Completeness of an Euler Diagrammatic System with Constant and Existential Points

Size: px
Start display at page:

Download "Completeness of an Euler Diagrammatic System with Constant and Existential Points"

Transcription

1 omleteness of n uler igrmmtic System with onstnt nd xistentil Points Ryo Tkemur Nihon University, Jn. tkemur.ryo@nihon-u.c.j strct We extend uler digrmmtic system of Minshim, Okd, & Tkemur (2012) y distinguishing constnt nd existentil oints. onstnts oints corresond to constnt symols, nd existentil oints corresond to ound vriles ssocited with the existentil quntifier of the first-order lnguge in symolic logic. We rove the comleteness theorem of our extended uler digrmmtic system. 1 Introduction Since the 1990s, resoning with uler nd Venn digrms hs een studied from mthemticl nd logicl viewoint. uler nd Venn digrms re rigorously defined s syntctic ojects, like formuls in symolic logic, nd inference systems re formlized, which re equivlent to some symolic logicl systems. Then, fundmentl logicl roerties such s soundness nd comleteness re investigted..g., [Shin, 1994, Howse et l., 2005, Mineshim et l., 2012]. See [Stleton, 2005] for survey. Mineshim, Okd, & Tkemur (2012) introduced sic uler digrmmtic system, clled GS, in which digrm consists of nmed circles nd oints. Then, the soundness nd comleteness theorems of the system re estlished. Furthermore, it is shown tht the trditionl ristotelin ctegoricl syllogisms re esily simulted in the system. In the simultion, n existentil sentence such s Some re is trnslted into n uler digrm through sentence c is nd c is for some constnt c. lthough this trnsltion works well for the simultion of the syllogisms, if we consider the negtion of whole digrm eyond the syllogisms, the ove trnsltion my cuse some rolem: while No re is the negtion of Some re, it is no longer the negtion of c is nd c is. In this er, we extend the uler digrmmtic system of [Mineshim et l., 2012] y introducing existentil oints, which corresond to ound vriles ssocited with the existentil quntifier of the first-order lnguge in symolic logic. The introduction of existentil oints, distinguished from constnt oints, mkes our uler digrmmtic system more exressive, nd enles us to trnslte syllogistic sentences more nturlly. In Section 2, we introduce the syntx, semntics, nd inference rules of our uler digrmmtic system. Then, in Section 3, y extending the roof given in [Mineshim et l., 2012], we rove the comleteness theorem of our system. 1

2 2 System of uler digrms Our uler digrm, clled UL-digrm, is defined s lne with nmed circles nd oints. ch digrm is secified y toologicl (inclusion nd exclusion) reltions mintined etween circles nd oints. Thus digrms re syntcticlly equivlent when the sme reltions hold on ech. sed on the interrettion of circles (res. oints) s susets (res. elements) of certin set-theoreticl domin, digrms re interreted in terms of reltions tht hold on them. In Section 2.1, we introduce syntx nd semntics of UL-digrms with existentil oints. In Section 2.2, we introduce our inference rules. 2.1 Syntx nd semntics of UL Our uler digrm in this er is slight extension of the most sic one of [Mineshim et l., 2012]: s well s constnt oints, which corresond to constnt symols of the first order lnguge FOL in symolic logic, we here introduce existentil oints, which corresond to ound vriles ssocited with the existentil quntifier of FOL. efinition 2.1. n UL-digrm is lne (R 2 ) with finite numer, t lest two, of nmed simle closed curves (simly clled nmed circles, nd denoted y,,,... ) nd constnt oints (denoted y,, c,... ), nd existentil oints (denoted y x, y, z,... ), where no two nmed circles, s well s oints, re comletely concurrent, nd no two nmed circles, s well s oints, hve the sme nme. onstnt oints nd existentil oints re collectively clled (nmed) oints, nd denoted y, q, 1, 2,.... Nmed circles nd oints re collectively clled (digrmmtic) ojects, nd denoted y s, t, u,.... We use rectngle to reresent the lne for digrm. igrms re denoted y,, 1, 2,.... When is digrm, we denote y t() the set of nmed oints of, y cr() the set of nmed circles of, y o() the set of ojects of. digrm consisting of only two ojects is clled miniml digrm, nd these re denoted y, β, γ,.... Our digrms re investigted in terms of the following toologicl reltions etween digrmmtic ojects. efinition 2.2. UL-reltions re the following reflexive symmetric inry reltion, nd irreflexive symmetric inry reltions nd : the interior of is inside of the interior of, the interior of is outside of the interior of, there is t lest one crossing oint etween nd, is inside of the interior of, is outside of the interior of, q is outside of q (i.e. is not locted t the oint of q). The set of UL-reltions tht hold in digrm is uniquely determined, nd we denote this set y rel(). In the descrition of rel(), we omit the trivil reflexive reltion s s for ech oject s. We consider n equivlence clss of lne digrms in terms of the UL-reltions. efinition 2.3. ny ir of UL-digrms nd re (syntcticlly) equivlent if rel() = rel(). 2

3 In wht follows, the digrms which re syntcticlly equivlent re identified, nd they re referred y single nme. See [Mineshim et l., 2012], for discussion out our slightly rough eqution of digrms. sed on the ove equivlence on digrms, we refer to ny miniml digrm, sy where s t holds, y the non-trivil UL-reltion holding on it, s s t. UL-digrms re interreted in terms of UL-reltions tht hold on them. efinition 2.4. model M is ir (U, I), where U is non-emty set (the domin of M), nd I is n interrettion function which ssigns to ech circle or constnt oint non-emty suset of U such tht I() is singleton for ny constnt oint, nd I() I() for ny constnt oints, of distinct nmes. In order to void the comlexity cused y existentil oints, we define our interrettion for set of digrms insted for single digrm. efinition 2.5. Let e set of digrms 1,..., n such tht rel( ) = rel( 1 ) rel( n ) = {R 1,..., R i, x 1 1,..., x 1 k,..., x l 1,..., x l k }, where is or, nd no existentil oints er in ech of R 1,..., R i. M = (U, I) is model of, written M =, if nd only if: for every R j rel( ) (1 j i), I(s) I(t) holds if R j is s t; nd I(s) I(t) = holds if R j is s t: for every x j (1 j l), there exists m j M such tht m j I( 1 ) nd nd m j I( k ) hold, where is if x j rel( ), nd it is if x j rel( ). From the symolic logicl viewoint, the ove interrettion corresonds to the usul set-theoreticl interrettion of the following formul: R 1 R i x 1 ((x 1 1 ) (x 1 k )) x l ((x l 1 ) (x l k )) Remrk 2.6. y efinition 2.5, the UL-reltion does not contriute to the truthcondition of UL-digrms. Informlly seking, might e understood s I() I() = or I() I(), which is true in ny model. The semntic consequence reltion, = etween UL-digrms is defined s usul in symolic logic. (See [Mineshim et l., 2012] for detiled descrition.) 2.2 Inference system GS Mineshim, Okd, & Tkemur (2012) introduced n uler digrmmtic inference system, clled Generlized igrmmtic Syllogistic inference system GS. It consists of two kinds of inference rules: eletion nd Unifiction. eletion llows us to delete digrmmtic oject from given digrm. Unifiction (rules of U1 U10, PI) llows us to unify two digrms into one digrm in which the semntic informtion is equivlent to the conjunction of the originl two digrms. Two kinds of constrint re imosed on unifiction. One is the constrint for determincy, which locks the disjunctive miguity with resect to loctions of nmed oints. The other is the constrint for consistency, which locks reresenting inconsistent informtion in single digrm. 3

4 ch unifiction rule is descried y secifying (i) remise digrms, one of which is required to e miniml; (ii) digrmmtic oertions to introduce new oject into, or to rerrnge configurtion of ojects of, one of the remise digrms. We lso give schemtic illustrtions nd concrete exmles of lictions of rules. We further secify the set of UL-reltions rel() of the unified digrm. In the following, we introduce our xiom, nd of the eleven unifiction rules, we descrie U5 nd U7. The other unifiction rules re found in endix nd [Mineshim et l., 2012]. We further introduce nother rule of Ren (Renming). In wht follows, in order to void nottionl comlexity in digrm, we exress ech nmed oint, sy, simly y its nme. efinition 2.7 (Inference rules of GS). xiom: For ny ir of circles nd, ny miniml digrm where holds is n xiom. ny UL-digrm tht consists only of oints is n xiom. For ny existentil oint x, nd ny circle, ny miniml digrm where x holds is n xiom. Unifiction: U5 Premises: miniml digrm on which holds; nd digrm such tht cr() (ut cr()). onstrint for determincy: holds for ll t(). Oertion: dd the circle to (with reservtion of ll reltions on ) so tht the following conditions re stisfied on : (1) holds; (2) X holds for ll circles X ( ) such tht X or X holds on. The set of reltions rel() of the unified digrm is secified s follows: rel() rel() { X X or X rel(), X } { X X rel()} {X X rel()} { t()} Schem of U5 F xmle of U5 U5 F U5 U7 Premises: miniml digrm on which holds; nd digrm such tht cr() (ut cr()). onstrint for determincy: holds for ll t(). 4

5 Oertion: dd the circle to so tht the following conditions re stisfied on : (1) holds; (2) X holds for ll circles X ( ) such tht X or X or X holds on. rel() rel() { X X or X or X rel(), X } {X X rel()} { t()} Schem of U7 xmle of U7 U7 U7 Ren (Renming) Premise: digrm contining oint such tht x for n existentil oint x. Oertion: Relce the oint of with the existentil oint x. The set of reltions rel([ x]) of the resulting digrm is secified s follows: (rel() \ { s {, }, s o()}) {x s s rel()} {x s s rel()} xmle of Ren Ren x [ x] Remrk 2.8 (oy). omining Ren nd PI rules, we re le to dulicte ny oint in digrm s illustrted in the following: Ren x PI x Note tht, in generl, n dditionl oint is restricted to e existentil, nd it is locted in the sme region s the originl oint. The notion of digrmmtic roof (or, d-roof for short) is defined inductively s tree structures consisting of Unifiction, eletion, nd Renming stes. (f. Fig. 1 in xmle 3.11.) 5

6 efinition 2.9. Let e set of UL-digrms. n UL-digrm is rovle from, written s, if there is d-roof of in GS from 1,..., m such tht: (1) i ; (2) U1, U2 rules (unifiction y shred oint) re not lied to ny existentil oint rovided y Ren rule; (3) the existentil oint of ny xiom 3 ers only in digrms directly follow the xiom. Remrk In our system, we ostulte the interrettion I() of circle is non-emty. ccording to this definition, lso in our inference rules, we dot ny miniml digrm such tht x holds s n xiom (3). Our definition corresonds to the existentil imort in the literture of syllogisms. Without this ostulte, two digrms 1 in tht holds, nd 2 in tht holds, re consistent, when denotes the emty set. (f. Lemm 3.3.) However, it is difficult to exress 1 nd 2 in single digrm in our frmework. Introduction of nother device such s shding, which exress the corresonding region is emty, my coe with this rolem rtly. However, the question remins whether we drw the shded circle inside or outside. Thus, in our sic uler digrmmtic system, we ssume the existentil imort. Lemm The following hold in GS: 1. If u s nd s t, then u t; 2. If u t nd s t, then u s; 3. If u s nd s t nd v t, then u v. 3 omleteness of GS In this section, we rove soundness (Theorem 3.1) nd comleteness (Theorem 3.10) of GS with resect to our forml semntics. The soundness is shown y induction on the height of given d-roof s usul. Theorem 3.1 (Soundness). Let, e UL-digrms. If is rovle from the remises ( ) in GS, then is n semntic consequence of ( = ). For the comleteness, we imose the following condition for remise digrms: efinition 3.2. set of digrms is consistent if it hs model. Without this condition, ny digrm, sy where holds, is vlid consequence of n inconsistent set of remise digrms 1 nd 2 where nd hold, resectively, lthough there is no d-roof of from 1 nd 2 in GS. This is ecuse GS does not hve rule tht corresonds to the surdity rule of usul nturl deduction: we cn infer ny digrm from ir of inconsistent digrms. It is ovious tht the soundness theorem lso holds under the ssumtion of the consistency of the remises. The following is n imortnt consequence of the consistency: Lemm 3.3 (onsistency). Let e set of digrms which is consistent. Then none of the following holds in GS for ny ojects s nd t: 1. s t nd s t. 2. There is n oject u such tht s t nd u s nd u t. 6

7 Proof. (1) y the soundness of GS, in ny model M = (U, I) of, we hve I(s) I(t), nd I(s) I(t) =. y the definition of our interrettion, we hve I(s), nd hence, we hve I(s) I(t), which contrdicts to I(s) I(t) =. (2) ssume u is nmed oint. Then, y the soundness of GS, in ny model M = (U, I) of, we hve I(s) I(t) = nd I(s) I(t), ut it is imossile. When u is circle, y the definition of our interrettion, I(u). Hence, I(u) I(s) nd I(u) I(t) imly I(s) I(t). Thus, this cse is lso imossile s the revious cse. In order to show the comleteness theorem of GS, we construct two kinds of syntctic models, clled cnonicl models, in similr wy s the construction of Lindenum lgers in the literture of lgeric semntics for vrious roositionl logics. We first define the simler one. efinition 3.4 (nonicl model M ). Let e set of miniml digrms which is consistent. cnonicl model M = (M, I ) for is defined s follows: The domin M is the set of digrmmtic ojects (nmed circles nd oints) which occur in ny miniml digrm. I is n interrettion function such tht, for ny oject t, I (t) = {s s t in GS} {t}. Oserve tht in the ove definition of I, when t is nmed oint, sy, its interrettion I () is the singleton {} since s for ny oject s y soundness. Lemm 3.5 (nonicl model M ). Let e set 1,..., n of miniml digrms which is consistent. Then M is model of. Proof. We divide into the following cses ccording to the reltion R rel( ). Since the cse R is of the form s t is ovious, we ssume R s t in wht follows. 1. When R is of the form s t, in which s is not n existentil oint, we hve s t in GS since s t rel( ). We show M = s t, i.e., I (s) I (t). Let u I (s). () When u s, we immeditely hve s I (t) y the fct s t. () Otherwise, y the definition of I (s), we hve u s. y comosing it with s t s seen in Lemm 2.11(1), we hve u t in GS, tht is, u I (t). 2. When R is of the form s t, in which s nor t is n existentil oint, we hve s t in GS. We show M = s t, i.e., I (s) I (t) =. When oth s nd t re constnt oints, the clim is trivil. Otherwise, ssume to the contrry tht some u I (s) I (t). () When u s, we hve s I (t), i.e., s t. This, together with s t, is contrdiction y Lemm 3.3(1). The sme lies to the cse u t. () Otherwise, s u t, we hve u s nd u t y the definition of I (s) nd I (t). They contrdict s t y Lemm 3.3(2). 3. When ll reltions of n existentil oint x of rel( ) re x 1,..., x i, x 1,..., x j, we show tht there exists m M such tht m I ( 1 ) I ( i ) I ( 1 ) I ( j ), where X denotes the comlement of set X. 7

8 For every 1 k i, we hve x k, since x k rel( ). Hence, y the definition of I, we hve x I ( k ). For every 1 l j, to show x I ( l ), we ssume to the contrry tht x I ( l ). Then, y the definition of I, we hve x l. On the other hnd, since x l rel( ), we hve x l. They re contrdiction y Lemm 3.3(1). Thus, we hve x I ( 1 ) I ( i ) I ( 1 ) I ( j ). s n illustrtion of the cnonicl model, let us consider the following exmle. xmle 3.6. Let e the following miniml digrms 1, 2, 3, 4 : c 1 2 Oserve tht we hve nd. In such cse, we sy tht the oint is indeterminte with resect to the circle. Let us construct the cnonicl model for the y defining: I () = {,, x, y, z,... }, where x, y, z,... denotes ll existentil oints, nd I () = {, c, x, y, z,... }. Note tht the indeterminte oint w.r.t. is not contined in the interrettion of. With this interrettion, for ny nmed oint I (), we hve. In generl, vlidity of -reltion in the model M imlies rovility of -reltion. In the ove model, however, I () does not necessrily imly ; ecuse we do not hve, while I (). Thus, in the cnonicl model M of efinition 3.4, vlidity of -reltion does not imly rovility of -reltion, nd hence the model is not enough to estlish comleteness. Let us try to modify the ove model M so tht the indeterminte oint w.r.t. is contined in the interrettion I () of : I () = {,, x, y, z,... } nd I () = {, c,, x, y, z,... }. This definition lso rovides model of, nd we hve for ny oint I (). However, in this model, I () does not necessrily imly ; ecuse we do not hve, while I (). lthough one of our two cnonicl models lone is insufficient to estlish comleteness, we cn otin our comleteness result in the following mnner: we construct cnonicl model M (efinition 3.4 ove) for vlidity of -reltion, which imlies rovility of - reltion, nd model M, (efinition 3.7 elow) for vlidity of -reltion, which imlies rovility of -reltion. We now construct nother cnonicl model. In contrst to the revious model M of efinition 3.4, we include, for fixed circle, indeterminte ojects w.r.t. into the interrettion of the circle in the following model M,. efinition 3.7 (nonicl model M, ). Let e set of miniml digrms which is consistent. Let e fixed nmed circle. cnonicl model M, = (M,, I, ) for is defined s follows: The domin M, is the sme set s M of efinition 3.4. I, is n interrettion function defined s follows: For ny oject t, when t or t holds, I, (t) = I (t) {s s nd s nd s }; otherwise, I, (t) = I (t)

9 Lemm 3.8 (nonicl model M, ). Let e set 1,..., n of miniml digrms which is consistent. Let e fixed nmed circle. Then M, is model of. Proof. We divide into the following cses ccording to the form of R rel( ). We write s t when none of s t, t s, nd s t holds. Since the cse R is of the form s t is trivil, we ssume R is not of the form. 1. When R is of the form s t, we hve s t since s t rel( ). We show I, (s) I, (t). Let u I, (s). Since the cse u s is immedite, we ssume u s. ssume s or s hold. Then, y the definition of I, (s), we hve (i) u s or (ii) u. (i) imlies, together with s t, tht u t, y Lemm 2.11(1), i.e., u I, (t). For (ii), s nd s t imly t y Lemm 2.11(1). Hence, in conjunction with u, we hve u I, (t) y the definition of I,. The other cse (s nd s) is similr. 2. When R is of the form s t, we hve s t since s t rel( ). We ssume s t nd s u t since the other cses re similr. We show tht I, (s) I, (t) =. When oth s nd t re oints, the clim is trivil. Otherwise, ssume to the contrry tht some u I, (s) I, (t). We divide into the following cses: (i) s nd t; (ii) s nd t; (iii) s nd t; (iv) s nd t. (i) contrdicts s t. For (ii), y the definitions of I, (s) nd I, (t), we hve u s nd u t, which contrdict s t. For (iii), y the definition of I, (s), we hve u s. y the definition of I, (t), we hve (iii-1) u t or (iii-2) u. (iii-1), together with u s, contrdicts s t. For (iii-2), u s, s t, nd t imly, y Lemm 2.11(3), tht u, which contrdicts u. (iv) is similr to (iii). 3. When ll reltions of n existentil oint x of rel( ) re x 1,..., x i, x 1,..., x j, we show tht there exists some m M, such tht m I, ( 1 ) I, ( i ) I, ( 1 ) I, ( j ). For every 1 k i, we hve x k since x k rel( ). Hence, we hve x I ( k ), tht imlies x I, ( k ). For every 1 l j, in order to show x I, ( l ), we ssume to the contrry tht x I, ( l ). Let l or l. Then, y the definition of I, ( l ), we hve (i) x l or (ii) x. (i) leds to contrdiction since we hve x l y the fct x l rel( ). For (ii), y the fct x l nd l, we hve x, which contrdicts to (ii). The other cse ( l nd l ) is immedite. Therefore, we hve x I, ( 1 ) I, ( i ) I, ( 1 ) I, ( j ). Using the two kinds of cnonicl models introduced so fr, we rove the following tomic comleteness, from which comleteness (Theorem 3.10) of GS is derived. Proosition 3.9 (tomic comleteness). Let 1,..., n e set of digrms which is consistent. Let β e miniml digrm. If 1,..., n = β, then 1,..., n β in GS. Proof. We first consider the cse where the remise digrms 1,..., n re restricted to miniml digrms 1,..., n. Then we extend to the generl cse. We denote y the set of given miniml digrms. ssume = β. When β is s t, we immeditely hve s t since it is n xiom. Otherwise, we divide into the following two cses ccording to the form of β. 9

10 (1) When β is of the form s t, y the ssumtion = s t, we hve, in rticulr for the cnonicl model of efinition 3.4, M = M = s t. Then, since M = y Lemm 3.5, we hve M = s t, i.e., I (s) I (t). Since s I (s) y efinition 3.4, we hve s I (t), tht is, s t in GS. (2) When β is of the form s t, oserve tht if s nd t re oth oints, then the ssertion is trivil since β is n xiom in tht cse. Otherwise, we ssume, without loss of generlity, tht t is nmed circle. y the ssumtion = s, we hve, in rticulr for the cnonicl model of efinition 3.7, M, = M, = s. Then since M, = y Lemm 3.8, we hve M, = s, i.e., I, (s) I, () =. Hence we hve s I, () nd I, (s). Then y the definition of I, () nd I, (s) of efinition 3.7, we hve s, nd s nd s for some {,, }. Therefore, we hve s in GS. Next, we extend the remises to generl digrms 1,..., n insted of miniml digrms. Let 1,..., n = β. Let rel( ) = {R 1,..., R m }, then there is some such tht rel( ) = rel( ). Hence, when M =, y the ove rgument, we hve β, i.e., there is d-roof from 1,..., m to β in GS. Since ech j is derived from some i y some lictions of eletion rule, we hve 1,..., n β. y extending the conclusion digrm β of tomic comleteness to generl (not restricted to miniml) digrm, we estlish our comleteness theorem. Proosition 3.10 (omleteness). Let 1,..., n, e UL-digrms. Let 1,..., n e consistent. If 1,..., n =, then 1,..., n in GS. Proof (sketch). We define cnonicl wy to construct d-roof of from the given remise digrms 1,..., n (see lso xmle 3.11 elow): (I) Miniml rt: y using the tomic comleteness theorem, we derive ll of: (1) ointfree miniml digrms ering in the conclusion; (2) ointed miniml digrms consisting of every oint contined in remise; (3) ointed miniml digrms otined y comining the digrms of (1) with n xiom 3 of the form x for fresh oint x nd for circle contined in remise or the conclusion. (II) Venn rt: y lying U1, U2 rules for the ove ointed miniml digrms of (I-2) nd (I-3), we construct, for every oint of the Miniml rt, Venn-like digrm, in which holds for ny ir of circles in it, nd which consists of nd ll circles of the conclusion. If it is not ossile to construct Venn-like digrm for oint ecuse of the constrint for determincy, we do not construct it. When no Venn-like digrm with oint is constructed, y lying U8 rule nd the xiom 1, we construct Venn-like digrm (without ny oint) which consists of ll circles of. (III) Modifiction rt: y using U9, U10, nd the oint-free miniml digrms otined t the Miniml rt (I-1), we modify forms nd ositions of circles of ech Venn-like digrm ove so tht they corresond to those of the conclusion. (IV) PI rt: y lying PI, we unify ll digrms otined t the Modifiction rt. 10

11 (V) Renming rt: We finlly otin y lying Ren, el, nd the coy oertion descried in Remrk 2.8. y the definition of our inference rules, oint in the conclusion comes, ossily with lictions of Ren, from the following wys: (1) it is contined in remise; (2) it is otined y lying the coy oertion of Remrk 2.8; (3) it is rovided y lying the xiom 3. Thus, t the Miniml rt, we derive ll ossile ointed miniml digrms consisting of these oints. lso t the Renming rt, we otin the conclusion y lying Ren, el, nd the coy oertion. t the Venn rt, we re le to ignore oint for which we cnnot construct Venn-like digrm. This is ecuse, for ny oint contined in the conclusion, the reltions etween the oint nd ll circles of re determined. t the Modifiction rt, we re le to ly U9, U10 rules undisturedly. This is ecuse, if digrms 1 nd 2 could not e unified ecuse of the constrint for consistency of U9, U10 rules, since 1 nd 2 re oth derived from the remises, it mens the remises re inconsistent. t the PI rt, we re le to unify ll digrms otined so fr. This is ecuse ll circles nd oints of those digrms re essentilly the sme s those of the conclusion excet for their nmes. The correctness of the ove cnonicl construction is shown in similr wy s [Mineshim et l., 2012]. Fig. 1 is n exmle of the cnonicl d-roof. xmle 3.11 (nonicl d-roof of GS). s n illustrtion of the cnonicl construction of d-roofs, let us consider the following digrms 1, 2, 3, nd : 1,, 2 We hve cnonicl d-roof of from 1, 2, 3 s in Fig. 1, where the derivtion of 15 is omitted since it is similr to tht of 13. We first derive ointed miniml digrms 1, 4, 5, 6 consisting of oint contined in remise (I-2), nd 7, 8 consisting of fresh oint comes from n xiom 3 (I-3). Next, t the Venn rt, with U1 nd U2 rules, we construct Venn-like digrms 9, 10 nd 11 ech of which consists of the ove oint (,, z) nd ll circles nd of. Then, t the Modifiction rt, with U10 rule, we modify the ove Venn-like digrms so tht ositions of circles fit to those of the conclusion. Then, t the PI rt, with PI rule, we unify 12, 13, 14, nd 15 to otin 18. Finlly, y renming the nmes of the oints nd z, nd y deleting w, we otin the conclusion. 3 x y References [Howse et l., 2005] J. Howse, G. Stleton, nd J. Tylor (2005) Sider igrms, LMS Journl of omuttion nd Mthemtics, London Mthemticl Society, Volume 8,

12 2 2 1 U2 4 9 U U7 PI 5 3 U U PI z PI x z 3 w z 18 Ren & el y U7 7 Fig. 1 nonicl d-roof z z 3 U1 z 11 z 8 U10 z 14 } 3 Miniml }. w 15 Venn Renming } Modifiction PI [Mineshim et l., 2012] K. Mineshim, M. Okd, nd R. Tkemur (2012) igrmmtic Inference System with uler ircles, Journl of Logic, Lnguge nd Informtion, 21, 3, [Shimojim, 1996]. Shimojim (1996) On the fficcy of Reresenttion, Ph. thesis, Indin University. [Shin, 1994] S.-J. Shin (1994) The Logicl Sttus of igrms, mridge University Press. [Stleton, 2005] G. Stleton (2005) survey of resoning systems sed on uler digrms, Proceedings of uler 2004, lectronic Notes in Theoreticl omuter Science, 134, 1, [Tkemur, 2013] R. Tkemur (2013) Proof theory for resoning with uler digrms: logic trnsltion nd normliztion, Studi Logic, 101, 1,

13 Unifiction rules of GS Unifiction rules re divided into three grous, Grou (I), (II), nd (III). The rules in Grou (I) nd (II) re clssified ccording to the numer nd tye of ojects shred y digrm nd miniml digrm. The rule in Grou (III) is the PI rule, where neither of two remise digrms is restricted to e miniml. (I) The cse nd shre one oject: U1 Premises: holds on, nd t(). onstrint for determincy: t() = {}. Oertion: dd the circle to (with reservtion of ll reltions on ) so tht the following conditions re stisfied on +: (1) holds; (2) X holds for ll circles X of. The set of reltions rel() is secified s rel() rel() { X X cr()}. Schem of U1 U1 xmle of U1 U1 U2 Premises: holds on, nd t(). onstrint for determincy: t() = {}. Oertion: dd the circle to so tht the following conditions re stisfied on : (1) holds; (2) X holds for ll circles X of. rel() = rel() rel() { X X cr()} Schem of U2 U2 xmle of U2 U2 U3 Premises: holds on, nd cr(). onstrint for determincy: X or X holds for ll circles X of. Oertion: dd the oint to so tht the following conditions re stisfied on : (1) holds; (2) q holds for ll oints q such tht q holds on. rel() =rel() rel() { X X rel()} { X X rel()} { q q t()} 13

14 U4 U3 U3 Premises: holds on, nd cr(). onstrint for determincy: X holds for ll circles X of. Oertion: dd the oint to so tht the following conditions re stisfied on : (1) holds; (2) q holds for ll oints q such tht q holds on. rel() = rel() rel() { X X rel()} { q q t()} U4 U4 U6 Premises: holds on, nd cr(). onstrint for determincy: holds for ll t(). Oertion: dd the circle to so tht the following conditions re stisfied on : (1) holds; (2) X holds for ll circles X( ) such tht X or X or X holds on. rel() = rel() rel() {X X or X or X rel(), X } {X X rel()} { t()} U6 U6 U8 Premises: holds on, nd cr(). onstrint for determincy: t() =. Oertion: dd the circle to so tht X holds for ll circles X of. rel() = rel() rel() { X X cr()} U8 14 U8

15 (II) The cse nd shre two circles: U9 Premises: holds on, nd holds on. onstrint for consistency: There is no oject s such tht s nd s hold on. Oertion: Modify ll circles X (including ) of such tht X holds so tht the following conditions re stisfied on +: (1) X holds; (2) X t holds with {,,, } for ll oject t of such tht t, X t rel(). rel(+)= ( rel() \ {X Y X nd Y rel()} \ {X Y X nd Y rel()} ) {X Y X nd Y rel()} {X Y X nd Y rel()} U9 U9 U10 Premises: holds on, nd holds on. onstrint for consistency: There is no oject s such tht s nd s hold on. Oertion: Modify ll circles X (including ) nd Y (including ) of such tht X nd Y, resectively hold on so tht the following conditions re stisfied on : (1) X holds; (2) X t holds with {,,, } for ll oject t of such tht t, X t rel(); (3) Y holds; (4) Y s holds with {,,, } for ll oject s of such tht s, Y s rel(). rel() = ( rel() \ {X Y X nd Y rel()} ) {X Y X nd Y rel()} F U10 U10 F (III) Neither of two remise digrms is restricted to e miniml: PI (Point Insertion) Premises: X Y rel( 1 ) iff X Y rel( 2 ) holds for ny circles X, Y with {,,, }, nd t( 2 ) = {} such tht t( 1 ). Oertion: dd the oint to 1 so tht the following conditions re stisfied on : (1) t of rel( 2 ) holds for ll ojects t; (2) q holds for ll q t( 1 ). rel( ) = rel( 1 ) rel( 2 ) { q q t( 1 )} 15

16 c 1 2 c el (eletion) Premise: contins n oject s. onstrint: is not miniml. Oertion: elete the oject s from. rel( s) = rel() \ {s t t o(), {,,, }} 18 Leonhrd uler 1990 Mineshim, Okd, & Tkemur (2012) Mineshim, Okd, & Tkemur (2012) 16

A Diagrammatic Inference System with Euler Circles

A Diagrammatic Inference System with Euler Circles igrmmtic Inference System with uler ircles Koji Mineshim, Mitsuhiro Okd, nd Ryo Tkemur eprtment of Philosophy, Keio University, Jpn. {minesim,mitsu,tkemur}@elrd.flet.keio.c.jp strct Proof-theory hs trditionlly

More information

Coalgebra, Lecture 15: Equations for Deterministic Automata

Coalgebra, Lecture 15: Equations for Deterministic Automata Colger, Lecture 15: Equtions for Deterministic Automt Julin Slmnc (nd Jurrin Rot) Decemer 19, 2016 In this lecture, we will study the concept of equtions for deterministic utomt. The notes re self contined

More information

Name of the Student:

Name of the Student: SUBJECT NAME : Discrete Mthemtics SUBJECT CODE : MA 2265 MATERIAL NAME : Formul Mteril MATERIAL CODE : JM08ADM009 Nme of the Student: Brnch: Unit I (Logic nd Proofs) 1) Truth Tble: Conjunction Disjunction

More information

USA Mathematical Talent Search Round 1 Solutions Year 25 Academic Year

USA Mathematical Talent Search Round 1 Solutions Year 25 Academic Year 1/1/5. Alex is trying to oen lock whose code is sequence tht is three letters long, with ech of the letters being one of A, B or C, ossibly reeted. The lock hs three buttons, lbeled A, B nd C. When the

More information

k and v = v 1 j + u 3 i + v 2

k and v = v 1 j + u 3 i + v 2 ORTHOGONAL FUNCTIONS AND FOURIER SERIES Orthogonl functions A function cn e considered to e generliztion of vector. Thus the vector concets like the inner roduct nd orthogonlity of vectors cn e extended

More information

Supplement 4 Permutations, Legendre symbol and quadratic reciprocity

Supplement 4 Permutations, Legendre symbol and quadratic reciprocity Sulement 4 Permuttions, Legendre symbol nd qudrtic recirocity 1. Permuttions. If S is nite set contining n elements then ermuttion of S is one to one ming of S onto S. Usully S is the set f1; ; :::; ng

More information

Designing finite automata II

Designing finite automata II Designing finite utomt II Prolem: Design DFA A such tht L(A) consists of ll strings of nd which re of length 3n, for n = 0, 1, 2, (1) Determine wht to rememer out the input string Assign stte to ech of

More information

QUADRATIC RESIDUES MATH 372. FALL INSTRUCTOR: PROFESSOR AITKEN

QUADRATIC RESIDUES MATH 372. FALL INSTRUCTOR: PROFESSOR AITKEN QUADRATIC RESIDUES MATH 37 FALL 005 INSTRUCTOR: PROFESSOR AITKEN When is n integer sure modulo? When does udrtic eution hve roots modulo? These re the uestions tht will concern us in this hndout 1 The

More information

Handout: Natural deduction for first order logic

Handout: Natural deduction for first order logic MATH 457 Introduction to Mthemticl Logic Spring 2016 Dr Json Rute Hndout: Nturl deduction for first order logic We will extend our nturl deduction rules for sententil logic to first order logic These notes

More information

Duke Math Meet

Duke Math Meet Duke Mth Meet 01-14 Power Round Qudrtic Residues nd Prime Numers For integers nd, we write to indicte tht evenly divides, nd to indicte tht does not divide For exmle, 4 nd 4 Let e rime numer An integer

More information

Farey Fractions. Rickard Fernström. U.U.D.M. Project Report 2017:24. Department of Mathematics Uppsala University

Farey Fractions. Rickard Fernström. U.U.D.M. Project Report 2017:24. Department of Mathematics Uppsala University U.U.D.M. Project Report 07:4 Frey Frctions Rickrd Fernström Exmensrete i mtemtik, 5 hp Hledre: Andres Strömergsson Exmintor: Jörgen Östensson Juni 07 Deprtment of Mthemtics Uppsl University Frey Frctions

More information

1. For each of the following theorems, give a two or three sentence sketch of how the proof goes or why it is not true.

1. For each of the following theorems, give a two or three sentence sketch of how the proof goes or why it is not true. York University CSE 2 Unit 3. DFA Clsses Converting etween DFA, NFA, Regulr Expressions, nd Extended Regulr Expressions Instructor: Jeff Edmonds Don t chet y looking t these nswers premturely.. For ech

More information

Revision Sheet. (a) Give a regular expression for each of the following languages:

Revision Sheet. (a) Give a regular expression for each of the following languages: Theoreticl Computer Science (Bridging Course) Dr. G. D. Tipldi F. Bonirdi Winter Semester 2014/2015 Revision Sheet University of Freiurg Deprtment of Computer Science Question 1 (Finite Automt, 8 + 6 points)

More information

Formal Languages and Automata

Formal Languages and Automata Moile Computing nd Softwre Engineering p. 1/5 Forml Lnguges nd Automt Chpter 2 Finite Automt Chun-Ming Liu cmliu@csie.ntut.edu.tw Deprtment of Computer Science nd Informtion Engineering Ntionl Tipei University

More information

Assignment 1 Automata, Languages, and Computability. 1 Finite State Automata and Regular Languages

Assignment 1 Automata, Languages, and Computability. 1 Finite State Automata and Regular Languages Deprtment of Computer Science, Austrlin Ntionl University COMP2600 Forml Methods for Softwre Engineering Semester 2, 206 Assignment Automt, Lnguges, nd Computility Smple Solutions Finite Stte Automt nd

More information

CS12N: The Coming Revolution in Computer Architecture Laboratory 2 Preparation

CS12N: The Coming Revolution in Computer Architecture Laboratory 2 Preparation CS2N: The Coming Revolution in Computer Architecture Lortory 2 Preprtion Ojectives:. Understnd the principle of sttic CMOS gte circuits 2. Build simple logic gtes from MOS trnsistors 3. Evlute these gtes

More information

(9) P (x)u + Q(x)u + R(x)u =0

(9) P (x)u + Q(x)u + R(x)u =0 STURM-LIOUVILLE THEORY 7 2. Second order liner ordinry differentil equtions 2.1. Recll some sic results. A second order liner ordinry differentil eqution (ODE) hs the form (9) P (x)u + Q(x)u + R(x)u =0

More information

Quadratic Forms. Quadratic Forms

Quadratic Forms. Quadratic Forms Qudrtic Forms Recll the Simon & Blume excerpt from n erlier lecture which sid tht the min tsk of clculus is to pproximte nonliner functions with liner functions. It s ctully more ccurte to sy tht we pproximte

More information

Parse trees, ambiguity, and Chomsky normal form

Parse trees, ambiguity, and Chomsky normal form Prse trees, miguity, nd Chomsky norml form In this lecture we will discuss few importnt notions connected with contextfree grmmrs, including prse trees, miguity, nd specil form for context-free grmmrs

More information

Watson-Crick local languages and Watson-Crick two dimensional local languages

Watson-Crick local languages and Watson-Crick two dimensional local languages Interntionl Journl of Mthemtics nd Soft Comuting Vol.5 No.. (5) 65-7. ISSN Print : 49 338 ISSN Online: 39 55 Wtson-Crick locl lnguges nd Wtson-Crick two dimensionl locl lnguges Mry Jemim Smuel nd V.R.

More information

Families of Solutions to Bernoulli ODEs

Families of Solutions to Bernoulli ODEs In the fmily of solutions to the differentil eqution y ry dx + = it is shown tht vrition of the initil condition y( 0 = cuses horizontl shift in the solution curve y = f ( x, rther thn the verticl shift

More information

Lecture 09: Myhill-Nerode Theorem

Lecture 09: Myhill-Nerode Theorem CS 373: Theory of Computtion Mdhusudn Prthsrthy Lecture 09: Myhill-Nerode Theorem 16 Ferury 2010 In this lecture, we will see tht every lnguge hs unique miniml DFA We will see this fct from two perspectives

More information

CS 275 Automata and Formal Language Theory

CS 275 Automata and Formal Language Theory CS 275 utomt nd Forml Lnguge Theory Course Notes Prt II: The Recognition Prolem (II) Chpter II.5.: Properties of Context Free Grmmrs (14) nton Setzer (Bsed on ook drft y J. V. Tucker nd K. Stephenson)

More information

Boolean Algebra. Boolean Algebra

Boolean Algebra. Boolean Algebra Boolen Alger Boolen Alger A Boolen lger is set B of vlues together with: - two inry opertions, commonly denoted y + nd, - unry opertion, usully denoted y ˉ or ~ or, - two elements usully clled zero nd

More information

3 Regular expressions

3 Regular expressions 3 Regulr expressions Given n lphet Σ lnguge is set of words L Σ. So fr we were le to descrie lnguges either y using set theory (i.e. enumertion or comprehension) or y n utomton. In this section we shll

More information

Lecture 08: Feb. 08, 2019

Lecture 08: Feb. 08, 2019 4CS4-6:Theory of Computtion(Closure on Reg. Lngs., regex to NDFA, DFA to regex) Prof. K.R. Chowdhry Lecture 08: Fe. 08, 2019 : Professor of CS Disclimer: These notes hve not een sujected to the usul scrutiny

More information

Minimal DFA. minimal DFA for L starting from any other

Minimal DFA. minimal DFA for L starting from any other Miniml DFA Among the mny DFAs ccepting the sme regulr lnguge L, there is exctly one (up to renming of sttes) which hs the smllest possile numer of sttes. Moreover, it is possile to otin tht miniml DFA

More information

p-adic Egyptian Fractions

p-adic Egyptian Fractions p-adic Egyptin Frctions Contents 1 Introduction 1 2 Trditionl Egyptin Frctions nd Greedy Algorithm 2 3 Set-up 3 4 p-greedy Algorithm 5 5 p-egyptin Trditionl 10 6 Conclusion 1 Introduction An Egyptin frction

More information

Quadratic reciprocity

Quadratic reciprocity Qudrtic recirocity Frncisc Bozgn Los Angeles Mth Circle Octoer 8, 01 1 Qudrtic Recirocity nd Legendre Symol In the eginning of this lecture, we recll some sic knowledge out modulr rithmetic: Definition

More information

set is not closed under matrix [ multiplication, ] and does not form a group.

set is not closed under matrix [ multiplication, ] and does not form a group. Prolem 2.3: Which of the following collections of 2 2 mtrices with rel entries form groups under [ mtrix ] multipliction? i) Those of the form for which c d 2 Answer: The set of such mtrices is not closed

More information

Lecture 2 : Propositions DRAFT

Lecture 2 : Propositions DRAFT CS/Mth 240: Introduction to Discrete Mthemtics 1/20/2010 Lecture 2 : Propositions Instructor: Dieter vn Melkeeek Scrie: Dlior Zelený DRAFT Lst time we nlyzed vrious mze solving lgorithms in order to illustrte

More information

Quadratic Residues. Chapter Quadratic residues

Quadratic Residues. Chapter Quadratic residues Chter 8 Qudrtic Residues 8. Qudrtic residues Let n>be given ositive integer, nd gcd, n. We sy tht Z n is qudrtic residue mod n if the congruence x mod n is solvble. Otherwise, is clled qudrtic nonresidue

More information

Boolean algebra.

Boolean algebra. http://en.wikipedi.org/wiki/elementry_boolen_lger Boolen lger www.tudorgir.com Computer science is not out computers, it is out computtion nd informtion. computtion informtion computer informtion Turing

More information

McGill University Math 354: Honors Analysis 3 Fall 2012 Solutions to selected Exercises. g(x) 2 dx 1 2 a

McGill University Math 354: Honors Analysis 3 Fall 2012 Solutions to selected Exercises. g(x) 2 dx 1 2 a McGill University Mth 354: Honors Anlysis 3 Fll 2012 Assignment 1 Solutions to selected Exercises Exercise 1. (i) Verify the identity for ny two sets of comlex numers { 1,..., n } nd { 1,..., n } ( n )

More information

Convert the NFA into DFA

Convert the NFA into DFA Convert the NF into F For ech NF we cn find F ccepting the sme lnguge. The numer of sttes of the F could e exponentil in the numer of sttes of the NF, ut in prctice this worst cse occurs rrely. lgorithm:

More information

Reasoning and programming. Lecture 5: Invariants and Logic. Boolean expressions. Reasoning. Examples

Reasoning and programming. Lecture 5: Invariants and Logic. Boolean expressions. Reasoning. Examples Chir of Softwre Engineering Resoning nd progrmming Einführung in die Progrmmierung Introduction to Progrmming Prof. Dr. Bertrnd Meyer Octoer 2006 Ferury 2007 Lecture 5: Invrints nd Logic Logic is the sis

More information

Closure Properties of Regular Languages

Closure Properties of Regular Languages Closure Properties of Regulr Lnguges Regulr lnguges re closed under mny set opertions. Let L 1 nd L 2 e regulr lnguges. (1) L 1 L 2 (the union) is regulr. (2) L 1 L 2 (the conctention) is regulr. (3) L

More information

Bases for Vector Spaces

Bases for Vector Spaces Bses for Vector Spces 2-26-25 A set is independent if, roughly speking, there is no redundncy in the set: You cn t uild ny vector in the set s liner comintion of the others A set spns if you cn uild everything

More information

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER LANGUAGES AND COMPUTATION ANSWERS

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER LANGUAGES AND COMPUTATION ANSWERS The University of Nottinghm SCHOOL OF COMPUTER SCIENCE LEVEL 2 MODULE, SPRING SEMESTER 2016 2017 LNGUGES ND COMPUTTION NSWERS Time llowed TWO hours Cndidtes my complete the front cover of their nswer ook

More information

CMPSCI 250: Introduction to Computation. Lecture #31: What DFA s Can and Can t Do David Mix Barrington 9 April 2014

CMPSCI 250: Introduction to Computation. Lecture #31: What DFA s Can and Can t Do David Mix Barrington 9 April 2014 CMPSCI 250: Introduction to Computtion Lecture #31: Wht DFA s Cn nd Cn t Do Dvid Mix Brrington 9 April 2014 Wht DFA s Cn nd Cn t Do Deterministic Finite Automt Forml Definition of DFA s Exmples of DFA

More information

1 From NFA to regular expression

1 From NFA to regular expression Note 1: How to convert DFA/NFA to regulr expression Version: 1.0 S/EE 374, Fll 2017 Septemer 11, 2017 In this note, we show tht ny DFA cn e converted into regulr expression. Our construction would work

More information

Homework 3 Solutions

Homework 3 Solutions CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 3 Solutions 1. Give NFAs with the specified numer of sttes recognizing ech of the following lnguges. In ll cses, the lphet is Σ = {,1}.

More information

CM10196 Topic 4: Functions and Relations

CM10196 Topic 4: Functions and Relations CM096 Topic 4: Functions nd Reltions Guy McCusker W. Functions nd reltions Perhps the most widely used notion in ll of mthemtics is tht of function. Informlly, function is n opertion which tkes n input

More information

Exercises with (Some) Solutions

Exercises with (Some) Solutions Exercises with (Some) Solutions Techer: Luc Tesei Mster of Science in Computer Science - University of Cmerino Contents 1 Strong Bisimultion nd HML 2 2 Wek Bisimultion 31 3 Complete Lttices nd Fix Points

More information

1 Nondeterministic Finite Automata

1 Nondeterministic Finite Automata 1 Nondeterministic Finite Automt Suppose in life, whenever you hd choice, you could try oth possiilities nd live your life. At the end, you would go ck nd choose the one tht worked out the est. Then you

More information

378 Relations Solutions for Chapter 16. Section 16.1 Exercises. 3. Let A = {0,1,2,3,4,5}. Write out the relation R that expresses on A.

378 Relations Solutions for Chapter 16. Section 16.1 Exercises. 3. Let A = {0,1,2,3,4,5}. Write out the relation R that expresses on A. 378 Reltions 16.7 Solutions for Chpter 16 Section 16.1 Exercises 1. Let A = {0,1,2,3,4,5}. Write out the reltion R tht expresses > on A. Then illustrte it with digrm. 2 1 R = { (5,4),(5,3),(5,2),(5,1),(5,0),(4,3),(4,2),(4,1),

More information

OPIAL S INEQUALITY AND OSCILLATION OF 2ND ORDER EQUATIONS. 1. Introduction We consider the second-order linear differential equation.

OPIAL S INEQUALITY AND OSCILLATION OF 2ND ORDER EQUATIONS. 1. Introduction We consider the second-order linear differential equation. PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY Volume 5, Numer, Aril 997, Pges 3 9 S 000-993997)03907-5 OPIAL S INEQUALITY AND OSCILLATION OF ND ORDER EQUATIONS R C BROWN AND D B HINTON Communicted y

More information

Chapter 9 Definite Integrals

Chapter 9 Definite Integrals Chpter 9 Definite Integrls In the previous chpter we found how to tke n ntiderivtive nd investigted the indefinite integrl. In this chpter the connection etween ntiderivtives nd definite integrls is estlished

More information

Learning Goals. Relational Query Languages. Formal Relational Query Languages. Formal Query Languages: Relational Algebra and Relational Calculus

Learning Goals. Relational Query Languages. Formal Relational Query Languages. Formal Query Languages: Relational Algebra and Relational Calculus Forml Query Lnguges: Reltionl Alger nd Reltionl Clculus Chpter 4 Lerning Gols Given dtse ( set of tles ) you will e le to express dtse query in Reltionl Alger (RA), involving the sic opertors (selection,

More information

Vectors , (0,0). 5. A vector is commonly denoted by putting an arrow above its symbol, as in the picture above. Here are some 3-dimensional vectors:

Vectors , (0,0). 5. A vector is commonly denoted by putting an arrow above its symbol, as in the picture above. Here are some 3-dimensional vectors: Vectors 1-23-2018 I ll look t vectors from n lgeric point of view nd geometric point of view. Algericlly, vector is n ordered list of (usully) rel numers. Here re some 2-dimensionl vectors: (2, 3), ( )

More information

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir)

BİL 354 Veritabanı Sistemleri. Relational Algebra (İlişkisel Cebir) BİL 354 Veritnı Sistemleri Reltionl lger (İlişkisel Ceir) Reltionl Queries Query lnguges: llow mnipultion nd retrievl of dt from dtse. Reltionl model supports simple, powerful QLs: Strong forml foundtion

More information

Tries and suffixes trees

Tries and suffixes trees Trie: A dt-structure for set of words Tries nd suffixes trees Alon Efrt Comuter Science Dertment University of Arizon All words over the lhet Σ={,,..z}. In the slides, let sy tht the lhet is only {,,c,d}

More information

Harvard University Computer Science 121 Midterm October 23, 2012

Harvard University Computer Science 121 Midterm October 23, 2012 Hrvrd University Computer Science 121 Midterm Octoer 23, 2012 This is closed-ook exmintion. You my use ny result from lecture, Sipser, prolem sets, or section, s long s you quote it clerly. The lphet is

More information

Kronecker-Jacobi symbol and Quadratic Reciprocity. Q b /Q p

Kronecker-Jacobi symbol and Quadratic Reciprocity. Q b /Q p Kronecker-Jcoi symol nd Qudrtic Recirocity Let Q e the field of rtionl numers, nd let Q, 0. For ositive rime integer, the Artin symol Q /Q hs the vlue 1 if Q is the slitting field of in Q, 0 if is rmified

More information

Chapter 8.2: The Integral

Chapter 8.2: The Integral Chpter 8.: The Integrl You cn think of Clculus s doule-wide triler. In one width of it lives differentil clculus. In the other hlf lives wht is clled integrl clculus. We hve lredy eplored few rooms in

More information

2.4 Linear Inequalities and Interval Notation

2.4 Linear Inequalities and Interval Notation .4 Liner Inequlities nd Intervl Nottion We wnt to solve equtions tht hve n inequlity symol insted of n equl sign. There re four inequlity symols tht we will look t: Less thn , Less thn or

More information

Finite Automata Theory and Formal Languages TMV027/DIT321 LP4 2018

Finite Automata Theory and Formal Languages TMV027/DIT321 LP4 2018 Finite Automt Theory nd Forml Lnguges TMV027/DIT321 LP4 2018 Lecture 10 An Bove April 23rd 2018 Recp: Regulr Lnguges We cn convert between FA nd RE; Hence both FA nd RE ccept/generte regulr lnguges; More

More information

Homework 4. 0 ε 0. (00) ε 0 ε 0 (00) (11) CS 341: Foundations of Computer Science II Prof. Marvin Nakayama

Homework 4. 0 ε 0. (00) ε 0 ε 0 (00) (11) CS 341: Foundations of Computer Science II Prof. Marvin Nakayama CS 341: Foundtions of Computer Science II Prof. Mrvin Nkym Homework 4 1. UsetheproceduredescriedinLemm1.55toconverttheregulrexpression(((00) (11)) 01) into n NFA. Answer: 0 0 1 1 00 0 0 11 1 1 01 0 1 (00)

More information

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3

I1 = I2 I1 = I2 + I3 I1 + I2 = I3 + I4 I 3 2 The Prllel Circuit Electric Circuits: Figure 2- elow show ttery nd multiple resistors rrnged in prllel. Ech resistor receives portion of the current from the ttery sed on its resistnce. The split is

More information

Tutorial Automata and formal Languages

Tutorial Automata and formal Languages Tutoril Automt nd forml Lnguges Notes for to the tutoril in the summer term 2017 Sestin Küpper, Christine Mik 8. August 2017 1 Introduction: Nottions nd sic Definitions At the eginning of the tutoril we

More information

Finite state automata

Finite state automata Finite stte utomt Lecture 2 Model-Checking Finite-Stte Systems (untimed systems) Finite grhs with lels on edges/nodes set of nodes (sttes) set of edges (trnsitions) set of lels (lhet) Finite Automt, CTL,

More information

Ehrenfeucht-Fraïssé Games: Applications and Complexity. Department of Mathematics and Computer Science University of Udine, Italy ESSLLI 2010 CPH

Ehrenfeucht-Fraïssé Games: Applications and Complexity. Department of Mathematics and Computer Science University of Udine, Italy ESSLLI 2010 CPH Ehrenfeucht-Frïssé Gmes: Applictions nd Complexity Angelo Montnri Nicol Vitcolonn Deprtment of Mthemtics nd Computer Science University of Udine, Itly ESSLLI 2010 CPH Outline Introduction to EF-gmes Inexpressivity

More information

Lecture 3: Equivalence Relations

Lecture 3: Equivalence Relations Mthcmp Crsh Course Instructor: Pdric Brtlett Lecture 3: Equivlence Reltions Week 1 Mthcmp 2014 In our lst three tlks of this clss, we shift the focus of our tlks from proof techniques to proof concepts

More information

Section 6.1 INTRO to LAPLACE TRANSFORMS

Section 6.1 INTRO to LAPLACE TRANSFORMS Section 6. INTRO to LAPLACE TRANSFORMS Key terms: Improper Integrl; diverge, converge A A f(t)dt lim f(t)dt Piecewise Continuous Function; jump discontinuity Function of Exponentil Order Lplce Trnsform

More information

1.9 C 2 inner variations

1.9 C 2 inner variations 46 CHAPTER 1. INDIRECT METHODS 1.9 C 2 inner vritions So fr, we hve restricted ttention to liner vritions. These re vritions of the form vx; ǫ = ux + ǫφx where φ is in some liner perturbtion clss P, for

More information

Torsion in Groups of Integral Triangles

Torsion in Groups of Integral Triangles Advnces in Pure Mthemtics, 01,, 116-10 http://dxdoiorg/1046/pm011015 Pulished Online Jnury 01 (http://wwwscirporg/journl/pm) Torsion in Groups of Integrl Tringles Will Murry Deprtment of Mthemtics nd Sttistics,

More information

MTH 505: Number Theory Spring 2017

MTH 505: Number Theory Spring 2017 MTH 505: Numer Theory Spring 207 Homework 2 Drew Armstrong The Froenius Coin Prolem. Consider the eqution x ` y c where,, c, x, y re nturl numers. We cn think of $ nd $ s two denomintions of coins nd $c

More information

CS 330 Formal Methods and Models

CS 330 Formal Methods and Models CS 330 Forml Methods nd Models Dn Richrds, George Mson University, Spring 2017 Quiz Solutions Quiz 1, Propositionl Logic Dte: Ferury 2 1. Prove ((( p q) q) p) is tutology () (3pts) y truth tle. p q p q

More information

Analytically, vectors will be represented by lowercase bold-face Latin letters, e.g. a, r, q.

Analytically, vectors will be represented by lowercase bold-face Latin letters, e.g. a, r, q. 1.1 Vector Alger 1.1.1 Sclrs A physicl quntity which is completely descried y single rel numer is clled sclr. Physiclly, it is something which hs mgnitude, nd is completely descried y this mgnitude. Exmples

More information

1B40 Practical Skills

1B40 Practical Skills B40 Prcticl Skills Comining uncertinties from severl quntities error propgtion We usully encounter situtions where the result of n experiment is given in terms of two (or more) quntities. We then need

More information

arxiv: v2 [cs.ai] 25 Feb 2016

arxiv: v2 [cs.ai] 25 Feb 2016 Bisimultion nd exressivity for conditionl belief, degrees of belief, nd sfe belief Mikkel Birkegrd Andersen, Thoms Bolnder, Hns vn Ditmrsch, nd Mrtin Holm Jensen rxiv:1506.07990v2 [cs.ai] 25 Feb 2016 Februry

More information

Homework Solution - Set 5 Due: Friday 10/03/08

Homework Solution - Set 5 Due: Friday 10/03/08 CE 96 Introduction to the Theory of Computtion ll 2008 Homework olution - et 5 Due: ridy 10/0/08 1. Textook, Pge 86, Exercise 1.21. () 1 2 Add new strt stte nd finl stte. Mke originl finl stte non-finl.

More information

Myhill-Nerode Theorem

Myhill-Nerode Theorem Overview Myhill-Nerode Theorem Correspondence etween DA s nd MN reltions Cnonicl DA for L Computing cnonicl DFA Myhill-Nerode Theorem Deepk D Souz Deprtment of Computer Science nd Automtion Indin Institute

More information

The area under the graph of f and above the x-axis between a and b is denoted by. f(x) dx. π O

The area under the graph of f and above the x-axis between a and b is denoted by. f(x) dx. π O 1 Section 5. The Definite Integrl Suppose tht function f is continuous nd positive over n intervl [, ]. y = f(x) x The re under the grph of f nd ove the x-xis etween nd is denoted y f(x) dx nd clled the

More information

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations.

Lecture 3. In this lecture, we will discuss algorithms for solving systems of linear equations. Lecture 3 3 Solving liner equtions In this lecture we will discuss lgorithms for solving systems of liner equtions Multiplictive identity Let us restrict ourselves to considering squre mtrices since one

More information

5.4. The Fundamental Theorem of Calculus. 356 Chapter 5: Integration. Mean Value Theorem for Definite Integrals

5.4. The Fundamental Theorem of Calculus. 356 Chapter 5: Integration. Mean Value Theorem for Definite Integrals 56 Chter 5: Integrtion 5.4 The Fundmentl Theorem of Clculus HISTORICA BIOGRAPHY Sir Isc Newton (64 77) In this section we resent the Fundmentl Theorem of Clculus, which is the centrl theorem of integrl

More information

The Maximum Number of Squares in a Tree

The Maximum Number of Squares in a Tree The Mximum Numer of Sures in Tree Mxime Crochemore 1,3, Costs S. Iliooulos 1,4, Tomsz Kociumk 2, Mrcin Kuic 2, Jku Rdoszewski 2, Wojciech Rytter 2,5, Wojciech Tyczy«ski 2, nd Tomsz Wle«2,6 1 Det. of Informtics,

More information

DATABASE DESIGN I - 1DL300

DATABASE DESIGN I - 1DL300 DATABASE DESIGN I - DL300 Fll 00 An introductory course on dtse systems http://www.it.uu.se/edu/course/homepge/dstekn/ht0/ Mnivskn Sesn Uppsl Dtse Lortory Deprtment of Informtion Technology, Uppsl University,

More information

Mrgolius 2 In the rticulr cse of Ploue's constnt, we tke = 2= 5+i= 5, nd = ;1, then ; C = tn;1 1 2 = ln(2= 5+i= 5) ln(;1) More generlly, we would hve

Mrgolius 2 In the rticulr cse of Ploue's constnt, we tke = 2= 5+i= 5, nd = ;1, then ; C = tn;1 1 2 = ln(2= 5+i= 5) ln(;1) More generlly, we would hve Ploue's Constnt is Trnscendentl Brr H. Mrgolius Clevelnd Stte University Clevelnd, Ohio 44115.mrgolius@csuohio.edu Astrct Ploue's constnt tn;1 ( 1 2) is trnscendentl. We rove this nd more generl result

More information

Lecture 3: Dealing with Non-Compliance

Lecture 3: Dealing with Non-Compliance Comlince Roustness Power References Socil Lws for Multi-Agent Systems: Logic nd Gmes Lecture 3: Deling with Non-Comlince Thoms Ågotnes 1 1 Dertment of Informtion Science nd Medi Studies University of Bergen,

More information

The practical version

The practical version Roerto s Notes on Integrl Clculus Chpter 4: Definite integrls nd the FTC Section 7 The Fundmentl Theorem of Clculus: The prcticl version Wht you need to know lredy: The theoreticl version of the FTC. Wht

More information

AUTOMATED REASONING. Agostino Dovier. Udine, November Università di Udine CLPLAB

AUTOMATED REASONING. Agostino Dovier. Udine, November Università di Udine CLPLAB AUTOMATED REASONING Agostino Dovier Università di Udine CLPLAB Udine, Novemer 2017 AGOSTINO DOVIER (CLPLAB) AUTOMATED REASONING UDINE, NOVEMBER 2017 1 / 15 Semntics of Logic Progrms AGOSTINO DOVIER (CLPLAB)

More information

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS.

THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS. THE EXISTENCE-UNIQUENESS THEOREM FOR FIRST-ORDER DIFFERENTIAL EQUATIONS RADON ROSBOROUGH https://intuitiveexplntionscom/picrd-lindelof-theorem/ This document is proof of the existence-uniqueness theorem

More information

LECTURE 10: JACOBI SYMBOL

LECTURE 10: JACOBI SYMBOL LECTURE 0: JACOBI SYMBOL The Jcobi symbol We wish to generlise the Legendre symbol to ccomodte comosite moduli Definition Let be n odd ositive integer, nd suose tht s, where the i re rime numbers not necessrily

More information

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique?

How do we solve these things, especially when they get complicated? How do we know when a system has a solution, and when is it unique? XII. LINEAR ALGEBRA: SOLVING SYSTEMS OF EQUATIONS Tody we re going to tlk out solving systems of liner equtions. These re prolems tht give couple of equtions with couple of unknowns, like: 6= x + x 7=

More information

Lecture 6: Isometry. Table of contents

Lecture 6: Isometry. Table of contents Mth 348 Fll 017 Lecture 6: Isometry Disclimer. As we hve textook, this lecture note is for guidnce nd sulement only. It should not e relied on when rering for exms. In this lecture we nish the reliminry

More information

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-2700: Digital Logic Design Fall Notes - Unit 1

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-2700: Digital Logic Design Fall Notes - Unit 1 INTRODUTION TO LOGI IRUITS Notes - Unit 1 OOLEN LGER This is the oundtion or designing nd nlyzing digitl systems. It dels with the cse where vriles ssume only one o two vlues: TRUE (usully represented

More information

Triangles The following examples explore aspects of triangles:

Triangles The following examples explore aspects of triangles: Tringles The following exmples explore spects of tringles: xmple 1: ltitude of right ngled tringle + xmple : tringle ltitude of the symmetricl ltitude of n isosceles x x - 4 +x xmple 3: ltitude of the

More information

Compiler Design. Fall Lexical Analysis. Sample Exercises and Solutions. Prof. Pedro C. Diniz

Compiler Design. Fall Lexical Analysis. Sample Exercises and Solutions. Prof. Pedro C. Diniz University of Southern Cliforni Computer Science Deprtment Compiler Design Fll Lexicl Anlysis Smple Exercises nd Solutions Prof. Pedro C. Diniz USC / Informtion Sciences Institute 4676 Admirlty Wy, Suite

More information

DFA minimisation using the Myhill-Nerode theorem

DFA minimisation using the Myhill-Nerode theorem DFA minimistion using the Myhill-Nerode theorem Johnn Högerg Lrs Lrsson Astrct The Myhill-Nerode theorem is n importnt chrcteristion of regulr lnguges, nd it lso hs mny prcticl implictions. In this chpter,

More information

Intermediate Math Circles Wednesday, November 14, 2018 Finite Automata II. Nickolas Rollick a b b. a b 4

Intermediate Math Circles Wednesday, November 14, 2018 Finite Automata II. Nickolas Rollick a b b. a b 4 Intermedite Mth Circles Wednesdy, Novemer 14, 2018 Finite Automt II Nickols Rollick nrollick@uwterloo.c Regulr Lnguges Lst time, we were introduced to the ide of DFA (deterministic finite utomton), one

More information

More on automata. Michael George. March 24 April 7, 2014

More on automata. Michael George. March 24 April 7, 2014 More on utomt Michel George Mrch 24 April 7, 2014 1 Automt constructions Now tht we hve forml model of mchine, it is useful to mke some generl constructions. 1.1 DFA Union / Product construction Suppose

More information

Linear Inequalities. Work Sheet 1

Linear Inequalities. Work Sheet 1 Work Sheet 1 Liner Inequlities Rent--Hep, cr rentl compny,chrges $ 15 per week plus $ 0.0 per mile to rent one of their crs. Suppose you re limited y how much money you cn spend for the week : You cn spend

More information

AUTOMATA AND LANGUAGES. Definition 1.5: Finite Automaton

AUTOMATA AND LANGUAGES. Definition 1.5: Finite Automaton 25. Finite Automt AUTOMATA AND LANGUAGES A system of computtion tht only hs finite numer of possile sttes cn e modeled using finite utomton A finite utomton is often illustrted s stte digrm d d d. d q

More information

Continuous Random Variables Class 5, Jeremy Orloff and Jonathan Bloom

Continuous Random Variables Class 5, Jeremy Orloff and Jonathan Bloom Lerning Gols Continuous Rndom Vriles Clss 5, 8.05 Jeremy Orloff nd Jonthn Bloom. Know the definition of continuous rndom vrile. 2. Know the definition of the proility density function (pdf) nd cumultive

More information

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-378: Computer Hardware Design Winter Notes - Unit 1

ELECTRICAL AND COMPUTER ENGINEERING DEPARTMENT, OAKLAND UNIVERSITY ECE-378: Computer Hardware Design Winter Notes - Unit 1 ELETRIL ND OMPUTER ENGINEERING DEPRTMENT, OKLND UNIVERSIT EE-78: omputer Hrdwre Design Winter 016 INTRODUTION TO LOGI IRUITS Notes - Unit 1 OOLEN LGER This is the oundtion or designing nd nlyzing digitl

More information

5. (±±) Λ = fw j w is string of even lengthg [ 00 = f11,00g 7. (11 [ 00)± Λ = fw j w egins with either 11 or 00g 8. (0 [ ffl)1 Λ = 01 Λ [ 1 Λ 9.

5. (±±) Λ = fw j w is string of even lengthg [ 00 = f11,00g 7. (11 [ 00)± Λ = fw j w egins with either 11 or 00g 8. (0 [ ffl)1 Λ = 01 Λ [ 1 Λ 9. Regulr Expressions, Pumping Lemm, Right Liner Grmmrs Ling 106 Mrch 25, 2002 1 Regulr Expressions A regulr expression descries or genertes lnguge: it is kind of shorthnd for listing the memers of lnguge.

More information

A study of Pythagoras Theorem

A study of Pythagoras Theorem CHAPTER 19 A study of Pythgors Theorem Reson is immortl, ll else mortl. Pythgors, Diogenes Lertius (Lives of Eminent Philosophers) Pythgors Theorem is proly the est-known mthemticl theorem. Even most nonmthemticins

More information

Designing Information Devices and Systems I Spring 2018 Homework 7

Designing Information Devices and Systems I Spring 2018 Homework 7 EECS 16A Designing Informtion Devices nd Systems I Spring 2018 omework 7 This homework is due Mrch 12, 2018, t 23:59. Self-grdes re due Mrch 15, 2018, t 23:59. Sumission Formt Your homework sumission should

More information

Parallel Projection Theorem (Midpoint Connector Theorem):

Parallel Projection Theorem (Midpoint Connector Theorem): rllel rojection Theorem (Midpoint onnector Theorem): The segment joining the midpoints of two sides of tringle is prllel to the third side nd hs length one-hlf the third side. onversely, If line isects

More information