Analogies between Proofs { A Case Study. Erica Melis. Universitat Saarbrucken. Fachbereich Informatik Saarbrucken.

Size: px
Start display at page:

Download "Analogies between Proofs { A Case Study. Erica Melis. Universitat Saarbrucken. Fachbereich Informatik Saarbrucken."

Transcription

1 Analogies between Proofs { A Case Study Erica Melis Universitat Saarbrucken Fachbereich Informatik 6600 Saarbrucken melis@cs.uni-sb.de This case study examines in detail the theorems and proofs that are shown by analogy in a mathematical textbook on semigroups and automata, that is widely used as an undergraduate textbook in theoretical computer science at German universities (P. Deussen, Halbgruppen und Automaten, Springer 1971). The study shows the important r^ole of restructuring a proof for nding analogous subproofs, and of reformulating a proof for the analogical transformation. It also emphasizes the importance of the relevant assumptions of a known proof, i.e., of those assumptions actually used in the proof. In this document we show the theorems, the proof structure, the subproblems and the proofs of subproblems and their analogues with the purpose to provide an empirical test set of cases for automated analogy-driven theorem proving. Theorems and their proofs are given in natural language augmented by the usual set of mathematical symbols in the studied textbook. As a rst step we encode the theorems in logic and show the actual restructuring. Secondly, we code the proofs in a Natural Deduction calculus such that a formal analysis This work was supported by a research scholarship of the Deutsche Forschungsgemeinschaft (DFG) 0

2 becomes possible and mention reformulations that are necessary in order to reveal the analogy. 1

3 Introduction Justied analogical reasoning proceeds by transferring an aspect from the base case s to a target case t based on the similarity of these cases with respect to a second aspect. The second and the rst aspect have to be inherently connected. For example, analogical reasoning takes as input the similarity of s and t with respect to their function and the connection between function and structure. Then it yields the commonality of s and t with respect to their structure. Within the context of (automated) theorem proving, problems and proofs are usually inherently connected, in the sense that a basic heuristic assumption stipulates that analogous theorems can be proved analogously also. This assumption is true in many cases. For analogical theorem proving the rst aspect of a connection is the pair (ass; thm) which we call problem, that consists of the set of relevant assumptions ass and of the theorem thm, and the second aspect is the proof of the theorem thm from the assumptions ass. To obtain an empirical test set and in order to gain practical experience with analogical reasoning in mathematical theorem proving we have studied the textbook \Halbgruppen und Automaten" (abbreviated as HUA in the following) [1], since it is particularly rich in proofs that are explicitly stated as analogous to previous proofs by the author. Furthermore the book already served as a test case for automated theorem proving for the Margraf Karl Refutation Procedure [2]. This empirical study is the basis for our own approach to analogy-driven theorem proving that is presented in detail in [5]. This approach is inherently based on the reformulation of the base problem together with the base proof, and on the reformulation of the target problem. The aim of the reformulation is to make the representation of the base and the target problem compatible such that the essential analogy is revealed, carrying over certain reformulated parts of the base proof as parts of a hypothetical target proof. The following study presents all theorems in HUA that are explicitly marked as analogous by the author. Theorems are rst given in English (our 2

4 translation) and coded in predicate logic. The proofs are then coded in a Natural Deduction format, such that a formal analysis becomes possible. The main nding is that a problem P 2 is called analogous to a problem P 1 in the textbook, if P 1 can be reformulated to a problem equal to P 2, or P 1 and P 2 can be reformulated to a common abstraction. Actually, P 2 is often called analogous to P 1 even if only an important subproblem of P 2 is analogous to a subproblem of P 1. Hence the standard approach to automated theorem proving by analogy (e.g., [6]), which is mainly based on symbol mapping of the base case to the target case for a given representation fails in many cases: There is no such symbol map unless the actually given representation is reformulated such that the analogy becomes visible. Why \Halbgruppen und Automaten"? The textbook \Halbgruppen und Automaten" [1] was chosen for this case study since it consists of the three chapters each of which is built upon the previous one, partially by analogies. This is the reason, why this particular textbook is so rich in explicit proofs by analogy and actually very much liked by students because of its uniform structure. The actual chapters are: Semigroups and relations Semigroups and semimoduls Automata. Notation The study is based on Natural Deduction (ND) proofs, since it turned out to be most natural to code the proofs given within the textbook in a proof calculus, whose (primitive) rules are presented in [4] which in turn is based on [3]. The displayed ND-proof lines do not always correspond to primitive rules but can easily splitted into several lines that correspond to primitive ND-rules. The reason is to keep the proofs more readable. In the following we quote the theorems by their original decimal numbering from HUA, for example, Theorem refers to Satz on page 182 in HUA. Sometimes a theorem is not explicitly stated in the textbook but just mentioned as analogous to some previous theorem, for example the existence of certain homomorphisms in semimoduls is directly carried over (i.e. 3

5 is analogous) from the existence of homomophisms in semigroups. Then, for instance, the theorem mentioned as analogous to theorem 5.7 in section 7 of HUA is denoted as As another notational convention, we denote part n of theorem m by m:n. The ND-proofs contain parts that are called relevant assumptions, and these may correspond to applications of the ND-rule called HYP (hypothesis introduction). The relevant assumptions are those hypotheses which cannot be omitted in the proof. As a further renement, the origin of the HYPrule is replaced by the name of the assumption that was introduced by the HYP-rule. For example, ASS means that the formula is an assumption of the problem, DEF points to a denition, and AX means that the hypothesis is an axiom. 4

6 Analogous Theorems and Proofs in HUA The following theorems are marked by the author of HUA to be shown by analogy: Theorem 6.3. (Chapter II) is analogous to theorem 3.3. (Ch.I). Theorem 6.6. (Ch.II) is analogous to theorem 3.6. (Ch.I). Theorem (Ch.II) is analogous to theorem 5.2. (Ch.I). Theorems 4.10, 4.11, and 4.12 (Ch.I) for sets can be taken over for the corresponding (sub-)theorems of 5.6, 5.7, and 5.8 for semigroups. Theorems 5.6, 5.7, and 5.8 (Ch.I) for semigroups are supposed to be carried over analogously to the corresponding theorems 7.5.6, 7.5.7, and for semimoduls (in Ch.II). Theorem 5.3 (Ch.I) is analogous to theorem 4.8 (Ch.I). Theorem is analogous to 9.8 (Ch.II). Theorem 13.7 (Ch.III) is analogous to theorem 6.9 (Ch.II). Theorem (Ch.III) is analogous to theorem 17.6 in the same section (Ch.III). Theorem 17.9 part 2 (Ch.III) is analogous to 17.9 part 1 (Ch.III). Two subproofs of theorem 17.6 are analogous. The more interesting analogies are examined in the following. 5

7 CASE 1: THEOREMS 3.3 and 6.3 The proof of theorem 6.3 is analogous to the proof of theorem 3.3 in HUA, where the respective theorems are given as: Theorem 3.3 Let ft i : i 2 Ig be a family of leftideals in the semigroup F. 1. Then S i T i is a leftideal in F. 2. If T i T i is not empty then T i T i is a leftideal in F. Theorem 6.3 Let ft i : i 2 Ig be a family of F -subsemimoduls in the F -semimodul S. 1. Then S i T i is an F -subsemimodul in S. 2. If T i T i is not empty then T i T i is an F -subsemimodul in S. The analogy of theorem 3.3 and theorem 6.3 is based on the correspondence between the denitions of a leftideal and of a subsemimodul (denition 3.1 and denition 6.2 in HUA) which are given as: Denition 3.1 A nonempty subset T of a semigroup F is called leftideal if F T T, where F T = fft : f 2 F; t 2 T g. Denition 6.2 A nonempty subset T of an F -semimodul S is called F-subsemimodul if F T T, where F T = fft : f 2 F; t 2 T g. Consider the analogy between the subproof of and the subproof of 6.3.1: Corresponding to the denition of a leftideal, it is shown for that S i T i is nonempty, S i T i is a subset of F, and F S i T i S i T i. Thus splitting the theorem into its conjunctive subparts, a straightforward proof structure of is the following: Part 1: Theorem: S i T i is nonempty, i.e. (expanding the denition of 'nonempty'): 9x(x 2 S i T i ). Relevant assumptions: 8i(i 2 I! 9x(x 2 T i )); the denition of S i T i. Part 2: Theorem: S i T i F. Relevant assumptions: the denition of S ; the denition of ; the assumption 6

8 8i(i 2 I! (T i F )). This part is demonstrated in more detail below. Part3: Theorem: F S i T i S i T i, e.g.(after expanding the denition of F T and of ): 8i; x; f(i 2 I ^ x 2 T i ^ f 2 F! f x 2 T i ) Relevant assumptions: the denition of F T ; the denition of ; the denition of S ; the assumption 8i(i 2 I! F T i T i ). Given the denition of an F -subsemimodul, it has to be shown in a proof of that S i T i is nonempty, S i T i is a subset of S, and F S i T i S i T i. Splitting the theorem of into its conjunctive subparts, a straightforward proof structure of becomes: Part 1: Theorem: S i T i is nonempty, i.e.(expanding the denition of `nonemptyness'): 9x(x 2 S i T i ). Relevant assumptions: 8i(i 2 I! 9x(x 2 T i )); the denition of S i T i. Part 2: Theorem: S i T i S. Relevant assumptions of the completed proof: the denition of S ; the denition of ; the assumption 8i(i 2 I! (T i S)). Part3: Theorem: F S i T i S i T i, i.e.(after expanding the denition of F T and of ): 8i; x; f(i 2 I ^ x 2 T i ^ f 2 F! f x 2 T i ) Relevant assumptions: the denition of F T ; the denition of ; the denition of S ; the assumption 8i(i 2 I! F T i T i ). We shall now give the explicit ND proofs of theorem part 2 and of theorem part 2. The rst proof is a translation of the given natural language proof in HUA into an ND-calculus, while the second proof is an analogical reconstruction (it is not given in the textbook but just mentioned as \to be shown analogously"). 7

9 ND proof for theorem part 2. NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8I; x(x 2 i2i T i $ 9i(i 2 I ^ x 2 T i )) S (DEF ) 2. ; 2 ` 8M; N (M N $ 8x(x 2 M! x 2 N )) (DEF ) 3. ; 3 ` 8i(i 2 I! T i F ) (ASS) S the proof 4. 4; ` t 2 i T i (HYP) 5. 4; 1 ` t 2 i T i $ 9i(i 2 I ^ t 2 T i ) (8D 1) 6. 4; 1 ` t 2 i T i! 9i(i 2 I ^ t 2 T i ) ($ D 5) 7. 4; 1 ` 9i(i 2 I ^ t 2 T i ) (! D 6) 8. 8; ` i 0 2 I ^ t 2 T i0 (HYP) 9. 8; ` t 2 T i0 (^D) 10. 8; ` i 0 2 I (^D) 11. ; 3 ` i 0 2 I! T i0 F (8D) 12. 8; 3 ` T i0 F (! D 10 11) 13. 8; 1, 2, 3 ` t 2 F (8D; $ D;! D ) 14. 4; 1, 2, 3 ` t 2 F (Choice 7 8) 15. ; 1, 2, 3 ` t 2 i TS i! t 2 F (DED 14) 16. ; 1, 2, 3 ` 8x(x 2 i T i! x 2 F ) (8I) 17. ; 2, 3 ` Si T i F ($ D;! D Thm. ; ` Si T i F 16 2) () ND proof for theorem part 2. NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8I; x(x 2 i2i T i $ 9i(i 2 I ^ x 2 T i )) S (DEF ) 2. ; 2 ` 8M; N (M N $ 8x(x 2 M! x 2 N )) (DEF ) 3. ; 3 ` 8i(i 2 I! T i S) (ASS) S the proof 4. 4; ` t 2 i T i (HYP) 5. 4; 1 ` t 2 i T i $ 9i(i 2 I ^ t 2 T i ) (8D 1) 6. 4; 1 ` t 2 i T i! 9i(i 2 I ^ t 2 T i ) ($ D 5) 7. 4; 1 ` 9i(i 2 I ^ t 2 T i ) (! D 6) 8. 8; ` i 0 2 I ^ t 2 T i0 (HYP) 9. 8; ` t 2 T i0 (^D) 10. 8; ` i 0 2 I (^D) 8

10 11. ; 3 ` i 0 2 I! T i0 S (8D) 12. 8; 3 ` T i0 S (! D 10 11) 13. 8; 2, 3 ` t 2 S (8D; $ D;! D ) 14. 4; 1, 2, 3 ` t 2 (Choice 7 8) 15. ; 1, 2, 3 ` t 2 i TS i! t 2 S (DED 14) 16. ; 1, 2, 3 ` 8x(x 2 i T i! x 2 S) (8I) 17. ; 1, 2, 3 ` Si T i S ($ D;! D Thm. ; ` Si T i S 16 2) () Discussion Conjunctive goal splitting yields the same proof structure for theorem and theorem Expanding the respective denitions then yields the same subtheorems and relevant assumptions for parts 1 and 3, respectively. For these parts the proofs are equal as well, due to the commonality of the subtheorems and of the relevant assumptions. For part 2 the subtheorems in and are not equal right away, however the dierence of the subtheorems and can be removed by replacing the constant F by the constant S. The symbol mapping F ) S applied to theorem 3.3 in order to obtain theorem 6.3 can be extended by matching the assumptions as well. After unfolding the denitions, the proof of theorem 3.3 contains only parts of the denitions 3.1 and 6.2 that correspond directly. These are called assumptions relevant in the base proof. The proof does not use those parts of the denition that actually dier, such as an ideal being contained in a semigroup and a subsemimodul being contained in a semimodul. Since the symbol mapping ff ) Sg is applied to the second subproblem of only, the mapping is consistent (one symbol is mapped to one symbol). The mapped versions of all assumptions relevant in the base proof all occur in the knowledge base or in the assumptions of the target problem 6.3, and this serves as a strong justication for this analogy formation. This example can be dealt with by standard techniques known from the literature on theorem proving by analogy, provided that means for structuring proofs and isolating relevant assumptions are present. 9

11 CASE 2: THEOREM 17.6 and ITS ANALOGUE Theorem 17.6 Let E F, then 1. E is a leftcongruence in the semigroup F, 2. E is compatible with E, 3. For all leftcongruences in F, which are compatible with, we have E, where E is dened in denition 17.5 (see below). Theorem analogue Let E F, then 1. E is a rightcongruence in the semigroup F, 2. E is compatible with E, 3. For all rightcongruences in F, which are compatible with, we have E, where E is dened in a denition analogous to 17.5 (see below). The following denitions are relevant assumptions: Deniton 17.4 Let be an equivalence relation on F and E F. is called compatible with E i for all f 2 F with (f) \ E 6= ; holds (f) E, where (x) = fy : (y; x) 2 g. Denition 5.1 Let be an equivalence relation on a semigroup F. Then is called a leftcongruence i for all g; f 1 ; f 2 2 F holds if (f 1 ; f 2 ) then (gf 1 ; gf 2 ). is called a rightcongruence i for all g; f 1 ; f 2 2 F holds if (f 1 ; f 2 ) then (f 1 g; f 2 g). The particular leftcongruence E in F is dened for E F as. Denition (f; g) 2 E $ ((f 2 E $ g 2 E)! 8h(h 2 F! (hf 2 E $ hg 2 E))). The particular rightcongruence E in F is dened for E F by the following analogous denition. Analogue to denition (f; g) 2 E $ ((f 2 E $ g 2 E)! 8h(h 2 F! (fh 2 E $ gh 2 E))). The proof structure of 17.6 is: 10

12 Part 1: Theorem: E is a leftcongruence in F. Relevant assumptions: the denition of a leftcongruence, the denition of a semigroup, the denition Part 2: Theorem: E is compatible with E. Relevant assumptions: the denition of [; the denition of ; denition 17.4; and denition Part 3: Theorem: leftcongruence() ^ compatible(; E)! E Relevant assumptions: the denition 17.4; the denition of leftcongruence; and the denition of. The proof structure of the analogue of 17.6 is: Part 1: Theorem: E is a rightcongruence in F Relevant assumptions: the denition of a rightcongruence; the denition of a semigroup; the analogue of denition Part 2: Theorem: E is compatible with E. Relevant assumptions: the denition of [; the denition of ; the analogue of denition 17.4; and the analogue of denition Part 3: Theorem: rightcongruence() ^ compatible(; E)! E. Relevant assumptions: the analogue of denition 17.4; the denition of rightcongruence; and the denition of. Discussion The symbol mapping fleftcongruence ) rightcongruence; E ) E g makes the subproblems of 17.6 and those of its analogous theorem equal but in this case the corresponding proofs still dier. This is due to the use of the different denitions of lef tcongruence and rightcongruence within the proofs which belong to the relevant assumptions. 11

13 The denition 17.5 can be transformed to the analogous one by term mapping (i.e. not just symbol mapping, as in the previous example). There are two possibilities for the term mapping that transform the assumptions of 17.6 into the assumptions of its analogue: the concrete term mapping: hf ) fh; hg ) gh; kf ) fk; kg ) gk; hkf ) fhk; hkg ) ghk for constants and variables h; f; g; k or, the term mapping based on the schema term 1 term 2 ) term 2 term 1 which could be used as well. The occurrence of the mapped versions of all relevant assumptions of the base proof in the knowledge base or in the assumptions of the analogue of problem serves as a justication for this analogy formation. This example could also be treated by techniques known from the literature, provided that means for isolating relevant assumptions are used in addition. 12

14 CASE 3: TWO ANALOGOUS PARTS OF This example demonstrates a kind of analogy which is used very often in mathematics. It is shown on the third part of theorem 17.6 of HUA. Theorem Let E F and let be a leftcongruence in F which is compatible with E, then E. The denitions of compatible(; E); leftcongruence(); E, and (x) are relevant assumptions. They have been given in the previous paragraph. The problem is ` E with = flef tcongruence(); compatible(; E); (E F ); semigroup(f )g. Some preparatory steps, usually not expressed explicitly by mathematicians, are necessary for the full ND-proof: 1. Expanding the denition of yields the problem ` 8x; y((x; y) 2! (x; y) 2 E ). 2. Expanding the denition of E yields the problem ` 8x; y((x; y) 2! (x 2 E $ y 2 E) ^ 8f(f 2 F! fx 2 E $ fy 2 E)). 3. Two applications of the Deduction Theorem yield the problem [ f(x 0 ; y 0 ) 2 ; (x 0 2 E $ y 0 2 E)g ` 8f(f 2 F! fx 0 2 E $ fy 0 2 E). 4. Restructuring (splitting) yields the subproblems [ f(x 0 ; y 0 ) 2 ; (x 0 2 E $ y 0 2 E)g ` 8f (f 2 F! f x 0 2 E! f y 0 2 E) [ f(x 0 ; y 0 ) 2 ; (x 0 2 E $ y 0 2 E)g ` 8f (f 2 F! f y 0 2 E! f x 0 2 E). 5. Application of the Deduction Theorem yields the subproblems (a) [ f(x 0 ; y 0 ) 2 ; (x 0 2 E $ y 0 2 E)g [ ff 0 2 F; f 0 x 0 2 Eg ` f 0 y 0 2 E (b) [ f(x 0 ; y 0 ) 2 ; (x 0 2 E $ y 0 2 E)g [ ff 0 2 F; f 0 y 0 2 Eg ` f 0 x 0 2 E. 13

15 Thus we have obtained the subproblems (a) and (b) which are supposed to be proved analogously in HUA. We present the two ND-proofs in the following and discuss the respective transformation afterwards. 14

16 ND Proof of theorem part (a) NNo S;D Formula Reason assumptions 1. ; 1 ` 8R; x; y8f(leftcongr(r) $ ((x; y) 2 R ^ f 2 F! (DEF) (fx; fy) 2 R)) 2. ; 2 ` leftcongr() (ASS) 3. ; 3 ` 8x; y(x 2 (y) $ (x; y) 2 ) (DEF) 4. ; 4 ` 8M; N : set; 8x(x 2 (M \ N ) $ x 2 M ^ x 2 N ) (DEF) 5. ; 5 ` 8M : set(nonempty(m ) $ 9x(x 2 M )) (DEF) 6. ; 6 ` 8E(compatible(; E) $ 8x(nonempty((x) \ E)! (DEF) (x) E)) 7. ; 7 ` compatible(; E) (ASS) 8. ; 8 ` 8M; N : set8x(m N! (x 2 M! x 2 N )) (DEF) 9. ; 9 ` 8R8x; y; z(equivrelr $ (x; x) 2 R ^ ((x; y) 2 R! (y; x) 2 R)...) (DEF equivrel) 10. ; 10 ` equivrel() (ASS) 11. ; 11 ` (x 0 ; y 0 ) 2 (ASS) 12. ; 12 ` f 0 2 F (ASS) 13. ; 13 ` f 0 x 0 2 E (ASS) proof 14. ; 9, 10 ` 8x; y; z((x; x) 2 ^ ((x; y) 2! (y; x) 2 )...) (8D,$D 9) 15. ; 9, 10 ` 8x((x; x) 2 ) (^D 14) 16. ; 1, 2, 12 ` (x 0 ; y 0 ) 2! (f 0 x 0 ; f 0 x 0 ) 2 (8D,$D,!D ) 17. ; 1, 2, 11, ` (f 0 x 0 ; f 0 y 0 ) 2 (! D 11 16) ; 3 ` (f 0 x 0 ; f 0 y 0 ) 2! f 0 x 0 2 (f 0 y 0 ) (8D,$D 3) 19. ; 1, 2, 3, 11, ` f 0 x 0 2 (f 0 y 0 ) (! D 17 18) ; 1, 2, 3, 11, ` f 0 x 0 2 (f 0 y 0 ) ^ f 0 x 0 2 E (^I 19 13) 12, ; 13, 1, 2, 3, ` f 0 x 0 2 ((f 0 y 0 ) \ E) (8D,$D,!D 4, 11, ) 22. ; 13, 1, 2, 3, ` 9x(x 2 ((f 0 y 0 ) \ E)) (9I 21) 4, 11, ; 5, 13, 1, 2, ` nonempty((f 0 y 0 ) \ E) (8D, 3, 4, 11, 12 $D,!D 5 22) 24. ; 6, 7 ` 8x(nonempty((x) \ E)! (x) E) ($D,!D ; 5, 6, 7, 13, 1, 2, 3, 4, 11, 12 7) ` (f 0 y 0 ) E (8D!D 23 24) 15

17 26. ; 8, 5, 6, 7, 13, 1, 2, 3, 4, 11, 12 ` f 0 y 0 2 (f 0 y 0 )! f 0 y 0 2 E (8D,!D 8 25) 27. ; 9, 10 ` (f 0 y 0 ; f 0 y 0 ) 2 (8D 15) 28. ; 3, 9, 10 ` f 0 y 0 2 (f 0 y 0 ) (8D,$ 29. ; 3, 9, 10, 8, 5, 6, 7, 13, 1, 2, 3, 4, 11, 12 D,!D 3 27) ` f 0 y 0 2 E (! D 28 26) Thm. ; ` f 0 y 0 2 E () 16

18 ND Proof of theorem part (b) NNo S;D Formula Reason assumptions 1. ; 1 ` 8R; x; y8f(leftcongr(r) $ ((x; y) 2 R ^ f 2 F! (DEF) (fx; fy) 2 R)) 2. ; 2 ` leftcongr() (ASS) 3. ; 3 ` 8x; y(x 2 (y) $ (x; y) 2 ) (DEF) 4. ; 4 ` 8M; N : set; 8x(x 2 (M \ N ) $ x 2 M ^ x 2 N ) (DEF) 5. ; 5 ` 8M : set(nonempty(m ) $ 9x(x 2 M )) (DEF) 6. ; 6 ` 8E(compatible(; E) $ 8x(nonempty((x) \ E)! (DEF) (x) E)) 7. ; 7 ` compatible(; E) (ASS) 8. ; 8 ` 8M; N : set8x(m N! (x 2 M! x 2 N )) (DEF) 9. ; 9 ` 8R8x; y; z(congruencer $ (x; x) 2 R ^ ((x; y) 2 R! (y; x) 2 R)...) (DEF equivrel) 10. ; 10 ` congruence() (ASS) 11. ; 11 ` (x 0 ; y 0 ) 2 (ASS) 12. ; 12 ` f 0 2 F (ASS) 13. ; 13 ` f 0 y 0 2 E (ASS) proof 14. ; 9, 10 ` 8x; y; z((x; x) 2 ^ ((x; y) 2! (y; x) 2 )...) (8D,$D 9) 15. ; 9, 10 ` 8x((x; x) 2 ) (^D 14) 16. ; 9, 10 ` (y 0 ; x 0 ) 2! (x 0 ; y 0 ) 2 (8D,$D,^D 9 10) 17. ; 9, 11 ` (y 0 ; x 0 ) 2 (! D 11 16) 18. ; 1, 2, 12 ` (y 0 ; x 0 ) 2! (f 0 y 0 ; f 0 x 0 ) 2 (8D,$D,!D ) 19. ; 1, 2, 9, 11, ` (f 0 y 0 ; f 0 x 0 ) 2 (! D 17 18) ; 3 ` (f 0 y 0 ; f 0 x 0 ) 2! f 0 y 0 2 (f 0 x 0 ) (8D,$D 3) 21. ; 1, 2, 3, 9, ` f 0 y 0 2 (f 0 x 0 ) (! D 19 20) 11, ; 1, 2, 3, 9, ` f 0 y 0 2 (f 0 x 0 ) ^ f 0 y 0 2 E (^I 21 13) 11, 12, ; 13, 1, 2, 3, ` f 0 y 0 2 ((f 0 x 0 ) \ E) (8D,$D,!D 4, 9, 11, ) 24. ; 13, 1, 2, 3, ` 9x(x 2 ((f 0 x 0 ) \ E)) (9I 23) 4, 9, 11, ; 5, 13, 1, 2, ` nonempty((f 0 x 0 ) \ E) (8D,$D,!D 3, 4, 9, 11, 5 24) ; 6, 7 ` 8x(nonempty((x) \ E)! (x) E) ($D,!D 6 7) 17

19 27. ; 5, 6, 7, 13, 1, 2, 3, 4, 9, 11, ; 8, 5, 6, 7, 13, 1, 2, 3, ` (f 0 x 0 ) E (8D!D 25 26) ` f 0 x 0 2 (f 0 x 0 )! f 0 x 0 2 E (8D!D 8 27) 4, 9, 11, ; 9, 10 ` (f 0 x 0 ; f 0 x 0 ) 2 (8D 15) 30. ; 3, 9, 10 ` f 0 x 0 2 (f 0 x 0 ) (8D,$ D,!D 3 29) 31. ; 9, 10, 8, 5, ` f 0 x 0 2 E (! D 30 28) Thm. 6, 7, 13, 1, 2, 3, 4, 11, 12 ; ` f 0 x 0 2 E () 18

20 Discussion An attempt to translate the rst subproof to the second subproof by the symbol mapping fx 0 ) y 0 ; y 0 ) x 0 g fails, since the relevant assumptions dier in ((x 0 ; y 0 ) 2 ) and ((y 0 ; x 0 ) 2 ) after this mapping, respectively. In order to obtain equal assumptions, ((x 0 ; y 0 ) 2 ) is to be replaced by ((y 0 ; x 0 ) 2 ) within the assumptions. ((y 0 ; x 0 ) 2 ) becomes a new subtheorem, which is proven by the subproof of (b) that consists of the lines 15 and

21 CASE 4: THEOREMS 5.7 and Let us look at the analogy that provides a proof of theorem 5.7 that is based on the proof of theorem by examining the proofs of theorem and theorem 5.7: A stronger reformulation technique works for these examples, namely, abstraction based on the denition of a homomorphism. Theorem Let S; T 1 ; T 2 be F -semimoduls. Let 1 : S 7! T 1 ; 2 : S 7! T 2 be two homomorphisms into the F -semimoduls T 1 and T 2, respectively, and let 1, 2 be the respectively induced leftcongruences. 1. If there exists a homomorphism : T 1 7! T 2 with 1 = 2, then Let 1 2 and if 1 is surjective, then there is a unique homomorphism : H 1 7! H 2 with 1 = 2. If in addition, 2 is surjective, then is surjective as well. Theorem 5.7 Let S 0 ; H 1 ; H 2 be semigroups. Let 1 : S 0 7! H 1 ; 2 : S 0 7! H 2 be two homomorphisms into the semigroups H 1 and H 2, respectively, and let 1, 2 be the respectively induced congruences. 1. If there exists a homomorphism : H 1 7! H 2 with 1 = 2, then Let 1 2 and if 1 is surjective, then there is a unique homomorphism : H 1 7! H 2 with 1 = 2. If in addition, 2 is surjective, then is surjective as well. The proofs are based on the denitions of a homomorphism in semigroups and a homomorphism in F-semimoduls, respectively: Denition 2.1 Let F and H be semigroups. A mapping : F 7! H is called a homomorphism (from F to H) i 8f; g(f; g 2 F! (f g) = (f) (g). Denition 7.1 Let S and T be F -semimoduls. A mapping : F 7! H 1 This analogy is harder to nd than the transformation of the proof of 5.7 to a proof of

22 is called a homomorphism (from S to T ) i 8f; s(f 2 F ^ s 2 S! (f s) = (f) (s). The proofs of theorem and of theorem 5.7 can now be structured as follows. The proof structure of becomes: Part 1: Theorem: 1 2 Relevant assumptions: the denition of 1 mapping with 1 = 2. and of 2 ; existence of a Part 2a: Theorem: There exists a function with (8z(z 2 S! 1 (z) = 2 (z)) ^ 8x9y((x 2 T 1! y 2 T 2 ) ^ (x) = y). Relevant assumptions: 2 is a mapping S 7! T 2 ; 1 is a mapping S 7! T 1 ; 1 is surjective; the comprehension axiom; = is an equivalence relation; the denition of 1 and 2 ; 1 2 ; the representation of functions as relations. Part 2b: Theorem: is the only mapping for which the theorem of 2a holds, i.e., 8 0 8x; y((x 2 S! 0 ( 1 (x)) = 2 (x))! (y 2 T 1! (y) = 0 (y))) Relevant assumptions: the denition of : ( 1 ) = 2 ; surjectivity of 1 ; transitivity of =. Part 2c: Theorem: is a F -semimodul-homomorphism, i.e., 8f; x(x 2 T 1 ^ f 2 F! (f x) = f (x)). Relevant assumptions: surjective 1 ; 1 is a homomorphism in an F - semimodul; 2 is a homomorphism in an F -semimodul; the denition of ; theorem of 2a. Part 2d: Theorem: If 2 is surjective then is surjective. The proof structure of 5.7 becomes: 21

23 Part 1: Theorem: 1 2 Relevant assumptions: the denition of 1 and of 2 ; the existence of a mapping with 1 = 2. Part 2a: Theorem: There exists a function with 8z(z 2 S 0! 1 (z) = 2 (z)) ^ 8x9y((x 2 H 1! y 2 H 2 ) ^ (x) = y). Relevant assumptions: 1 : F 7! H 1 is a mapping from a semigroup into a semigroup; 2 : F 7! H 2 is a mapping from a semigroup into a semigroup F ) H 2 ; 1 is surjective; the comprehension axiom; = is an equivalence relation; the denitions of 1 and 2 ; 1 2 ; the representation of functions as relations. Part 2b: Theorem: is the only mapping for which the theorem of 2a holds, i.e., 8 0 8x; y((x 2 S 0! 0 ( 1 (x)) = 2 (x))! (y 2 H 1! (y) = 0 (y))) Relevant assumptions: the denition of : ( 1 ) = 2 ; 1 is surjective; the transitivity of =. Part 2c: Theorem: is a semigroup-homomorphism, i.e., 8x; y(x 2 H 1 ^ y 2 H 1! (x y) = (x) (y)). Relevant assumptions: 1 is surjective; 1 is a semigroup-homomorphism; 2 is a semigroup-homomorphism; the denition of ; the theorem of 2a. Part 2d: If 2 is surjective then is surjective. Note that, the parts 1, 2a, 2b, 2d of theorem are equal to the corresponding parts of theorem 4.11 of HUA as well, and in general play an important r^ole. The crucial point for the transformation of the proof of theorem to the proof of theorem are the relevant assumptions of the respective part 1 of theorem 5.7 and of theorem 7.5.7, which dier in symbols only. Hence, they become equal by the symbol mapping ff ) S, H 1 ) T 1, and H 2 ) T 2 g. This symbol mapping is to be applied to the whole proof of

24 The proofs of parts 2c of theorem and theorem 5.7 are given next. For simplicity, let be a polymorphic function. 23

25 ND Proof of theorem part 2c NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8x; y; f(x 2 T 2^y 2 T 2 ^f 2 F ^x = y! f x = f y) (T 2 is semimodul) 2. ; 2 ` 8x; f(f 2 F ^ x 2 S! (f x) 2 S) (S is semimodul) 3. ; 3 ` 8x; y; f(x 2 T 1^y 2 T 1 ^f 2 F ^x = y! f x = f y) (Ax =T 1 -issemimodul) 4. ; 4 ` hom from S() $ 8f8x(f 2 F ^ x 2 S! (f x) = f (x)) (DEF hom from S ) (hom from T 1 ) 5. ; 5 ` hom from T 1 () $ 8f8x(f 2 F ^ x 2 T 1! (f x) = f (x)) 6. ; 6 ` 8x; f(f 2 F ^ x 2 T 1! f x 2 T 1 ) (T 1 -issemimodul) 7. ; 7 ` 8x; y; z(x = y ^ y = z! x = z) (Ax =transitive) 8. ; 8 ` 8x(x 2 S! 2 (x) 2 T 2 ) (Def 2 ) 9. ; 9 ` 8x(x 2 T 1! (x) 2 T 2 ) (lemma 2a) 10. ; 10 ` 8x(x 2 S! 1 (x) 2 T 1 ) (Def 1 ) 11. ; 11 ` 8x; y(x 2 T 1 ^ y 2 T 1 ^ x = y! (x) = (y)) (lemma 2a) 12. ; 12 ` 8x(x 2 S! ( 1 (x)) = 2 (x)) (lemma 2a) 13. ; 13 ` 8y(y 2 T 1! 9x(x 2 S ^ 1 (x) = y)) (ASS surjective 1 ) 14. ; 14 ` hom from S( 1 ) (ASS) 15. ; 15 ` hom from S( 2 ) (ASS) The Proof 16. ; 4, 14 ` 8f8x(f 2 F ^ x 2 S! 1 (f x) = f 1 (x)) ($ D;! D 4 14) 17. ; 4, 15 ` 8f8x(f 2 F ^ x 2 S! 2 (f x) = f 2 (x)) ($ D;! D 4 15) ; ` f 2 F (HYP) ; ` x 0 2 T 1 (HYP) (*) ; 13 ` 9y(y 2 S ^ 1 (y) = x 0 ) (8D;! D 19 13) ; 13 ` a 2 S ^ 1 (a) = x 0 (9D 20) ; 10, 13 ` a 2 S ^ 1 (a) = x 0 ^ 1 (a) 2 T 1 (8D; ^D; $ D; ^I 10 21) ; 10, 13 ` 1 (a) 2 T 1 ^ 1 (a) = x 0 (^ D 22) , 18; 10, 13 ` x 0 2 T 1 ^ 1 (a) 2 T 1 ^ f 2 F ^ 1 (a) = x 0 (^ I ) 24

26 25. 18, 19; 10, 13, , 18; 10, 13, , 18; 10, 3, 4, 11, , 19; 10, 3, 4, 14, , 18; 10, 3, 4, 2, , 19; 10, 3, 4, , 18; 10, 3, 4, 12, 1, 8, , 18; 10, 3, 4, 11, , 18; 10, 3, 4, 14, 15, 11, 7, 2, 8, 9, 6, ; 3, 4, 14, 4, 15, 11, 7, 2, 10, 8, 9, 6, 13, 12, ; 3, 4, 14, 15, 11, 7, 2, 10, 8, 9, 6, 13, 12, ; 3, 4, 14, 15, 11, 7, 2, 10, 8, 9, 6, 13, 12, 1, 5 ` f 1 (a) = f x 0 (8D;! D 3 24) ` a 2 S ^ 1 (a) = x 0 ^ 1 (a) 2 T 1 ^ f 1 (a) = f x 0 (^ I 25 22) (**) ` (f x 0 ) = (f 1 (a)) (^D;! D ) ` (f 1 (a)) = ( 1 (f a)) (8D;! D ) ` ( 1 (f a)) = 2 (f a) (8D,! D ) ` 2 (f a) = f 2 (a) (8D;! D ) ` f 2 (a) = f ( 1 (a)) (8D ) ` f ( 1 (a)) = f (x 0 ) (! D ) ` (f x 0 ) = f (x 0 ) (! D ) ` f 2 F ^ x 0 2 T 1! (f x 0 ) = f (x 0 )) (DED 33) ` 8f8x(f 2 F ^ x 2 T 1! (f x) = f (x)) (8I 34) ` hom from T 1 () ($ D;! D; 8D 5 35) ND Proof of theorem 5.7 part 2c NNo S;D Formula Reason m relevant assumptions 1. ; 1 ` 8x 1 ; x 2 ; y 1 ; y 2 (x 1 ; x 2 ; y 1 ; y 2 2 H 2 ^ x 1 = x 2 ^ y 1 = (Ax semigroup y 2! x 1 y 1 = x 2 y 2 ) H 2 ) 2. ; 2 ` 8x 1 ; x 2 (x 1 2 S 0 ^ x 2 2 S 0! x 1 x 2 2 S 0 ) (Ax S' semigroup) 25

27 3. ; 3 ` 8x 1 ; x 2 ; y 1 ; y 2 (x 1 ; x 2 ; y 1 ; y 2 2 H 1 ^ x 1 = x 2 ^ y 1 = y 2! x 1 y 1 = x 2 y 2 ) (Ax semigrouph 1 ) 4. ; 4 ` hom from S 0 () $ 8x8y(x 2 S 0 ^ y 2 S 0! (x y) = (x) (y)) (DEF hom from S' ) 5. ; 5 ` hom from H 1 () $ 8x8y(x 2 H 1 ^ y 2 H 1! (x y) = (x) (y)) (DEF hom from H 1 ) 6. ; 6 ` 8x; y(x 2 H 1 ^ y 2 H 1! x y 2 H 1 ) (Ax semigroup H 1 ) 7. ; 7 ` 8x; y; z(x = y ^ y = z! x = z) (Ax= transitive) 8. ; 8 ` 8x(x 2 S 0! 2 (x) 2 H 2 ) (ASS Def 2 ) 9. ; 9 ` 8x(x 2 H 1! (x) 2 H 2 ) (lemma 2a) 10. ; 10 ` 8x(x 2 S 0! 1 (x) 2 H 1 ) (Def 1 ) 11. ; 11 ` 8x; y(x 2 H 1 ^ y 2 H 1 ^ x = y! (x) = (y)) (lemma 2a) 12. ; 12 ` 8x(x 2 S 0! ( 1 (x)) = 2 (x)) (lemma 2a) 13. ; 13 ` 8y(y 2 H 1! 9x(x 2 S 0 ^ 1 (x) = y)) (ASS surj 1 ) 14. ; 14 ` hom in S 0 ( 1 ) (ASS) 15. ; 15 ` hom in S 0 ( 2 ) (ASS) The Proof 16. ; 4, 14 ` 8y8x(y 2 S 0 ^ x 2 S 0! 1 (x y) = 1 (x) 1 (y) ($ D;! D 4 14) 17. ; 4, 15 ` 8y8x(y 2 S 0 ^ x 2 S 0! 2 (x y) = 2 (x) 2 (y) ($ D;! D 4 15) ; ` x 10 2 H 1 (HYP) ; ` x 20 2 H 1 (HYP) (*) ; 13 ` 9y(y 2 S 0 ^ 1 (y) = x 10 ) (! D; 8D 18 13) ; 13 ` 9z(z 2 S 0 ^ 1 (z) = x 20 ) (! D; 8D 19 13) ; 13 ` a 1 2 S 0 ^ 1 (a 1 ) = x 10 (9D 20) ; 13 ` a 2 2 S 0 ^ 1 (a 2 ) = x 20 (9D 21) ; 10, 13 ` a 1 2 S 0 ^ 1 (a 1 ) = x 10 ^ 1 (a 1 ) 2 H 1 (^D; 8D; ^I;! D 22 10) ; 10, 13 ` a 2 2 S 0 ^ 1 (a 2 ) = x 20 ^ 1 (a 2 ) 2 H 1 (^D; 8D; ^I;! D 23 10) ; 10, 13 ` 1 (a 1 ) 2 H 1 ^ 1 (a 1 ) = x 10 (^ D 24) ; 10, 13 ` 1 (a 2 ) 2 H 1 ^ 1 (a 2 ) = x 20 (^ D 25) ; 10, 13 ` x 10 2 H 1 ^ 1 (a 1 ) 2 H 1 ^ 1 (a 1 ) = x 10 (^ I 18 26) ; 10, 13 ` x 20 2 H 1 ^ 1 (a 2 ) 2 H 1 ^ 1 (a 2 ) = x 20 (^ I 19 26) , 19; 10, 13 ` x 10 2 H 1 ^ 1 (a 1 ) 2 H 1 ^ 1 (a 1 ) = x 10 ^ x 20 2 H 1 ^ 1 (a 2 ) 2 H 1 ^ 1 (a 2 ) = x 20 (^ I 28 29) 26

28 31. 18, 19; 10, 13, , 19; 10, 13, , 19; 10, 3, 13, 11, , 19; 10, 3, 13, 4, 14, 11, 6, , 19; 10, 3, 13, 2, , 19; 10, 3, 13, 4, , 19; 10, 3, 13, 12,??, 8, , 19; 10, 3, 13, 11, 1, , 19; 10, 3, 13, 1, 4, 14, 15, 11, 7, 2, 8, 9, 12, ; 3, 13, 1, 4, 14, 15, 11, 7, 2, 8, 9, 12, 6, ; 3, 13, 1, 4, 14, 15, 11, 7, 2, 8, 9, 12, 6, ; 3, 13, 1, 4, 14, 15, 11, 7, 2, 8, 9, 12, 6, 5, 10 ` 1 (a 1 ) 1 (a 2 ) = x 10 x 20 (8D;! D 3 30) ` a 1 2 S 0 ^ 1 (a 1 ) = x 10 ^ 1 (a 1 ) 2 H 1 ^ a 2 2 S 0 ^ (^ I (a 2 ) = x 20^ 1 (a 2 ) 2 H 1^ 1 (a 1 ) 1 (a 2 ) = x 10 x 20 25) (**) ` (x 10 x 20 ) = ( 1 (a 1 ) 1 (a 2 )) (^D;! D ) ` ( 1 (a 1 ) 1 (a 2 )) = ( 1 (a 1 a 2 )) (^D; 8D;! D ) ` ( 1 (a 1 a 2 )) = 2 (a 1 a 2 ) (^D; 8D,! D ) ` 2 (a 1 a 2 ) = 2 (a 1 ) 2 (a 2 ) (^D; 8D;! D 17 32) ` 2 (a 1 ) 2 (a 2 ) = ( 1 (a 1 )) ( 1 (a 2 )) (^D; 8D ) ` ( 1 (a 1 )) ( 1 (a 2 )) = (x 10 ) (x 20 ) (^D;! D ) ` (x 10 x 20 ) = (x 10 ) (x 20 ) (^D;! D ) ` x 10 2 H 1 ^ x 20 2 H 1! (x 10 x 20 ) = (x 10 ) (x 20 ) (DED 39) ` 8x 1 8x 2 (x 1 2 H 1 ^ x 2 2 H 1! (x 1 x 2 ) = (x 1 ) (x 2 )) (8I 40) ` hom from H 1 () ($ D;! D; 8D 5 41) Discussion The subtheorems 2c of and 5.7 dier in more than one corresponding symbol. Thus symbol mapping is not sucient to obtain equal theorems and 27

29 assumptions of 5.7.2c and c. Term mapping, e.g., ff term(x) ) term(x) term(y)g is not sucient either, since part (*) would dier after the term mapping and a proof checker would not accept the transformation as a proof of 5.7.2c. Probably more importantly however, the theorem and the assumptions of 5.7.2c and c contain dierent subformulae of the form x 2 M and quantiers which have to be modied by the mapping as well. This problem is due to fact that the mapping of terms is essentially an abstraction by which some irrelevant symbols disappear. The actual justication for this abstraction is the occurrence of the denition of a homomorphism within the relevant assumptions. An analogy based on pure term mapping is not justied at all and hence the abstracting reformulation has to be preferred. Another reason for this preference is that less modication is to be done after this analogy formation. An reformulation of theorem and its proof to theorem 5.7 and its proof consists of three steps. 1. Abstraction of both problems (i.e., theorem and assumptions) c and c based on the meaning of the two respective denitions of homomorphism. The key is a reformulation of terms of the form f term(x) to terms Op(term(x)) for c and term1term2 to Op(term1,term2) with a function variable Op. This reformulation aects the denitions of homomorphism within the relevant assumptions: 8f8x(f 2 F ^ x 2 S! (f x) = f (x)) becomes 8x(x 2 S! (Op(x)) = Op((x))) by the mapping f term )Op(term) 8x; y(x 2 S 0 ^ y 2 S 0! (x y) = (x) (y)) becomes 8x; y(x 2 S 0 ^ y 2 S 0! (Op 0 (x; y)) = Op 0 ((x); (y))) by the mapping term1term2 )Op(term1,term2). The reformulation aects also the corresponding terms within the whole proof. Certain subformulae and quantiers become superuous and, hence, can be omitted. As a result we obtain the theorems and reformulated proofs c 0 and c The problems c 0 and c 0 are not equal yet. Their comparison suggests another reformulation of c 0 to c 00 in order to obtain equal abstracted assumptions and theorems, which increases 28

30 the number of arguments of Op in c. 0. This reformulation causes several additional changes within the reformulated proof. 3. Finally, to return to the original theorem and assumptions of c, a reversion of the abstraction of c has to be applied to c 00. All these reformulations have to be applied to the whole proofs and not only to the assumptions and the theorem. 29

31 CASE 5: THEOREMS 4.8 and 5.3 Theorem 4.8 Let and be two equivalence relations, then 1. ( \ ) is an equivalence relation and 2. ( [ ) t is the smallest equivalence relation, containing and. Theorem 5.3 Let and be two leftcongruences, then 1. ( \ ) is a leftcongruence and 2. ( [ ) t is the smallest leftcongruence containing and. The proofs of theorem 4.8 and theorem 5.3 can be structured as follows. The proof structure for theorem 4.8 becomes: Part 1: 1. Theorem: ( \ ) is an equivalence relation Subtheorem: reexivity of ( \ ), 1.2. Subtheorem: symmetry of ( \ ), 1.3. Subtheorem: transitivity of ( \ ). Part 2: 2. Theorem: ( [ ) t is an equivalence relation Subtheorem: reexivity of ( [ ) t, 2.2. Subtheorem: symmetry of ( [ ) t, 2.3. Subtheorem: transitivity of ( [ ) t. Part 3: Theorem: ( [ ) t is the smallest equivalence relation. The proof structure of 5.3 becomes: Part 1: 1.a. Subtheorem: ( \ ) is a leftcongruence. 1.a.1. Subsubtheorem: reexivity of ( \ ), 1.a.2. Subsubtheorem: symmetry of ( \ ), 1.a.3. Subsubtheorem: transitivity of ( \ ), 1.b. Subtheorem: (f 1 ; f 2 ) 2 ( \ )! (gf 1 ; gf 2 ) 2 ( \ ). Part 2: 2. Theorem: ( [ ) t is a leftcongruence 30

32 2.a. Subtheorem: ( [ ) t is an equivalence relation. 2.a.1. Subsubtheorem: reexivity of ( [ ) t, 2.a.2. Subsubtheorem: symmetry of ( [ ) t, 2.a.3. Subsubtheorem: transitivity of ( [ ) t, 2.b. Subtheorem: (f 1 ; f 2 ) 2 ( [ ) t! (gf 1 ; gf 2 ) 2 ( [ ) t. Part 3: Theorem: ( [ ) t is the smallest equivalence relation. Discussion This example illustrates particularly well the importance of structuring theorems and proofs for analogy-driven theorem proving: Some parts of the proofs become identical. For example, the proofs of the parts 1a, 2a, and 3 of theorem 5.3 are identical to the corresponding subproofs of theorem 4.8 since the problems have identical theorems and assumptions. Looking at the remaining parts it turns out that b can be proved analogously to and b can be proved analogously to These proofs are given in the following: ND Proof of theorem 4.8 part 1.2 NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8R(symm(R) $ 8x 1 ; x 2 ((x 1 ; x 2 ) 2 R! (x 2 ; x 1 ) 2 R)) (DEFsymm) 2. ; 2 ` 8R 1 ; R 2 ; x((x 2 (R 1 \ R 2 ) $ (x 2 R 1 ^ x 2 R 2 )) (DEF-\) 3. ; 3 ` symm() (ASS) 4. ; 4 ` symm() (ASS) The proof 5. 5; ` (f 1 ; f 2 ) 2 ( \ ) (HYP) 6. ; 2 ` (f 1 ; f 2 ) 2 ( \ )! (f 1 ; f 2 ) 2 ^ (f 1 ; f 2 ) 2 (8D; $ D 2) 7. 5; 2 ` (f 1 ; f 2 ) 2 (! D; ^D 6) 8. 5; 2 ` (f 1 ; f 2 ) 2 (! D; ^D 6) 9. ; 1 ` symm()! 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (x 2 ; x 1 ) 2 ) (8D; $ D 1) 10. ; 1, 3 ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (x 2 ; x 1 ) 2 ) (! D 9 3) 11. ; 1, 3 ` (f 1 ; f 2 ) 2! (f 2 ; f 1 ) 2 (8D 10) 12. ; 1 ` symm()! 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (x 2 ; x 1 ) 2 ) (8D; $ D 1) 13. ; 1, 4 ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (x 2 ; x 1 ) 2 ) (! D 12 4) 31

33 14. ; 1, 4 ` (f 1 ; f 2 ) 2! (f 2 ; f 1 ) 2 (8D 13) 15. 5; 2, 1, 3 ` (f 2 ; f 1 ) 2 (! D 11 7) 16. 5; 2, 1, 4 ` (f 2 ; f 1 ) 2 (! D 14 8) 17. 5; 2, 1, 4, 3 ` (f 2 ; f 1 ) 2 ( \ ) (8D; $ D 2 16) 18. ; 2, 1, 4, 3 ` (f 1 ; f 2 ) 2 ( \ )! (f 2 ; f 1 ) 2 ( \ ) (DED 17) 19. ; 2, 1, 4, 3 ` 8f 1 ; f 2 ((f 1 ; f 2 ) 2 ( \ )! (f 2 ; f 1 ) 2 ( \ )) (8I 18) 20. ; 2, 1, 4, 3 ` symm( \ ) (8D; $ D;! D 1 19) Thm. ; ` symm( \ ) () 32

34 ND Proof of theorem 5.3 part 1.b NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8R(leftcongruence(R) $ 8g; x 1 ; x 2 (g 2 H ^ (x 1 ; x 2 ) 2 R! (gx 1 ; gx 2 ) 2 R)) (DEFleftcongruence) 2. ; 2 ` 8R 1 ; R 2 ; x((x 2 (R 1 \ R 2 ) $ (x 2 R 1 ^ x 2 R 2 )) (DEF-\) 3. ; 3 ` leftcongruence() (ASS) 4. ; 4 ` leftcongruence() (ASS) The proof 5. 5; ` (f 1 ; f 2 ) 2 ( \ ) (HYP) 6. ; 2 ` (f 1 ; f 2 ) 2 ( \ )! (f 1 ; f 2 ) 2 ^ (f 1 ; f 2 ) 2 (8D; $ D 2) 7. 7; ` g 0 2 H (HYP) 8. 5; 2 ` (f 1 ; f 2 ) 2 (! D; ^D, 6) 9. 5; 2 ` (f 1 ; f 2 ) 2 (! D; ^D, 6) 10. ; 1 ` leftcongruence() $ 8g; x 1 ; x 2 (g 2 H ^ (x 1 ; x 2 ) 2 (8D; $ D 1)! (gx 1 ; gx 2 ) 2 ) 11. ; 1 ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (g 0 x 1 ; g 0 x 2 ) 2 ) (! D 10 3) 12. ; 1 ` leftcongruence() $ 8g; x 1 ; x 2 (g 2 H ^ (x 1 ; x 2 ) 2 (8D; $ D 1)! (gx 1 ; gx 2 ) 2 ) 13. 7; 1 ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2! (g 0 x 1 ; g 0 x 2 ) 2 ) (! D 12 4) 14. 7; 1 ` (f 1 ; f 2 ) 2! (g 0 f 1 ; g 0 f 2 ) 2 (8D 11) 15. 5, 7; 2, 1, 3 ` (g 0 f 1 ; g 0 f 2 ) 2 (! D, 14 8) 16. 7; 1 ` (f 1 ; f 2 ) 2! (g 0 f 1 ; g 0 f 2 ) 2 (8D 13) 17. 5, 7; 2, 1, 4 ` (g 0 f 1 ; g 0 f 2 ) 2 (! D, 16 9) 18. 5, 7; 2, 1, 4, ` (g 0 f 1 ; g 0 f 2 ) 2 ( \ ) (8D; $ D ) 19. 7; 2, 1, 4, 3 ` g 0 2 H ^ (f 1 ; f 2 ) 2 ( \ )! (g 0 f 1 ; g 0 f 2 ) 2 ( \ ) (DED 18) 20. ; 2, 1, 4, 3 ` 8g; f 1 ; f 2 (g 2 H ^ (f 1 ; f 2 ) 2 ( \ )! (gf 1 ; gf 2 ) 2 (8I 19) \ ) 21. ; 2, 1, 4, 3 ` leftcongruence( \ ) (8D; $ D;! D, 1 20) Thm. ; ` leftcongruence( \ ) () Discussion Symbol- or term mappings are not sucient for a transformation of to b. For example, the symbol mapping fsymm ) lef tcongrunceg is not sucient, since the denitions of symm and lef tcongruence (which are part 33

35 of the relevant assumptions) are not equal after this mapping. An additional term mapping would have to be restricted to certain occurrences of terms, because the overall mapping f(f 2 ; f 1 ) ) (g f 1 ; g f 2 )g or f(term1; term2) ) (g term1; g term2)g also yields f(f 1 ; f 2 ) ) (gf 2 ; gf 1 )g which is not desired at all. Furthermore, the reformulated proof cannot be veried for b because of missing sort declarations and quantiers. Furthermore, the theorem and the assumptions of and b contain subformulae of the form x 2 M and quantiers which have to be modi- ed by the mapping. This problem is due to fact that the necessary mapping of terms is essentially an abstraction by which some symbols irrelevant for the proof disappear, just as in the previous case. The actual justication for this abstraction is the occurrence within the relevant assumptions of the denitions of symm and lef tcongruence, which have the same characteristic structure. An analogy formation based on pure term mapping is not justied at all and hence the abstracting reformulation has to be preferred. A successful transformation is composed of an abstraction followed by a symbol mapping, and a subsequent reverse abstraction. 1. The abstraction of problem that yields problem ' changes the pairs (term 2 ; term 1 ), which are determined by the denition of symm, to terms f rev (term 1 ; term 2 ). The abstraction of problem b that yields problem b' transforms the pairs (g term 1 ; g term 2 ) to f g (term 1 ; term 2 ). These reformulations aect the pairs contained in the denition of symm(r) and lef tcongruence(r), respectively. It aects the derived terms within the whole proof and in addition, certain formulae and quantiers have to be removed. 2. The symbol mapping fsymm ) leftcongruence, f rev ) f g g is applied to problem and yields problem which is equal to problem b Finally, to return to the original problem b, a reversion of the abstraction of problem b has to be applied to problem In the following the ND-proofs of theorem 4.8 part 2.2 and of theorem 5.3 part 2.b are given. 34

36 ND Proof for theorem 4.8 part 2.2 NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8R(symm(R) $ 8x 1 ; x 2 ((x 1 ; x 2 ) 2 R! (x 2 ; x 1 ) 2 R)) (DEF symm) 2. ; 2 ` 8x(x 2 ( [ ) $ x 2 _ x 2 ) (DEF-[) 3. ; 3 ` 8x; y; k(k 2 N! ((x; y) 2 R 1! (y; x) 2 R 1 ) ^ (((x; y) 2 R k! (y; x) 2 R k )! ((x; y) 2 R k+1! (y; x) 2 R k+1 ))! 8n(n 2 N! (x; y) 2 R n! (y; x) 2 R n )) (Induction- AX) 4. ; 4 ` 8x; y((x; y) 2 ( [ ) 1 $ (x; y) 2 ( [ )) (DEF- ( [ ) 1 ) 5. ; 5 ` 8n; x; y(n 2 N! ((x; y) 2 ( [ ) n+1 $ 9z((x; z) 2 (DEF ( [ ( [ ) n ^ (z; y) 2 ( [ ) 1 ) _ ((z; y) 2 ) n+1 ) ( [ ) n ^ (x; z) 2 ( [ ) 1 )) 6. ; 6 ` 8x; y(x; y) 2 ( [ ) t $ 9n(n 2 N ^ (x; y) 2 ( [ ) n ) (DEF- ( [ ) t ) 7. ; 7 ` symm() (ASS) 8. ; 8 ` symm() (ASS) induction base 9. 9; ` (f 1 ; f 2 ) 2 ( [ ) 1 (HYP) 10. 9; ` (f 1 ; f 2 ) 2 _ (f 1 ; f 2 ) 2 (8D;! D 2 9) ; ` (f 1 ; f 2 ) 2 (HYP) ; 1, 7 ` (f 2 ; f 1 ) 2 (8D;! D ) ; 1, 7, 2 ` (f 2 ; f 1 ) 2 ( [ ) (8D; $ D;! D 2 12) ; 1, 7, 2, ` (f 2 ; f 1 ) 2 ( [ ) 1 (8D; $ 4 D;! D 13 4) 15. ; 1, 7, 2, 4 ` (f 1 ; f 2 ) 2! (f 2 ; f 1 ) 2 ( [ ) 1 (DED 14) ; ` (f 1 ; f 2 ) 2 (HYP) ; 1, 8 ` (f 2 ; f 1 ) 2 (8D;! D ) ; 1, 2, 8 ` (f 2 ; f 1 ) 2 ( [ ) (8D; $ D;! D 2 17) ; 1, 2, 8, ` (f 2 ; f 1 ) 2 ( [ ) 1 (8D; $ 4 D;! D 18 4) 20. ; 1, 2, 8, 4 ` (f 1 ; f 2 ) 2! (f 2 ; f 1 ) 2 ( [ ) 1 (DED 19) 35

37 21. 9; 1, 2, 8, 7, ; 1, 2, 8, 7, 4 ` (f 2 ; f 1 ) 2 ( [ ) 1 (_D ) ` 8f 1 ; f 2 ((f 1 ; f 2 ) 2 ( [ ) 1! (f 2 ; f 1 ) 2 ( [ ) 1 (DED,8I 21) The proof induction step ; ` k 2 N (HYP) ; ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2 ( [ ) k! (x 2 ; x 1 ) 2 ( [ ) k ) (Induction- HYP) ; ` (f 1 ; f 2 ) 2 ( [ ) k+1 (HYP) , 23; 5 ` 9z(((f 1 ; z) 2 ( [ ) k ^ (z; f 2 ) 2 ( [ ) 1 ) _ ((z; f 2 ) 2 ($ D;! D ( [ ) k ^ (f 1 ; z) 2 ( [ ) 1 )) 5 25) ; ` ((f 1 ; x 0 ) 2 ( [ ) k ^ (x 0 ; f 2 ) 2 ( [ ) 1 ) _ ((x 0 ; f 2 ) 2 (HYP) ( [ ) k ^ (f 1 ; x 0 ) 2 ( [ ) 1 ) case ; ` (f 1 ; x 0 ) 2 ( [ ) k ^ (x 0 ; f 2 ) 2 ( [ ) 1 (HYP) ; ` (f 1 ; x 0 ) 2 ( [ ) k (^D 28) ; ` (x 0 ; f 2 ) 2 ( [ ) 1 (^D 28) , 23; ` (x 0 ; f 1 ) 2 ( [ ) k (8D;! D 24 29) , 24; ` (f 2 ; x 0 ) 2 ( [ ) 1 (8D;! D 24 30) , 28, 23; ` (f 2 ; x 0 ) 2 ( [ ) 1 ^ (x 0 ; f 1 ) 2 ( [ ) k ) (^I 31 32) 34. ; 24, 28, 23 ` (f 2 ; x 0 ) 2 ( [ ) 1 ^ (x 0 ; f 1 ) 2 ( [ ) k _ (f 2 ; x 0 ) 2 (_I 33) ( [ ) k ^ (x 0 ; f 1 ) 2 ( [ ) , 24, 23; ` 9z((f 2 ; z) 2 ( [ ) 1 ^ (z; f 1 ) 2 ( [ ) k _ (f 2 ; z) 2 (^I; 9I 34) ( [ ) k ^ (z; f 1 ) 2 ( [ ) 1 ) , 24, 23; 5 ` (f 2 ; f 1 ) 2 ( [ ) k+1 (8D; $ D;! D 35 5) case ; ` (x 0 ; f 2 ) 2 ( [ ) k ^ (f 1 ; x 0 ) 2 ( [ ) 1 (HYP) ; ` (x 0 ; f 2 ) 2 ( [ ) k (^D 37) ; ` (f 1 ; x 0 ; ) 2 ( [ ) 1 (^D 37) , 23; ` (f 2 ; x 0 ) 2 ( [ ) k (8D;! D 24 38) , 24; ` (x 0 ; f 1 ) 2 ( [ ) 1 (8D;! D 24 39) , 37, 23; ` (f 2 ; x 0 ) 2 ( [ ) 1 ^ (x 0 ; f 1 ) 2 ( [ ) k ) (^I 40 41) 43. ; 24, 37, 23 ` (f 2 ; x 0 ) 2 ( [ ) 1 ^ (x 0 ; f 1 ) 2 ( [ ) k ) _ (f 2 ; x 0 ) 2 (_I 42) ( [ ) k ^ (x 0 ; f 1 ) 2 ( [ ) 1 ) , 24, 23; ` 9z((z; f 1 ) 2 ( [ ) 1 ^ (f 2 ; z) 2 ( [ ) k _ (f 2 ; z) 2 (9I 43) ( [ ) k ^ (z; f 1 ) 2 ( [ ) 1 ) , 24, 23; 5 ` (f 2 ; f 1 ) 2 ( [ ) k+1 (8D; $ D;! D 44 5) 36

38 46. 37, 28, 24, ` (f 2 ; f 1 ) 2 ( [ ) k+1 (_D , 27; 5 27) , 24, 37, ` (f 2 ; f 1 ) 2 ( [ ) k+1 (CHOICE 25, 28; ) , 24, 28, ` 8f 1 ; f 2 ((f 1 ; f 2 ) 2 ( [ ) k+1! (f 2 ; f 1 ) 2 ( [ ) k+1 ) (DED,8I 47) 37; ; 5 ` k 2 N ^ 8x 1 ; x 2 (((x 1 ; x 2 ) 2 ( [ ) k! (x 2 ; x 1 ) 2 (DED 48) ( [ ) k )! 8f 1 ; f 2 ((f 1 ; f 2 ) 2 ( [ ) k+1! (f 2 ; f 1 ) 2 ( [ ) k+1 )) 50. ; 1, 2, 3, 4, ` 8f 1 ; f 2 8n(n 2 N ^ (f 1 ; f 2 ) 2 ( [ ) n! (f 2 ; f 1 ) 2 (8I; ^I;! 5, 7, 8 ( [ ) n ) D ) for ( [ ) t ; ` (f 1 ; f 2 ) 2 ( [ ) t (HYP) ; 6 ` 9n(n 2 N ^ (f 1 ; f 2 ) 2 ( [ ) n ) (8D; $ D;! D 6 51) ; ` m 0 2 N ^ (f 1 ; f 2 ) 2 ( [ ) m0 (HYP) ; 1, 2, 3, 4, 5, 7, 8 ` m 0 2 N ^ (f 2 ; f 1 ) 2 ( [ ) m0 (8D;! D 53 50) ; 1, 2, 3, ` 9n(n 2 N ^ (f 2 ; f 1 ) 2 ( [ ) n ) (9I 54) 4, 5, 7, ; 1, 2, 3, ` (f 2 ; f 1 ) 2 ( [ ) t (! D 6 55) 4, 5, 7, ; 6, 1, 2, 3, 4, 5, 7, 8 ` f 2 ; f 1 ) 2 ( [ ) t (CHOICE ) 58. ; 6, 1, 2, 3, ` (f 1 ; f 2 ) 2 ( [ ) t! (f 2 ; f 1 ) 2 ( [ ) t (DED 57) 4, 5, 7, ; 6, 1, 2, 3, ` 8f 1 ; f 2 ((f 1 ; f 2 ) 2 ( [ ) t! (f 2 ; f 1 ) 2 ( [ ) t ) (8I 58) 4, 5, 7, ; 6, 1, 2, 3, ` symm( [ ) t ($ D 59 1) 4, 5, 7, 8 Thm. ; ` symm( [ ) t () 37

39 ND Proof for theorem 5.3 part 2.b NNo S;D Formula Reason relevant assumptions 1. ; 1 ` 8R(leftcongruence(R) $ 8x 1 ; x 2 ; g(g 2 F (x 1 ; x 2 ) 2 R! (gx 1 ; gx 2 ) 2 R)) (DEFleftcongruence) 2. ; 2 ` 8x(x 2 ( [ ) $ x 2 _ x 2 ) (DEF-[) 3. ; 3 ` 8k; x; y; x 1 ; y 1 ; x 2 ; y 2 ; x 3 ; y 3 ; g(k 2 N ^ g 2 F! ((x; y) 2 R 1! (gx; gy) 2 R 1 ) ^ (((x 1 ; y 1 ) 2 R k! (Induction- AX) (gx 1 ; gy 1 ) 2 R k )! ((x 2 ; y 2 ) 2 R k+1! (gx 2 ; gy 2 ) 2 R k+1 ))! 8n(n 2 N! (x 3 ; y 3 ) 2 R n! (gx; gy) 2 R n )) 4. ; 4 ` 8x; y((x; y) 2 ( [ ) 1 $ (x; y) 2 ( [ )) (DEF- 5. ; 5 ` 8n; x; y(n 2 N! ((x; y) 2 ( [ ) n+1 $ 9z((x; z) 2 ( [ ) n ^ (z; y) 2 ( [ ) 1 ) _ ((z; y) 2 ( [ ) n ^ (x; z) 2 ( [ ) 1 ))) ( [ ) 1 ) (DEF ( [ ) n+1 ) 6. ; 6 ` 8x; y(x; y) 2 ( [ ) t $ 9n(n 2 N ^ (x; y) 2 ( [ ) n ) (DEF- ( [ ) t ) 7. ; 7 ` leftcongruence() (ASS) 8. ; 8 ` leftcongruence() (ASS) induction base 9. 9; ` g 0 2 F (HYP) ; ` (f 1 ; f 2 ) 2 ( [ ) 1 (HYP) ; 2 ` (f 1 ; f 2 ) 2 _ (f 1 ; f 2 ) 2 (8D;! D 2 10) ; ` (f 1 ; f 2 ) 2 (HYP) , 9; 1, 7 ` (g 0 f 1 ; g 0 f 2 ) 2 (8D; $ D; ^I;! D ) , 9; 1, 2, , 9; 1, 2, 4, 7 ` (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) (8D; $ D;! D 2 13) ` (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) 1 (8D; $ D;! D 14 4) 16. 9; 1, 2, 4, 7 ` (f 1 ; f 2 ) 2! (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) 1 (DED 15) ; ` (f 1 ; f 2 ) 2 (HYP) , 9; 1, 8 ` (g 0 f 1 ; g 0 f 2 ) 2 (8D; $ D; ^I! D ) , 9; 1, 2, 8 ` (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) (8D; $ D;! D 2 18) 38

40 (DED 35) (DED 43) , 9; 1, 2, ` (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) 1 (8D; $ 4, 8 D;! D 19 4) 21. 9; 1, 2, 4, 8 ` (f 1 ; f 2 ) 2! (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) 1 (DED 20) , 9; 1, 2, ` (g 0 f 1 ; g 0 f 2 ) 2 ( [ ) 1 (_D , 7, 8 21) 23. ; 1, 2, 4, 7, ` 8f 1 ; f 2 ; g(g 2 F ^ (f 1 ; f 2 ) 2 ( [ ) 1! (gf 1 ; gf 2 ) 2 (DED,8I 22) 8 ( [ ) 1 ) induction step ; ` k 2 N (HYP) ; ` 8x 1 ; x 2 ((x 1 ; x 2 ) 2 ( [ ) k! (gx 1 ; gx 2 ) 2 ( [ ) k ) (InductionHYP) , 24; ` (f 1 ; f 2 ) 2 ( [ ) k+1 (HYP) , 24; 5 ` 9z(((f 1 ; z) 2 ( [ ) k ^ (z; f 2 ) 2 ( [ ) 1 ) _ ((z; f 2 ) 2 (8D; $ ( [ ) k ^ (f 1 ; z) 2 ( [ ) 1 )) D;! D 5 26) , 26; 5 ` ((f 1 ; x 0 ) 2 ( [ ) k ^ (x 0 ; f 2 ) 2 ( [ ) 1 ) _ ((x 0 ; f 2 ) 2 (9D 27) ( [ ) k ^ (f 1 ; x 0 ) 2 ( [ ) 1 ) case ; ` (f 1 ; x 0 ) 2 ( [ ) k ^ (x 0 ; f 2 ) 2 ( [ ) 1 (HYP) , 24; ` (f 1 ; x 0 ) 2 ( [ ) k (^D 29) , 24; ` (x 0 ; f 2 ) 2 ( [ ) 1 (^D 29) , 24, 25; ` (gf 1 ; gx 0 ) 2 ( [ ) k (! D 25 30) , 24, 25; ` (gx 0 ; gf 2 ) 2 ( [ ) 1 (! D 25 31) , 24, 25; ` 9z((gf 1 ; z) 2 ( [ ) k ^ (z; gf 2 ) 2 ( [ ) 1 ) (^I; 9I 32 33) , 24, 25; 5 ` (gf 1 ; gf 2 ) 2 ( [ ) k+1 (^I; 8D; $ D;! D ) , 25; 5 ` (f 1 ; x 0 ) 2 ( [ ) k ^ (x 0 ; f 2 ) 2 ( [ ) 1! (gf 1 ; gf 2 ) 2 ( [ ) k+1 case ; ` (x 0 ; f 2 ) 2 ( [ ) k ^ (f 1 ; x 0 ) 2 ( [ ) 1 (HYP) , 24; ` (f 1 ; x 0 ) 2 ( [ ) 1 (^D 37) , 24; ` (x 0 ; f 2 ) 2 ( [ ) k (^D 37) , 24, 25; ` (gf 1 ; gx 0 ) 2 ( [ ) 1 (! D 25 38) , 24, 25; ` (gx 0 ; gf 2 ) 2 ( [ ) k (! D 25 39) , 24, 25; ` 9z((gf 1 ; z) 2 ( [ ) 1 ^ (z; gf 2 ) 2 ( [ ) k ) (^I; 9I 40 41) , 24, 25; 5 ` (gf 1 ; gf 2 ) 2 ( [ ) k+1 (^I; 8D; $ D;! D; _I ) , 25; 5 ` (f 1 ; x 0 ) 2 ( [ ) 1 ^ (x 0 ; f 2 ) 2 ( [ ) k! (gf 1 ; gf 2 ) 2 ( [ ) k , 26, 25; 5 ` (gf 1 ; gf 2 ) 2 ( [ ) k+1 (_D ) 39

Propositional Logic Language

Propositional Logic Language Propositional Logic Language A logic consists of: an alphabet A, a language L, i.e., a set of formulas, and a binary relation = between a set of formulas and a formula. An alphabet A consists of a finite

More information

Foundations of Mathematics MATH 220 FALL 2017 Lecture Notes

Foundations of Mathematics MATH 220 FALL 2017 Lecture Notes Foundations of Mathematics MATH 220 FALL 2017 Lecture Notes These notes form a brief summary of what has been covered during the lectures. All the definitions must be memorized and understood. Statements

More information

( V ametavariable) P P true. even in E)

( V ametavariable) P P true. even in E) Propositional Calculus E Inference rules (3.1) Leibniz: (3.2) Transitivity: (3.3) Equanimity: P = Q E[V := P ]=E[V := Q] P = Q Q = R P = R P P Q Q ( V ametavariable) Derived inference rules (3.11) Redundant

More information

Chapter 3. Formal Number Theory

Chapter 3. Formal Number Theory Chapter 3. Formal Number Theory 1. An Axiom System for Peano Arithmetic (S) The language L A of Peano arithmetic has a constant 0, a unary function symbol, a binary function symbol +, binary function symbol,

More information

Behavioural theories and the proof of. LIENS, C.N.R.S. U.R.A & Ecole Normale Superieure, 45 Rue d'ulm, F{75230 Paris Cedex 05, France

Behavioural theories and the proof of. LIENS, C.N.R.S. U.R.A & Ecole Normale Superieure, 45 Rue d'ulm, F{75230 Paris Cedex 05, France Behavioural theories and the proof of behavioural properties Michel Bidoit a and Rolf Hennicker b b a LIENS, C.N.R.S. U.R.A. 1327 & Ecole Normale Superieure, 45 Rue d'ulm, F{75230 Paris Cedex 05, France

More information

L bor y nnd Union One nnd Inseparable. LOW I'LL, MICHIGAN. WLDNHSDA Y. JULY ), I8T. liuwkll NATIdiNAI, liank

L bor y nnd Union One nnd Inseparable. LOW I'LL, MICHIGAN. WLDNHSDA Y. JULY ), I8T. liuwkll NATIdiNAI, liank G k y $5 y / >/ k «««# ) /% < # «/» Y»««««?# «< >«>» y k»» «k F 5 8 Y Y F G k F >«y y

More information

higher-order logic (e:g:, Church's simple theory of types [5]) P must be a simple type. Although CC types include the types of the simply-typed -calcu

higher-order logic (e:g:, Church's simple theory of types [5]) P must be a simple type. Although CC types include the types of the simply-typed -calcu The Calculus of Constructions as a Framework for Proof Search with Set Variable Instantiation Amy Felty Bell Laboratories Lucent Technologies, 700 Mountain Ave., Murray Hill, NJ 07974, USA felty@bell-labs.com

More information

Every formula evaluates to either \true" or \false." To say that the value of (x = y) is true is to say that the value of the term x is the same as th

Every formula evaluates to either \true or \false. To say that the value of (x = y) is true is to say that the value of the term x is the same as th A Quick and Dirty Sketch of a Toy Logic J Strother Moore January 9, 2001 Abstract For the purposes of this paper, a \logic" consists of a syntax, a set of axioms and some rules of inference. We dene a

More information

Introduction to Metalogic

Introduction to Metalogic Philosophy 135 Spring 2008 Tony Martin Introduction to Metalogic 1 The semantics of sentential logic. The language L of sentential logic. Symbols of L: Remarks: (i) sentence letters p 0, p 1, p 2,... (ii)

More information

A note on fuzzy predicate logic. Petr H jek 1. Academy of Sciences of the Czech Republic

A note on fuzzy predicate logic. Petr H jek 1. Academy of Sciences of the Czech Republic A note on fuzzy predicate logic Petr H jek 1 Institute of Computer Science, Academy of Sciences of the Czech Republic Pod vod renskou v 2, 182 07 Prague. Abstract. Recent development of mathematical fuzzy

More information

A MODEL-THEORETIC PROOF OF HILBERT S NULLSTELLENSATZ

A MODEL-THEORETIC PROOF OF HILBERT S NULLSTELLENSATZ A MODEL-THEORETIC PROOF OF HILBERT S NULLSTELLENSATZ NICOLAS FORD Abstract. The goal of this paper is to present a proof of the Nullstellensatz using tools from a branch of logic called model theory. In

More information

Solvability of Word Equations Modulo Finite Special And. Conuent String-Rewriting Systems Is Undecidable In General.

Solvability of Word Equations Modulo Finite Special And. Conuent String-Rewriting Systems Is Undecidable In General. Solvability of Word Equations Modulo Finite Special And Conuent String-Rewriting Systems Is Undecidable In General Friedrich Otto Fachbereich Mathematik/Informatik, Universitat GH Kassel 34109 Kassel,

More information

Syntax. Notation Throughout, and when not otherwise said, we assume a vocabulary V = C F P.

Syntax. Notation Throughout, and when not otherwise said, we assume a vocabulary V = C F P. First-Order Logic Syntax The alphabet of a first-order language is organised into the following categories. Logical connectives:,,,,, and. Auxiliary symbols:.,,, ( and ). Variables: we assume a countable

More information

Axioms for Set Theory

Axioms for Set Theory Axioms for Set Theory The following is a subset of the Zermelo-Fraenkel axioms for set theory. In this setting, all objects are sets which are denoted by letters, e.g. x, y, X, Y. Equality is logical identity:

More information

KRIPKE S THEORY OF TRUTH 1. INTRODUCTION

KRIPKE S THEORY OF TRUTH 1. INTRODUCTION KRIPKE S THEORY OF TRUTH RICHARD G HECK, JR 1. INTRODUCTION The purpose of this note is to give a simple, easily accessible proof of the existence of the minimal fixed point, and of various maximal fixed

More information

2 Lecture 2: Logical statements and proof by contradiction Lecture 10: More on Permutations, Group Homomorphisms 31

2 Lecture 2: Logical statements and proof by contradiction Lecture 10: More on Permutations, Group Homomorphisms 31 Contents 1 Lecture 1: Introduction 2 2 Lecture 2: Logical statements and proof by contradiction 7 3 Lecture 3: Induction and Well-Ordering Principle 11 4 Lecture 4: Definition of a Group and examples 15

More information

hal , version 1-21 Oct 2009

hal , version 1-21 Oct 2009 ON SKOLEMISING ZERMELO S SET THEORY ALEXANDRE MIQUEL Abstract. We give a Skolemised presentation of Zermelo s set theory (with notations for comprehension, powerset, etc.) and show that this presentation

More information

INDEPENDENCE OF THE CONTINUUM HYPOTHESIS

INDEPENDENCE OF THE CONTINUUM HYPOTHESIS INDEPENDENCE OF THE CONTINUUM HYPOTHESIS CAPSTONE MATT LUTHER 1 INDEPENDENCE OF THE CONTINUUM HYPOTHESIS 2 1. Introduction This paper will summarize many of the ideas from logic and set theory that are

More information

Kirsten Lackner Solberg. Dept. of Math. and Computer Science. Odense University, Denmark

Kirsten Lackner Solberg. Dept. of Math. and Computer Science. Odense University, Denmark Inference Systems for Binding Time Analysis Kirsten Lackner Solberg Dept. of Math. and Computer Science Odense University, Denmark e-mail: kls@imada.ou.dk June 21, 1993 Contents 1 Introduction 4 2 Review

More information

Equational Logic. Chapter Syntax Terms and Term Algebras

Equational Logic. Chapter Syntax Terms and Term Algebras Chapter 2 Equational Logic 2.1 Syntax 2.1.1 Terms and Term Algebras The natural logic of algebra is equational logic, whose propositions are universally quantified identities between terms built up from

More information

Peano Arithmetic. CSC 438F/2404F Notes (S. Cook) Fall, Goals Now

Peano Arithmetic. CSC 438F/2404F Notes (S. Cook) Fall, Goals Now CSC 438F/2404F Notes (S. Cook) Fall, 2008 Peano Arithmetic Goals Now 1) We will introduce a standard set of axioms for the language L A. The theory generated by these axioms is denoted PA and called Peano

More information

This is logically equivalent to the conjunction of the positive assertion Minimal Arithmetic and Representability

This is logically equivalent to the conjunction of the positive assertion Minimal Arithmetic and Representability 16.2. MINIMAL ARITHMETIC AND REPRESENTABILITY 207 If T is a consistent theory in the language of arithmetic, we say a set S is defined in T by D(x) if for all n, if n is in S, then D(n) is a theorem of

More information

The semantics of propositional logic

The semantics of propositional logic The semantics of propositional logic Readings: Sections 1.3 and 1.4 of Huth and Ryan. In this module, we will nail down the formal definition of a logical formula, and describe the semantics of propositional

More information

Math 42, Discrete Mathematics

Math 42, Discrete Mathematics c Fall 2018 last updated 10/10/2018 at 23:28:03 For use by students in this class only; all rights reserved. Note: some prose & some tables are taken directly from Kenneth R. Rosen, and Its Applications,

More information

3.1 Basic properties of real numbers - continuation Inmum and supremum of a set of real numbers

3.1 Basic properties of real numbers - continuation Inmum and supremum of a set of real numbers Chapter 3 Real numbers The notion of real number was introduced in section 1.3 where the axiomatic denition of the set of all real numbers was done and some basic properties of the set of all real numbers

More information

Linear Algebra (part 1) : Vector Spaces (by Evan Dummit, 2017, v. 1.07) 1.1 The Formal Denition of a Vector Space

Linear Algebra (part 1) : Vector Spaces (by Evan Dummit, 2017, v. 1.07) 1.1 The Formal Denition of a Vector Space Linear Algebra (part 1) : Vector Spaces (by Evan Dummit, 2017, v. 1.07) Contents 1 Vector Spaces 1 1.1 The Formal Denition of a Vector Space.................................. 1 1.2 Subspaces...................................................

More information

INCOMPLETENESS IN ZFC

INCOMPLETENESS IN ZFC INCOMPLETENESS IN ZFC VICTOR ZHANG Abstract. The statements of Gödel's incompleteness theorems are famous in mathematics, concerning the foundations of the eld. Whilst most mathematicians have heard of

More information

Predicates and Predicate Transformers for. Systems 1. Ratnesh Kumar. Department of Electrical Engineering. University of Kentucky

Predicates and Predicate Transformers for. Systems 1. Ratnesh Kumar. Department of Electrical Engineering. University of Kentucky Predicates and Predicate Transformers for Supervisory Control of Discrete Event Dynamical Systems 1 Ratnesh Kumar Department of Electrical Engineering University of Kentucy Lexington, KY 40506-0046 Vijay

More information

NP-Hard to Linearly Approximate. University of California, San Diego. Computer Science Department. August 3, Abstract

NP-Hard to Linearly Approximate. University of California, San Diego. Computer Science Department. August 3, Abstract Minimum Propositional Proof Length is NP-Hard to Linearly Approximate Michael Alekhnovich Faculty of Mechanics & Mathematics Moscow State University, Russia michael@mail.dnttm.ru Shlomo Moran y Department

More information

2 PLTL Let P be a set of propositional variables. The set of formulae of propositional linear time logic PLTL (over P) is inductively dened as follows

2 PLTL Let P be a set of propositional variables. The set of formulae of propositional linear time logic PLTL (over P) is inductively dened as follows Translating PLTL into WSS: Application Description B. Hirsch and U. Hustadt Department of Computer Science, University of Liverpool Liverpool L69 7ZF, United Kingdom, fb.hirsch,u.hustadtg@csc.liv.ac.uk

More information

Chapter 2 Axiomatic Set Theory

Chapter 2 Axiomatic Set Theory Chapter 2 Axiomatic Set Theory Ernst Zermelo (1871 1953) was the first to find an axiomatization of set theory, and it was later expanded by Abraham Fraenkel (1891 1965). 2.1 Zermelo Fraenkel Set Theory

More information

Math 4603: Advanced Calculus I, Summer 2016 University of Minnesota Notes on Cardinality of Sets

Math 4603: Advanced Calculus I, Summer 2016 University of Minnesota Notes on Cardinality of Sets Math 4603: Advanced Calculus I, Summer 2016 University of Minnesota Notes on Cardinality of Sets Introduction In this short article, we will describe some basic notions on cardinality of sets. Given two

More information

Syntactic Characterisations in Model Theory

Syntactic Characterisations in Model Theory Department of Mathematics Bachelor Thesis (7.5 ECTS) Syntactic Characterisations in Model Theory Author: Dionijs van Tuijl Supervisor: Dr. Jaap van Oosten June 15, 2016 Contents 1 Introduction 2 2 Preliminaries

More information

CHAPTER 0: BACKGROUND (SPRING 2009 DRAFT)

CHAPTER 0: BACKGROUND (SPRING 2009 DRAFT) CHAPTER 0: BACKGROUND (SPRING 2009 DRAFT) MATH 378, CSUSM. SPRING 2009. AITKEN This chapter reviews some of the background concepts needed for Math 378. This chapter is new to the course (added Spring

More information

ADDENDUM B: CONSTRUCTION OF R AND THE COMPLETION OF A METRIC SPACE

ADDENDUM B: CONSTRUCTION OF R AND THE COMPLETION OF A METRIC SPACE ADDENDUM B: CONSTRUCTION OF R AND THE COMPLETION OF A METRIC SPACE ANDREAS LEOPOLD KNUTSEN Abstract. These notes are written as supplementary notes for the course MAT11- Real Analysis, taught at the University

More information

MATH 433 Applied Algebra Lecture 22: Semigroups. Rings.

MATH 433 Applied Algebra Lecture 22: Semigroups. Rings. MATH 433 Applied Algebra Lecture 22: Semigroups. Rings. Groups Definition. A group is a set G, together with a binary operation, that satisfies the following axioms: (G1: closure) for all elements g and

More information

3 Propositional Logic

3 Propositional Logic 3 Propositional Logic 3.1 Syntax 3.2 Semantics 3.3 Equivalence and Normal Forms 3.4 Proof Procedures 3.5 Properties Propositional Logic (25th October 2007) 1 3.1 Syntax Definition 3.0 An alphabet Σ consists

More information

apply (Subst) expands accordingly. This does not mean that the notions to which one may apply induction throughout mathematics are limited to those ap

apply (Subst) expands accordingly. This does not mean that the notions to which one may apply induction throughout mathematics are limited to those ap The unfolding of non-nitist arithmetic Solomon Feferman Thomas Strahm Abstract The unfolding of schematic formal systems is a novel concept which was initiated in Feferman [6]. This paper is mainly concerned

More information

A version of for which ZFC can not predict a single bit Robert M. Solovay May 16, Introduction In [2], Chaitin introd

A version of for which ZFC can not predict a single bit Robert M. Solovay May 16, Introduction In [2], Chaitin introd CDMTCS Research Report Series A Version of for which ZFC can not Predict a Single Bit Robert M. Solovay University of California at Berkeley CDMTCS-104 May 1999 Centre for Discrete Mathematics and Theoretical

More information

3. Categories and Functors We recall the definition of a category: Definition 3.1. A category C is the data of two collections. The first collection

3. Categories and Functors We recall the definition of a category: Definition 3.1. A category C is the data of two collections. The first collection 3. Categories and Functors We recall the definition of a category: Definition 3.1. A category C is the data of two collections. The first collection is called the objects of C and is denoted Obj(C). Given

More information

One Quantier Will Do in Existential Monadic. Second-Order Logic over Pictures. Oliver Matz. Institut fur Informatik und Praktische Mathematik

One Quantier Will Do in Existential Monadic. Second-Order Logic over Pictures. Oliver Matz. Institut fur Informatik und Praktische Mathematik One Quantier Will Do in Existential Monadic Second-Order Logic over Pictures Oliver Matz Institut fur Informatik und Praktische Mathematik Christian-Albrechts-Universitat Kiel, 24098 Kiel, Germany e-mail:

More information

Provably Total Functions of Arithmetic with Basic Terms

Provably Total Functions of Arithmetic with Basic Terms Provably Total Functions of Arithmetic with Basic Terms Evgeny Makarov INRIA Orsay, France emakarov@gmail.com A new characterization of provably recursive functions of first-order arithmetic is described.

More information

Zermelo's Well-Ordering Theorem in Type Theory

Zermelo's Well-Ordering Theorem in Type Theory Zermelo's Well-Ordering Theorem in Type Theory Danko Ilik DCS Master Programme, Chalmers University of Technology Abstract. Taking a `set' to be a type together with an equivalence relation and adding

More information

Clausal Presentation of Theories in Deduction Modulo

Clausal Presentation of Theories in Deduction Modulo Gao JH. Clausal presentation of theories in deduction modulo. JOURNAL OF COMPUTER SCIENCE AND TECHNOL- OGY 28(6): 1085 1096 Nov. 2013. DOI 10.1007/s11390-013-1399-0 Clausal Presentation of Theories in

More information

in Linear Logic Denis Bechet LIPN - Institut Galilee Universite Paris 13 Avenue Jean-Baptiste Clement Villetaneuse, France Abstract

in Linear Logic Denis Bechet LIPN - Institut Galilee Universite Paris 13 Avenue Jean-Baptiste Clement Villetaneuse, France Abstract Second Order Connectives and roof Transformations in Linear Logic Denis Bechet LIN - Institut Galilee Universite aris 1 Avenue Jean-Baptiste Clement 90 Villetaneuse, France e-mail: dbe@lipnuniv-paris1fr

More information

A Preference Semantics. for Ground Nonmonotonic Modal Logics. logics, a family of nonmonotonic modal logics obtained by means of a

A Preference Semantics. for Ground Nonmonotonic Modal Logics. logics, a family of nonmonotonic modal logics obtained by means of a A Preference Semantics for Ground Nonmonotonic Modal Logics Daniele Nardi and Riccardo Rosati Dipartimento di Informatica e Sistemistica, Universita di Roma \La Sapienza", Via Salaria 113, I-00198 Roma,

More information

CHAPTER 2. FIRST ORDER LOGIC

CHAPTER 2. FIRST ORDER LOGIC CHAPTER 2. FIRST ORDER LOGIC 1. Introduction First order logic is a much richer system than sentential logic. Its interpretations include the usual structures of mathematics, and its sentences enable us

More information

Spurious Chaotic Solutions of Dierential. Equations. Sigitas Keras. September Department of Applied Mathematics and Theoretical Physics

Spurious Chaotic Solutions of Dierential. Equations. Sigitas Keras. September Department of Applied Mathematics and Theoretical Physics UNIVERSITY OF CAMBRIDGE Numerical Analysis Reports Spurious Chaotic Solutions of Dierential Equations Sigitas Keras DAMTP 994/NA6 September 994 Department of Applied Mathematics and Theoretical Physics

More information

Informal Statement Calculus

Informal Statement Calculus FOUNDATIONS OF MATHEMATICS Branches of Logic 1. Theory of Computations (i.e. Recursion Theory). 2. Proof Theory. 3. Model Theory. 4. Set Theory. Informal Statement Calculus STATEMENTS AND CONNECTIVES Example

More information

Propositional Logic: Syntax

Propositional Logic: Syntax 4 Propositional Logic: Syntax Reading: Metalogic Part II, 22-26 Contents 4.1 The System PS: Syntax....................... 49 4.1.1 Axioms and Rules of Inference................ 49 4.1.2 Definitions.................................

More information

Splitting a Default Theory. Hudson Turner. University of Texas at Austin.

Splitting a Default Theory. Hudson Turner. University of Texas at Austin. Splitting a Default Theory Hudson Turner Department of Computer Sciences University of Texas at Austin Austin, TX 7872-88, USA hudson@cs.utexas.edu Abstract This paper presents mathematical results that

More information

MATH 1090 Problem Set #3 Solutions March York University

MATH 1090 Problem Set #3 Solutions March York University York University Faculties of Science and Engineering, Arts, Atkinson MATH 1090. Problem Set #3 Solutions Section M 1. Use Resolution (possibly in combination with the Deduction Theorem, Implication as

More information

What are the recursion theoretic properties of a set of axioms? Understanding a paper by William Craig Armando B. Matos

What are the recursion theoretic properties of a set of axioms? Understanding a paper by William Craig Armando B. Matos What are the recursion theoretic properties of a set of axioms? Understanding a paper by William Craig Armando B. Matos armandobcm@yahoo.com February 5, 2014 Abstract This note is for personal use. It

More information

0 Sets and Induction. Sets

0 Sets and Induction. Sets 0 Sets and Induction Sets A set is an unordered collection of objects, called elements or members of the set. A set is said to contain its elements. We write a A to denote that a is an element of the set

More information

3. Only sequences that were formed by using finitely many applications of rules 1 and 2, are propositional formulas.

3. Only sequences that were formed by using finitely many applications of rules 1 and 2, are propositional formulas. 1 Chapter 1 Propositional Logic Mathematical logic studies correct thinking, correct deductions of statements from other statements. Let us make it more precise. A fundamental property of a statement is

More information

MAX-PLANCK-INSTITUT F UR INFORMATIK Killer Transformations Hans Jurgen Ohlbach Dov Gabbay David Plaisted MPI{I{94{226 June 94 k I N F O R M A T I K Im Stadtwald D 66123 Saarbrucken Germany Author's Address

More information

Introduction to Restriction Categories

Introduction to Restriction Categories Introduction to Restriction Categories Robin Cockett Department of Computer Science University of Calgary Alberta, Canada robin@cpsc.ucalgary.ca Estonia, March 2010 Defining restriction categories Examples

More information

A BRIEF INTRODUCTION TO ZFC. Contents. 1. Motivation and Russel s Paradox

A BRIEF INTRODUCTION TO ZFC. Contents. 1. Motivation and Russel s Paradox A BRIEF INTRODUCTION TO ZFC CHRISTOPHER WILSON Abstract. We present a basic axiomatic development of Zermelo-Fraenkel and Choice set theory, commonly abbreviated ZFC. This paper is aimed in particular

More information

Vector Space Basics. 1 Abstract Vector Spaces. 1. (commutativity of vector addition) u + v = v + u. 2. (associativity of vector addition)

Vector Space Basics. 1 Abstract Vector Spaces. 1. (commutativity of vector addition) u + v = v + u. 2. (associativity of vector addition) Vector Space Basics (Remark: these notes are highly formal and may be a useful reference to some students however I am also posting Ray Heitmann's notes to Canvas for students interested in a direct computational

More information

Fuzzy and Non-deterministic Automata Ji Mo ko January 29, 1998 Abstract An existence of an isomorphism between a category of fuzzy automata and a cate

Fuzzy and Non-deterministic Automata Ji Mo ko January 29, 1998 Abstract An existence of an isomorphism between a category of fuzzy automata and a cate University of Ostrava Institute for Research and Applications of Fuzzy Modeling Fuzzy and Non-deterministic Automata Ji Mo ko Research report No. 8 November 6, 1997 Submitted/to appear: { Supported by:

More information

Přednáška 12. Důkazové kalkuly Kalkul Hilbertova typu. 11/29/2006 Hilbertův kalkul 1

Přednáška 12. Důkazové kalkuly Kalkul Hilbertova typu. 11/29/2006 Hilbertův kalkul 1 Přednáška 12 Důkazové kalkuly Kalkul Hilbertova typu 11/29/2006 Hilbertův kalkul 1 Formal systems, Proof calculi A proof calculus (of a theory) is given by: A. a language B. a set of axioms C. a set of

More information

Resolution for Predicate Logic

Resolution for Predicate Logic Logic and Proof Hilary 2016 James Worrell Resolution for Predicate Logic A serious drawback of the ground resolution procedure is that it requires looking ahead to predict which ground instances of clauses

More information

Krivine s Intuitionistic Proof of Classical Completeness (for countable languages)

Krivine s Intuitionistic Proof of Classical Completeness (for countable languages) Krivine s Intuitionistic Proof of Classical Completeness (for countable languages) Berardi Stefano Valentini Silvio Dip. Informatica Dip. Mat. Pura ed Applicata Univ. Torino Univ. Padova c.so Svizzera

More information

Notation for Logical Operators:

Notation for Logical Operators: Notation for Logical Operators: always true always false... and...... or... if... then...... if-and-only-if... x:x p(x) x:x p(x) for all x of type X, p(x) there exists an x of type X, s.t. p(x) = is equal

More information

Math 300 Introduction to Mathematical Reasoning Autumn 2017 Inverse Functions

Math 300 Introduction to Mathematical Reasoning Autumn 2017 Inverse Functions Math 300 Introduction to Mathematical Reasoning Autumn 2017 Inverse Functions Please read this pdf in place of Section 6.5 in the text. The text uses the term inverse of a function and the notation f 1

More information

Herbrand Theorem, Equality, and Compactness

Herbrand Theorem, Equality, and Compactness CSC 438F/2404F Notes (S. Cook and T. Pitassi) Fall, 2014 Herbrand Theorem, Equality, and Compactness The Herbrand Theorem We now consider a complete method for proving the unsatisfiability of sets of first-order

More information

First-Order Predicate Logic. Basics

First-Order Predicate Logic. Basics First-Order Predicate Logic Basics 1 Syntax of predicate logic: terms A variable is a symbol of the form x i where i = 1, 2, 3.... A function symbol is of the form fi k where i = 1, 2, 3... und k = 0,

More information

A Tableau Calculus for Minimal Modal Model Generation

A Tableau Calculus for Minimal Modal Model Generation M4M 2011 A Tableau Calculus for Minimal Modal Model Generation Fabio Papacchini 1 and Renate A. Schmidt 2 School of Computer Science, University of Manchester Abstract Model generation and minimal model

More information

Chapter 3. Rings. The basic commutative rings in mathematics are the integers Z, the. Examples

Chapter 3. Rings. The basic commutative rings in mathematics are the integers Z, the. Examples Chapter 3 Rings Rings are additive abelian groups with a second operation called multiplication. The connection between the two operations is provided by the distributive law. Assuming the results of Chapter

More information

Automated Reasoning Lecture 5: First-Order Logic

Automated Reasoning Lecture 5: First-Order Logic Automated Reasoning Lecture 5: First-Order Logic Jacques Fleuriot jdf@inf.ac.uk Recap Over the last three lectures, we have looked at: Propositional logic, semantics and proof systems Doing propositional

More information

Normal forms in combinatorial algebra

Normal forms in combinatorial algebra Alberto Gioia Normal forms in combinatorial algebra Master s thesis, defended on July 8, 2009 Thesis advisor: Hendrik Lenstra Mathematisch Instituut Universiteit Leiden ii Contents Introduction iv 1 Generators

More information

LEBESGUE INTEGRATION. Introduction

LEBESGUE INTEGRATION. Introduction LEBESGUE INTEGATION EYE SJAMAA Supplementary notes Math 414, Spring 25 Introduction The following heuristic argument is at the basis of the denition of the Lebesgue integral. This argument will be imprecise,

More information

INFORMATIK SAARBR UCKEN AT DES SAARLANDE UNIVERSIT GERMANY D WWW: FACHBEREICH

INFORMATIK SAARBR UCKEN AT DES SAARLANDE UNIVERSIT GERMANY D WWW:   FACHBEREICH WWW: http://js-sfbsun.cs.uni-sb.de/pub/www/ AT DES SAARLANDE UNIVERSIT INFORMATIK FACHBEREICH SAARBR UCKEN D-66041 GERMANY PROVERB{ A System Explaining Machine-Found Proofs Xiaorong Huang Fachbereich Informatik,

More information

Denotational Semantics

Denotational Semantics 5 Denotational Semantics In the operational approach, we were interested in how a program is executed. This is contrary to the denotational approach, where we are merely interested in the effect of executing

More information

Notes on ordinals and cardinals

Notes on ordinals and cardinals Notes on ordinals and cardinals Reed Solomon 1 Background Terminology We will use the following notation for the common number systems: N = {0, 1, 2,...} = the natural numbers Z = {..., 2, 1, 0, 1, 2,...}

More information

2 ALGEBRA II. Contents

2 ALGEBRA II. Contents ALGEBRA II 1 2 ALGEBRA II Contents 1. Results from elementary number theory 3 2. Groups 4 2.1. Denition, Subgroup, Order of an element 4 2.2. Equivalence relation, Lagrange's theorem, Cyclic group 9 2.3.

More information

Computability and Complexity

Computability and Complexity Computability and Complexity Non-determinism, Regular Expressions CAS 705 Ryszard Janicki Department of Computing and Software McMaster University Hamilton, Ontario, Canada janicki@mcmaster.ca Ryszard

More information

Axioms of Kleene Algebra

Axioms of Kleene Algebra Introduction to Kleene Algebra Lecture 2 CS786 Spring 2004 January 28, 2004 Axioms of Kleene Algebra In this lecture we give the formal definition of a Kleene algebra and derive some basic consequences.

More information

Analysis 1. Lecture Notes 2013/2014. The original version of these Notes was written by. Vitali Liskevich

Analysis 1. Lecture Notes 2013/2014. The original version of these Notes was written by. Vitali Liskevich Analysis 1 Lecture Notes 2013/2014 The original version of these Notes was written by Vitali Liskevich followed by minor adjustments by many Successors, and presently taught by Misha Rudnev University

More information

Mathematics 114L Spring 2018 D.A. Martin. Mathematical Logic

Mathematics 114L Spring 2018 D.A. Martin. Mathematical Logic Mathematics 114L Spring 2018 D.A. Martin Mathematical Logic 1 First-Order Languages. Symbols. All first-order languages we consider will have the following symbols: (i) variables v 1, v 2, v 3,... ; (ii)

More information

A Graph Based Parsing Algorithm for Context-free Languages

A Graph Based Parsing Algorithm for Context-free Languages A Graph Based Parsing Algorithm for Context-free Languages Giinter Hot> Technical Report A 01/99 June 1999 e-mail: hotzocs.uni-sb.de VVVVVV: http://vwv-hotz.cs.uni-sb. de Abstract We present a simple algorithm

More information

Lecture Notes on Combinatory Modal Logic

Lecture Notes on Combinatory Modal Logic Lecture Notes on Combinatory Modal Logic 15-816: Modal Logic Frank Pfenning Lecture 9 February 16, 2010 1 Introduction The connection between proofs and program so far has been through a proof term assignment

More information

Functional Database Query Languages as. Typed Lambda Calculi of Fixed Order. Gerd G. Hillebrand and Paris C. Kanellakis

Functional Database Query Languages as. Typed Lambda Calculi of Fixed Order. Gerd G. Hillebrand and Paris C. Kanellakis Functional Database Query Languages as Typed Lambda Calculi of Fixed Order Gerd G. Hillebrand and Paris C. Kanellakis Department of Computer Science Brown University Providence, Rhode Island 02912 CS-94-26

More information

Exhaustive Classication of Finite Classical Probability Spaces with Regard to the Notion of Causal Up-to-n-closedness

Exhaustive Classication of Finite Classical Probability Spaces with Regard to the Notion of Causal Up-to-n-closedness Exhaustive Classication of Finite Classical Probability Spaces with Regard to the Notion of Causal Up-to-n-closedness Michaª Marczyk, Leszek Wro«ski Jagiellonian University, Kraków 16 June 2009 Abstract

More information

A Finitely Axiomatized Formalization of Predicate Calculus with Equality

A Finitely Axiomatized Formalization of Predicate Calculus with Equality A Finitely Axiomatized Formalization of Predicate Calculus with Equality Note: This is a preprint of Megill, A Finitely Axiomatized Formalization of Predicate Calculus with Equality, Notre Dame Journal

More information

for Propositional Temporal Logic with Since and Until Y. S. Ramakrishna, L. E. Moser, L. K. Dillon, P. M. Melliar-Smith, G. Kutty

for Propositional Temporal Logic with Since and Until Y. S. Ramakrishna, L. E. Moser, L. K. Dillon, P. M. Melliar-Smith, G. Kutty An Automata-Theoretic Decision Procedure for Propositional Temporal Logic with Since and Until Y. S. Ramakrishna, L. E. Moser, L. K. Dillon, P. M. Melliar-Smith, G. Kutty Department of Electrical and Computer

More information

Mathematics Course 111: Algebra I Part I: Algebraic Structures, Sets and Permutations

Mathematics Course 111: Algebra I Part I: Algebraic Structures, Sets and Permutations Mathematics Course 111: Algebra I Part I: Algebraic Structures, Sets and Permutations D. R. Wilkins Academic Year 1996-7 1 Number Systems and Matrix Algebra Integers The whole numbers 0, ±1, ±2, ±3, ±4,...

More information

Introduction to Logic in Computer Science: Autumn 2007

Introduction to Logic in Computer Science: Autumn 2007 Introduction to Logic in Computer Science: Autumn 2007 Ulle Endriss Institute for Logic, Language and Computation University of Amsterdam Ulle Endriss 1 Tableaux for First-order Logic The next part of

More information

Syntax of FOL. Introduction to Logic in Computer Science: Autumn Tableaux for First-order Logic. Syntax of FOL (2)

Syntax of FOL. Introduction to Logic in Computer Science: Autumn Tableaux for First-order Logic. Syntax of FOL (2) Syntax of FOL Introduction to Logic in Computer Science: Autumn 2007 Ulle Endriss Institute for Logic, Language and Computation University of Amsterdam The syntax of a language defines the way in which

More information

Some Applications of MATH 1090 Techniques

Some Applications of MATH 1090 Techniques 1 Some Applications of MATH 1090 Techniques 0.1 A simple problem about Nand gates in relation to And gates and inversion (Not) Gates. In this subsection the notation A means that A is proved from the axioms

More information

Chapter 1. Logic and Proof

Chapter 1. Logic and Proof Chapter 1. Logic and Proof 1.1 Remark: A little over 100 years ago, it was found that some mathematical proofs contained paradoxes, and these paradoxes could be used to prove statements that were known

More information

Lecture 10: Predicate Logic and Its Language

Lecture 10: Predicate Logic and Its Language Discrete Mathematics (II) Spring 2017 Lecture 10: Predicate Logic and Its Language Lecturer: Yi Li 1 Predicates and Quantifiers In this action, we show you why a richer language should be introduced than

More information

Basic Proof Examples

Basic Proof Examples Basic Proof Examples Lisa Oberbroeckling Loyola University Maryland Fall 2015 Note. In this document, we use the symbol as the negation symbol. Thus p means not p. There are four basic proof techniques

More information

Tableau Calculus for Local Cubic Modal Logic and it's Implementation MAARTEN MARX, Department of Articial Intelligence, Faculty of Sciences, Vrije Uni

Tableau Calculus for Local Cubic Modal Logic and it's Implementation MAARTEN MARX, Department of Articial Intelligence, Faculty of Sciences, Vrije Uni Tableau Calculus for Local Cubic Modal Logic and it's Implementation MAARTEN MARX, Department of Articial Intelligence, Faculty of Sciences, Vrije Universiteit Amsterdam, De Boelelaan 1081a, 1081 HV Amsterdam,

More information

Principles of Real Analysis I Fall I. The Real Number System

Principles of Real Analysis I Fall I. The Real Number System 21-355 Principles of Real Analysis I Fall 2004 I. The Real Number System The main goal of this course is to develop the theory of real-valued functions of one real variable in a systematic and rigorous

More information

Math 203A - Solution Set 3

Math 203A - Solution Set 3 Math 03A - Solution Set 3 Problem 1 Which of the following algebraic sets are isomorphic: (i) A 1 (ii) Z(xy) A (iii) Z(x + y ) A (iv) Z(x y 5 ) A (v) Z(y x, z x 3 ) A Answer: We claim that (i) and (v)

More information

A Proof Presentation Suitable for Teaching Proofs. Dept. of Science Education. Haifa, Israel 32000

A Proof Presentation Suitable for Teaching Proofs. Dept. of Science Education. Haifa, Israel 32000 A Proof Presentation Suitable for Teaching Proofs Erica Melis Universitat des Saarlandes, Fachbereich Informatik 66041 Saarbrucken melis@cs.uni-sb.de Uri Leron Dept. of Science Education Technion Inst.

More information

Simple Lie subalgebras of locally nite associative algebras

Simple Lie subalgebras of locally nite associative algebras Simple Lie subalgebras of locally nite associative algebras Y.A. Bahturin Department of Mathematics and Statistics Memorial University of Newfoundland St. John's, NL, A1C5S7, Canada A.A. Baranov Department

More information

Lecture Notes on Sequent Calculus

Lecture Notes on Sequent Calculus Lecture Notes on Sequent Calculus 15-816: Modal Logic Frank Pfenning Lecture 8 February 9, 2010 1 Introduction In this lecture we present the sequent calculus and its theory. The sequent calculus was originally

More information

Math 4606, Summer 2004: Inductive sets, N, the Peano Axioms, Recursive Sequences Page 1 of 10

Math 4606, Summer 2004: Inductive sets, N, the Peano Axioms, Recursive Sequences Page 1 of 10 Math 4606, Summer 2004: Inductive sets, N, the Peano Axioms, Recursive Sequences Page 1 of 10 Inductive sets (used to define the natural numbers as a subset of R) (1) Definition: A set S R is an inductive

More information