also withitsneighbours, but no‘transitivity’! Result • The definition of the species seems (today) not to be sufficient. • Thinking ahead (to the year 3000): Probably time (by survival of few species) reduces the problem (no ‘transitivity-rule’ is hurt nor needed).

  11. Further Notes about Vagueness (2) Vagueness is helpful: • Example: The forgotten ‘blue’ book (out of 1000). • Seeking without color-check needs more time. • Seeking with color-check is more efficient. What we addressed in this chapter: • Sometimes definitions seem to be precisely, although they are not. • Vagueness helps for efficiency. Vagueness is succeeding.

  12. Theories of Vagueness (1) Many-valued logics • Borderline questions show certainly true or certainly false cases, but there are a lot of cases which are neither true nor false. • So we need some intermediate (non-classical) truth-value(s). Questions: • How many of them? • Are the sentential connectives truth-functional? • What is the semantics of connectives and quantifiers? • What is their validity and how is the classical notion to be generalized? Approaches to many-valued logics: • Three-value logic • Infinite-value logic

  13. Theories of Vagueness (2) Three-value logic: • Michael Tye used three truth-values: T=true, F=false and I=indefinite.Truth-tables for the connectives Ø, Ù, Ú, Þ, Û are defined. • Example:Prop. Truth-valuesProp. Truth-values .P T I Fp T TT I II F FFØp F I T q T I F T I F T I F pÚq T TTT I I T I F • No tautologies, (none of the basic connections are always true). The ‘tercium non datur’: pÚ Ø p is not true ifp is indefinite. • The third truth-value defines the existence of a gap between true and false (and not a ‘reality-based’ truth-value near to continuous measurements). • Multi-valued (finite) logic systems are not mightier than a ‘simple’ three-value logic.

  14. Theories of Vagueness (3) Infinite-value logic: • Truth values: real numbers in the interval [0, 1] (K.F.Machina). The value of the connectives Ø, Ù, Ú, Þ, Û are defined. • Example:|Øp| = 1 - |p| (where |p| denotes the truth-value of p) |pÚq| = max (|p|, |q|) (i.e. the math. maximum of the conjunct-values). • Validity as preservation of truth degrees: A conclusion is at least as true as the least true premise. • Motivation: allow a continuous range of truth-values according to the continuity of given facts (see the given sorites paradoxa). • Yes-No-Situations: Checking the statement ‘The angle is acute’ The continuous range of degrees of the angle should always lead to the ‘pure’ answer Yes or No.

  15. Theories of Vagueness (4) Supervaluation (1): • The truth of a statement is defined by checking all possible situations for the statement in the following way (see R.Keefe): • Definition: Be v(p) the truth-value of p in classical logic and let be given an index i to all precifications of a clause, then is defined as true, iff vi(p) is true for all i and V(p) is defined as false, iff vi(p) is false for all i; is not defined for the other cases (i.e. when there are existing some vi which are true and some other vi which are false). • The ‘undefined’-status: A ‘hidden’ third truth-value or the ‘gap-indicator’ of a clause. • D- and I-Operator:K.Fine defined the D- and I-Operator for a general clause A: • DA is true (‘definitely’ A) if A is true in the sense of supervaluation, t.m. at (all) the base points of the viewed space; • IA (’indefinitely’ A) is (in the sense of supervaluation) undefined.

  16. Theories of Vagueness (5) The epistemic/pragmaticapproach. • Back tocommunication. Wecommunicatewhatwethinkweperceive, andwethinkweperceiveroughlywhatisrelevanttous. • Imaginegivingthisintroduction in front ofcrocodiles. Accordingtowhichcriteria will theyclassifywhattheysee? • Simple judgementsareusuallysharedbyalmost all individuals. • Complex judgement issharedwithlessprobability! • Therefore, growingcomplexityplaces judgement increasinglyintothefreedomandresponsibilityofthelistener.

  17. Theories of Vagueness (6) • The epistemic/pragmaticapproach. • Untilnow, wehaveencounteredmethodsofreasoningaboutvaguestatementsandtheirtruthvalueswithrespectto real worldsituations. • STATEMENT <=> REAL WORLD • Nowweintroduceanotheractorintothescene: • STATEMENT <=> PERCEPTION/ <=> REAL WORLD JUDGEMENT • Let'sview “supervaluation” in thiscontext.

  18. Theories of Vagueness (7) • Supervaluation (2): • Supervaluationcanbeinterpretedas a modal logicapproach. E.g. in „V(P) istrueif P isdefinitelytrue”, „definitely” isturnedinto a modal operator. But definitelyis also a judgement aboutone's judgement. • Individual valuationscanbeidentifiedwith individual judgement, orwithspecificsystemsofprecification. Example: “approximately 300/345.4 millionyears“ – approximately 345.4 millionyears.” (whichimposeclassesofprecision). • BySupervaluation, „approximately“ is not definedwithinthe real world (supertrue). Itisdefinedwithinthe judgement system (true).

  19. Theories of Vagueness (8) Supervaluation implicitly creates a kind of three valued logic – and a problem with it: • Is (A is undefined) supertrue? • Is there a border case between a border case and a none border case? • Is there a border case of ((A is undefined) is undefined) and ((A is undefined) is defined)? • Probably supervaluation works best based on vagueness. • But it can work: If supervaluation relates to real world facts, and valuation relates to judgement, and we only remain in that view!

  20. Theories of Vagueness (9) What we addressed in this chapter: • Three-value logicis a ‘gap-theory’ for the indefinite truth-value. • Infinite-value logicis an approach to continuous parameters. • Supervaluationis a system of defining truth-values by checking all the truth-possibilities of a statement and concluding (depending on them) the super-truth or super-falseness of a statement. • The epistemic/pragmatic approachintroduces the perception of the individuals be sited between the statements and the real world and showed an interpretation of supervaluation.

  21. Persistency and elasticity A: “Will it work well?” B: “It will work!” A: “But will it work well?” B: “I guess ...” A: “What you guess? Will it work well or not?” B: “Yes, it will work well or not!” A: “You know what I mean! I need you to tell me that it will definitely work well!” B: “I think it is possible that it will definitely work well.” A: “I must go and tell C that it will work well!!!” B: “You can tell C that it will work well.” A: “So that is what you say?” B: “No, that is what you say!” A: “I need you to tell me that it will work well!” B: “Well – yes, it will work well!” A: “Thank God!” B: “.. unless it won't”

  22. Summary • Introduction: Vagueness is an efficient and succeeding element in natural languages, but it brings also some difficulties in communication. • The most significant phenomena of vagueness were noted:borderline-cases, sorites problems, multi-dimension and higher-order vagueness. Points of hidden vagueness: An example showed where an (un-) precise definition creates a transitivity-problem. • The main theories of vagueness were introduced:three-value logic, infinite-value logic, supervaluation and the epistemic/pragmatic approach. • Special questions: persistence and elasticity. So we hope to have given an interesting overview over the theme as short as an introduction has to be and as long as it is needed to awake some further interest for it.

  23. Formal Semantic of Natural LanguagesFocus: Vagueness End of Introduction for TU-Wien / SS 2012 / 185.A53 / Fermüller Thanks from Hilbert Heikenwälder and Werner Doubek

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