s the set of onsequenes. Skeptil onsequenes re more roust in the sense tht they hold in ll possile relities desried y defult theory. All its desirle p

Size: px
Start display at page:

Download "s the set of onsequenes. Skeptil onsequenes re more roust in the sense tht they hold in ll possile relities desried y defult theory. All its desirle p"

Transcription

1 Skeptil Rtionl Extensions Artur Mikitiuk nd Miros lw Truszzynski University of Kentuky, Deprtment of Computer Siene, Lexington, KY 40506{0046, frtur Astrt. In this pper we propose version of defult logi with the following two properties (1) defults with mutully inonsistent justi- tions re never used together in onstruting set of defult onsequenes of theory (2) the resoning formlized y our logi is relted to the trditionl skeptil mode of defult resoning. Our logi is sed on the onept of skeptil rtionl extension. We give hrteriztion results for skeptil rtionl extensions nd n lgorithm to ompute them. We present some omplexity results. Our min gol is to hrterize ses when the lss of skeptil rtionl extensions is losed under intersetion. In the se of norml defult theories our logi oinides with the stndrd skeptil resoning with extensions. In the se of seminorml defult theories our formlism provides desription of the stndrd skeptil resoning with rtionl extensions. 1 Introdution In this pper we investigte version of defult logi with the following two min properties. First, defults with mutully inonsistent justitions re never used together in onstruting set of defult onsequenes of theory. This hs implitions for the dequy of our system to hndle situtions with disjuntive informtion. Seond, the resoning formlized y our logi is losely relted to the trditionl skeptil mode of defult resoning. In the se of norml defult theories it oinides with the stndrd skeptil resoning with extensions. In the se of seminorml defult theories our formlism provides desription of the stndrd skeptil resoning with rtionl extensions. Our logi is dened y mens of xpoint onstrution nd not s the intersetion of extensions, s is usully the se with the skeptil resoning. Hene, our results provide xpoint desription of the stndrd skeptil resoning from norml defult theories nd, in the se of rtionl extensions, from seminorml defult theories. Defult logi, introdued y Reiter [10], is one of the most extensively studied nonmonotoni systems. Severl reent reserh monogrphs oer omprehensive presenttion of theoretil nd prtil spets of defult logi [1, 3, 6]. Defult logi ssigns to defult theory olletion of theories lled extensions. Extensions model ll possile relities" desried y defult theory nd re used s the sis for two modes of resoning rve nd skeptil. In the rve mode, n ritrrily seleted extension denes the set of onsequenes for defult theory. In the skeptil one, the intersetion of ll extensions serves

2 s the set of onsequenes. Skeptil onsequenes re more roust in the sense tht they hold in ll possile relities desried y defult theory. All its desirle properties notwithstnding, there re situtions where defult logi of Reiter is not esily pplile. In prtiulr, defult logi does not hndle well inomplete informtion given in the form of disjuntive luses [9, 2, 4, 7]. To remedy this, severl moditions of defult logi were proposed disjuntive defult logi [4], umultive defult logi [2], onstrined defult logi [11] nd rtionl defult logi [7]. The rst system introdues new disjuntion opertor to hndle "eetive" disjuntion. The ltter three tke into ount, in one wy or nother, the requirement tht defults with mutully inonsistent justitions must not e used in the onstrution of the sme extension. Not surprisingly then, they re somewht relted. Connetions etween umultive defult logi nd onstrined defult logi re studied in [11]. Reltions etween onstrined defult logi nd rtionl defult logi re disussed in [8]. In this pper we ontinue our investigtion of rtionl defult logi introdued in [7]. The key ide ehind the onept of rtionl extension of defult theory (D W ) is tht of mximl set of defults in D tive with respet to theories W nd S. The olletion of ll suh sets (it is lwys nonempty) is denoted y MA(D W S). Intuitively, it ontins every group of defults the resoner n selet to justify tht S is rtionl extension of (D W ) (if none works, S is not rtionl extension). Tht is, S is rtionl extension if S n e derived from W y mens of some set of defults A 2 MA(D W S). In this pper, we strengthen the requirements for hypothetil ontext S to e rtionl extension. As result we otin new xpoint onstrution nd new lss of extensions skeptil rtionl extensions. (The word "extension" is eing used here in roder sense. A rtionl or skeptil rtionl extension of defult theory is not, in generl, n extension of the theory in Reiter's sense see Exmples 1 nd 2.) Speilly, for theory S to e skeptil rtionl extension, S must e extly the set of formuls tht n e derived from W y mens of every set of defults A 2 MA(D W S). In other words, S onsists of those formuls the resoner n justify no mtter whih element from MA(D W S) is seleted for resoning. This motivtes the term skeptil used to designte these extensions. The lss of skeptil rtionl extensions hs severl desirle properties. For mny defult theories, it ontins lest element with respet to inlusion. In suh se, this lest skeptil rtionl extension n e used s forml model of skeptil defult resoning (sometimes identil with nd sometimes dierent from the trditionl model of skeptil defult resoning). In this pper we investigte properties of skeptil rtionl extensions. We restrit ourselves to the propositionl se only. We give hrteriztion results for skeptil rtionl extensions nd n lgorithm to ompute them. We present some omplexity results. Our min gol is to hrterize ses when the lss of skeptil rtionl extensions is losed under intersetion. We otin the strongest results for norml nd seminorml defult theories. We show tht the intersetion of ll rtionl extensions of seminorml defult theory is its lest skeptil rtionl extension. In prtiulr, it mens tht the intersetion of ll extensions

3 of norml defult theory is, in ft, its lest skeptil rtionl extension. 2 Denitions nd Exmples Let L e lnguge of propositionl logi. A defult is ny expression of the form M 1 M k where, i, 1 i k nd re propositionl formuls from L. The formul is lled the prerequisite of d, p(d) in symols. The formuls i, 1 i k, re lled the justitions of d. The set of justitions is denoted y j(d). Finlly, the formul is lled the onsequent of d nd is denoted (d). For olletion D of defults y p(d), j(d) nd (D) we denote, respetively, the sets of ll prerequisites, justitions nd onsequents of the defults in D. A defult of the form M ( M(^), resp.) is lled norml (seminorml, resp.). A defult theory is pir (D W ), where D is set of defults nd W is set of propositionl formuls. A defult theory (D W ) is norml (seminorml, resp.) if ll defults in D re norml (seminorml, resp.). A defult theory (D W ) is nite if oth D nd W re nite. For set D of defults nd for propositionl theory S, we dene nd D S = M 1 M k 2 D nd S 6` i 1 i k Mon(D) = p(d) (d) d 2 D Given set of inferene rules A, y Cn A () we men the onsequene opertor of the forml proof system onsisting of propositionl lulus nd the rules in A (it is dened for ll theories in the lnguge). The key notion of (stndrd) defult logi is the notion of n extension 1. A theory S is n extension for defult theory (D W ) if S = Cn DS (W ). For detiled presenttion of defult logi the reder is referred to [6]. In [7] we introdued the notions of n tive set of defults nd rtionl extension of defult theory. A set A of defults is tive with respet to sets of formuls W nd S if it stises the following onditions AS1 j(a) =, or j(a) [ S is onsistent, AS2 p(a) Cn AS (W ). The set of ll susets of set of defults D whih re tive with respet to W nd S will e denoted y A(D W S). Oserve, tht is tive with respet to every W nd S. Hene, A(D W S) is lwys nonempty. By the Kurtowski-Zorn Lemm, every A 2 A(D W S) is 1 Our denition is dierent from ut equivlent to the originl denition of Reiter [10].

4 ontined in mximl (with respet to inlusion) element of A(D W S) (see [7]). Dene MA(D W S) to e the set of ll mximl elements in A(D W S). In [7], we dened S to e rtionl extension for defult theory (D W ) if S = Cn AS (W ) for some A 2 MA(D W S). We will now dene the notion of skeptil rtionl extension. Denition 1. A theory S is skeptil rtionl extension for defult theory (D W ) if S = Cn AS (W ) 2 A2MA(DWS) We will illustrte the notions dened ove with severl exmples. The rst exmple exhiits defult theory whih does not hve n extension or rtionl extension ut hs skeptil rtionl extension. In ll exmples,, nd d stnd for distint propositionl toms. Exmple 1. Let D = f M g. The defult theory (D ) hs no extension nd no rtionl extension. On the other hnd, S = Cn(f _ g) is its skeptil rtionl extension. Indeed, we hve nd M MA(D S) = M M A2MA(DS) The defult theory (f M g ) is lssil exmple of theory without extensions. More generlly, defult theory ontining the defult M, where Cn AS () = Cn(fg) Cn(fg) = Cn(f _ g) = S is n tom tht does not pper in ny other defult or formul, does not hve n extension. Hene, the ft tht Cn(f _ g) is skeptil rtionl extension of the defult theory of Exmple 1 my seem ounterintuitive. However, the mening of the defults in D is if (, resp.) is possile, then onlude (, resp.). In the ontext of Cn(f _ g), ny of the two defults n re (ut not together). Hene, no mtter wht is the hoie, _ follows. The next exmple shows tht there re lso defult theories whih hve extensions ut do not hve skeptil rtionl extensions. Exmple 2. Let us onsider the defult theory (D W ), where W = f _ g nd D = M M d M( _ d) ^ d This theory hs unique extension Cn(f_ dg). We proved in [7] tht (D W ) does not hve rtionl extensions. Assume tht S is skeptil rtionl extension for (D W ). Then _ 2 S. If ^ d =2 S then M MA(D W S) = M( _ d) ^ d M d M( _ d) ^ d 2

5 T Thus, A2MA(DWS) (W ) = L nd S 6= L (euse ^d 62 S). So, ssume CnAS tht ^ d 2 S. Then MA(D W S) = M M d nd T A2MA(DWS) CnAS (W ) = Cn(f dg) 6= S (euse ^d =2 Cn(f dg)). Hene, (D W ) does not hve skeptil rtionl extensions. 2 One of the properties we re espeilly interested in here is losure under intersetion of the fmily of skeptil rtionl extensions. The following exmple presents defult theory for whih the fmily of skeptil rtionl extensions is losed under intersetion. This theory is norml. We will lter show tht this property holds for every norml defult theory with nite numer of extensions. Exmple 3. Let W = nd M D = M M Let S 1 = Cn(f g), S 2 = Cn(f g) nd S = S 1 S 2 = Cn(fg). Then MA(D W S 1 ) = M nd M M MA(D W S 2 ) = M M M MA(D W S) = M M Clerly, S 1 nd S 2 re extensions, rtionl extensions nd skeptil rtionl extensions for (D W ) nd S is lso skeptil rtionl extension for (D W ). 2 For some defult theories the fmily of their skeptil rtionl extensions is not losed under nite intersetion. Exmple 4. Let W = nd M Md D = M( _ ) Md ^ Md M Let S 1 = Cn(fg), S 2 = Cn(fg) nd S = S 1 S 2 = Cn(f _ g). Then MA(D W S 1 ) = M Md M Md MA(D W S 2 ) = M( _ ) Md ^ M( _ ) Md ^ Md M nd MA(D W S) = MA(D W S 2 ). It is esy to see tht S 1 nd S 2 re skeptil rtionl extensions for (D W ) while S is not. This defult theory does not hve lest skeptil rtionl extension. Let us note tht S 1 nd S 2 re lso rtionl extensions for (D W ). Let S 3 = Cn(f g). We hve MA(D W S 3 ) = MA(D W S 1 ). Hene, S 3 is lso rtionl extension of (D W ). Finlly, it is esy to see tht S 3 is the only (Reiter's) extension for (D W ). 2

6 We onlude this setion with n lterntive hrteriztion of tive sets. Proposition 2. A set A of defults is tive with respet to sets of formuls W nd S if nd only if it stises AS1 nd the following ondition AS2 0 p(a) Cn Mon(A) (W ). 2 3 Generl Properties In this setion we present some results (Theorems 8 nd 9, Corollry 10) providing suient onditions for the intersetion of skeptil rtionl extensions to e skeptil rtionl extension too. These results will e used in Setions 5 nd 6. We strt with severl uxiliry oservtions. (Simple proofs of Lemms 3, 4 nd 6 re omitted due to spe restrition.) Lemm 3. Let (D W ) e defult theory. Let S e set of formuls nd let A 2 A(D W S). Then A 2 A(D W T ) for every theory T suh tht A stises AS1 for T. 2 Lemm 4. Let (D W ) e defult theory. Let S nd T e theories suh tht S T. If A 2 MA(D W S) nd A 2 A(D W T ), then A 2 MA(D W T ). 2 Lemm 5. Let (D W ) e defult theory nd let S = T k i=1 S i (k 1), where eh theory S i is losed under propositionl provility. Then MA(D W S) S k i=1 MA(D W S i ). Proof. Let A 2 MA(D W S). Then A stises AS1 for S. Thus, j(a) = or j(a) [ S is onsistent. If j(a) = then for every i (1 i k), A stises AS1 for S i. Let us ssume now tht j(a) [ S is onsistent. We hve We will show tht Cn(j(A) [ S) = Cn(j(A) [ Cn( k i=1 k i=1 (j(a) [ S i )) = S i ) = Cn( k i=1 k i=1 (j(a) [ S i )) (1) Cn(j(A) [ S i ) (2) Clerly, the left-hnd side of (2) is ontined in the right-hnd T side. So, we need k to prove only the onverse inlusion. Consider formul ' 2 Cn(j(A)[S i=1 i). For every i (1 i k), ' is provle from j(a) [ S i. By the Comptness Theorem, for every i, there is nite suset S 0 i of S i suh tht ' is provle from j(a) [ S 0 i. Let ' i e the onjuntion of ll formuls from S 0 i (1 i k). Then ' is provle from j(a) [ f' i g. Sine S i is losed under propositionl onsequenes, T ' i 2 S i. Consequently, T T k ' 1 ' k 2 S i=1 i. Let T v e vlution k stisfying (j(a) [ S k i=1 i). Sine (j(a) [ S k i=1 i) = j(a) [ S i=1 i, it follows

7 tht v stises j(a) nd v stises ' 1 ' k. Hene, v stises j(a) [ f' i g for some T i (1 i k). Sine ' is provle from j(a) [ f' i g, v stises '. Thus, k ' 2 Cn( (j(a) [ S i=1 i)). It follows from (1) nd (2) tht if j(a) [ S is onsistent then for some i (1 i k) j(a) [ S i is onsistent. Hene, in oth ses (j(a) =, or j(a) [ S is onsistent) A stises AS1 for some S i (1 i k). By Lemm 3, A 2 A(D W S i ) for some i (1 i k). Sine S S i, then y Lemm 4, A 2 MA(D W S i ) for some i (1 i k) nd we re done. 2 We will denote y GD(D S) the set of generting defults from D with respet to S, tht is, GD(D S) = M1 M k 2 D S ` nd S 6` i 1 i k Lemm 6. Let theory S e n extension of defult theory (D W ) nd let A 2 A(D W S). Then A GD(D S). In prtiulr, if GD(D S) 2 A(D W S) then MA(D W S) = fgd(d S)g. 2 Exmple 4 indites tht the notions of n extension, rtionl extension nd skeptil rtionl extension re, in generl, dierent. However, under some onditions they oinide. One suh sitution is desried in our rst theorem (the proof is omitted due to spe restrition). Theorem 7. Let (D W ) e defult theory nd let S e propositionl theory suh tht MA(D W S) = fgd(d S)g. Then S is n extension of (D W ) if nd only if S is rtionl extension of (D W ) if nd only if S is skeptil rtionl extension of (D W ). 2 The next severl results desrie onditions whih gurntee tht the intersetion of skeptil rtionl extensions is lso skeptil rtionl extension. Theorem 8. Let fs i i 2 Ig e set of skeptil rtionl extensions for defult theory (D W ), let S = T i2i S i nd MA(D W S) = S i2i MA(D W S i ). Then S is skeptil rtionl extension for (D W ). Proof. We hve i2i A2MA(DWS) Cn AS (W ) = A2MA(DWS i) Cn Mon(A) (W ) = i2i A2MA(DWS) A2MA(DWS i) Cn Mon(A) (W ) = Cn AS i (W ) = S i = S Theorem 9. Let fs i i 2 Ig e set of extensions for defult theory (D W ) suh tht for every i 2 I, MA(D W S i ) = fgd(d S i )g. Let S = T i2i S i nd MA(D W S) S i2i MA(D W S i ). Then S is skeptil rtionl extension for (D W ). i2i 2

8 Proof. Every S i is skeptil rtionl extension for (D W ) (Theorem 7). By Theorem 8, to prove the ssertion it sues to show tht S i2i MA(D W S i ) MA(D W S). Let A 2 MA(D W S i ) for some i 2 I. Hene, A = GD(D S i ). Sine S S i, A stises AS1 for S. By Lemm 3, A 2 A(D W S). There is B 2 MA(D W S) suh tht A B. Aording to the ssumption, B 2 MA(D W S j ) for some j 2 I, tht is, B = GD(D S j ). Sine A = GD(D S i ), we hve GD(D S i ) GD(D S j ). Thus, Cn(W [ (GD(D S i ))) Cn(W [ (GD(D S j ))). By Theorem 3.57 in [6], we hve S i = Cn(W [(GD(D S i ))) nd S j = Cn(W [ (GD(D S j ))), so we get S i S j. Sine S i nd S j re extensions of the sme defult theory, S i = S j nd A = B. Hene, A 2 MA(D W S). 2 Lemm 5 nd Theorem 9 imply the following orollry. Corollry 10. Let S 1 S k (k 1) e extensions of defult theory (D W ) suh tht for every i (1 i k), MA(D W S i ) = fgd(d S i )g. Then S = T k i=1 S i is skeptil rtionl extension for (D W ). 2 Oserve tht even though in Theorem 9 nd Corollry 10 we ssume tht sets S i re extensions, y Theorem 7 every S i is lso rtionl extension nd skeptil rtionl extension for (D W ). 4 Algorithmi Issues Proposition 11. Let S e skeptil rtionl extension for defult theory (D W ) suh tht D is nite. Then S = Cn(W [ f' 1 ' k g), where every ' i = V (A i ) for some A i 2 MA(D W S). Proof. Sine D is nite, MA(D W S) is nite, s well. Let us ssume tht MA(D W S) = fa 1 A k g. For eh A i 2 MA(D W S) dene ' i = V (A i ) (sine eh A i is nite, ' i is well-dened). Sine A i 2 A(D W S), Cn (Ai)S (W ) = Cn(W [ (A i )) = Cn(W [ f' i g). Hene, S = k i=1 Cn (Ai)S (W ) = k i=1 Cn(W [ f' i g) = Cn(W [ f' 1 ' k g) 2 If (D W ) is nite then the numer of sets of the form Cn(W [ f' 1 ' k g), where every ' i is of the form V (A) for some A D, is lso nite. For every suh set S, one n ompute MA(D W S) nd hek whether S = T A2MA(DWS) CnAS (W ). Thus, we hve the following lgorithm for omputing skeptil rtionl extensions. 1. For every A D, ompute ' A = V (A) (' = >). Let = f' A A Dg. 2. For every () ompute = W, () for every A D, verify whether A 2 MA(D W W [ f g), () ompute ' = W A2MA(DWW[f g) ' A,

9 (d) hek whether W [f'g ` nd W [f g ` ' if so, output Cn(W [f g) s skeptil rtionl extension for (D W ). The following exmple shows tht there re defult theories (D W ) nd sets S suh tht the size of MA(D W S) is exponentil in the size of D. It follows tht n lgorithm for verifying whether S is skeptil rtionl extension of (D W ) must hve in the worst se n exponentil omplexity. Exmple 5. Let us onsider the defult theory (D W ) where Mp1 D = Mp 1 Mp n Mp n p 1 p 1 p n p 1 p n re distint propositionl toms nd W =. Then MA(D W Cn()) hs 2 n elements, eh of them otined y seleting extly one defult from eh pir Mpi p i Mpi p i. 2 The omplexity of resoning with skeptil rtionl extensions in the generl se remins n open prolem. p n 5 Seminorml Defult Theories In this setion we study skeptil rtionl extensions of seminorml defult theories. We show tht every seminorml defult theory hs lest skeptil rtionl extension nd tht it oinides with the intersetion of ll rtionl extensions. Our rst min result of this setion shows tht every skeptil rtionl extension of seminorml defult theory n e represented s the intersetion of ertin numer (possily innitely mny) of rtionl extensions. Theorem 12. For every skeptil rtionl extension S of seminorml defult theory (D W ) there is set fs i i 2 Ig of rtionl extensions for (D W ) suh tht S = T i2i S i. Proof. Let S e skeptil rtionl extension for (D W ). Consequently, we hve S = T A2MA(DWS) CnAS (W ). Let MA(D W S) = fa i i 2 Ig nd let us denote S i = Cn (Ai)S (W ) (i 2 I). Then S = T i2i S i. We will show tht eh S i is rtionl extension for (D W ). Sine A i 2 MA(D W S), A i stises AS1 for S. Hene, j(a i ) = or j(a i ) [ S is onsistent. If j(a i ) = then A i stises AS1 for S i. If j(a i ) [ S is onsistent then, sine W S, j(a i ) [ W is onsistent. Sine ll defults in A i re seminorml, j(a i ) implies (A i ). It follows tht j(a i ) [ (A i ) [ W is onsistent. Sine A i 2 MA(D W S), Cn (Ai)S (W ) = Cn(W [ (A i )). Hene, S i = Cn(W [ (A i )). It follows tht j(a i ) [ S i is onsistent. Consequently, A i stises AS1 for S i. Thus, in oth ses (j(a i ) =, or j(a i ) [ S is onsistent) A i stises AS1 for S i. By Lemm 3, A i 2 A(D W S i ). Sine S S i, then y Lemm 4, A i 2 MA(D W S i ). It follows tht (A i ) Si = Mon(A i ) = (A i ) S. Sine

10 S i = Cn (Ai)S (W ), we hve S i = Cn (Ai)S i (W ). Hene, S i is rtionl extension of (D W ). 2 In [6] tehnique for onstruting n extension of defult theory from n ordering of defults ws presented nd thoroughly studied. In [7] we dpted this tehnique to the se of rtionl extensions. We will use some properties of this onstrution in the proof of the seond min result of this setion. The reder is referred to [6, 7] for detils. We ssume tht the set of the toms of our lnguge L is denumerle. Consequently, the set of ll defults over the lnguge L is denumerle. Let (D W ) e defult theory nd well-ordering of D. We dene n ordinl. For every ordinl < we dene set of defults AD nd defult d. We lso dene set of defults AD. We proeed s follows If the sets AD, <, hve een dened ut hs not een dened then 1. If there is no defult d 2 D n S < AD suh tht () j(d) = or W [ ( S < AD ) [ j( S < AD ) [ j(d) is onsistent, nd () W [ ( S < AD ) ` p(d), then =. 2. Otherwise, dene d to e the -lest defult d 2 D n S < AD suh tht the onditions () nd () ove hold. Then set AD = S < AD [ fd g. When the onstrution termintes, put AD = S < AD. The theory Cn(W [ (AD)) will e lled generted y the well-ordering. We will need the following property of this onstrution. Theorem 13. (extended version of [7]) Let (D W ) e seminorml defult theory nd let e well-ordering of D. Then T = Cn(W [ (AD)) is rtionl extension for (D W ). Moreover, AD 2 MA(D W T). 2 It follows from this theorem tht every seminorml defult theory hs rtionl extension. In the proof of our next result we will lso need the following proposition. Proposition 14. (extended version of [7]) Let (D W ) e defult theory nd let S nd T e rtionl extensions of (D W ) suh tht S = Cn AS (W ) for some A 2 MA(D W S), T = Cn BT (W ) for some B 2 MA(D W T ) nd A B. Then A = B nd S = T. 2 Now we re redy to present the seond min result of this setion. Theorem 15. The intersetion of ll rtionl extensions of seminorml defult theory is the lest skeptil rtionl extension for this theory. Proof. Let fs i i 2 Ig e the set of ll rtionl extensions of seminorml defult theory (D W ) nd let S = T i2i S i. By Theorem 12, we need only to prove tht S is skeptil rtionl extension for (D W ). Let A 2 MA(D W S). Let us onsider ny well-ordering of D in whih the defults in A preede ll other defults. Assume lso tht the defults of A

11 re ordered y ording to the order in whih their orresponding monotoni inferene rules re pplied in the proess of omputing Cn AS (W ). It is esy to see tht A AD. Sine the theory (D W ) is seminorml, the theory generted y, Cn(W [ (AD)), is rtionl extension for (D W ) (Theorem 13), tht is, Cn(W [ (AD)) = S i for some i 2 I. Moreover, 2 MA(D W S i ). AD stises AS1 for S i. Hene, j(ad) = or j(ad) [ S i is onsistent. If j(ad) = then = (every defult in D hs justition). Sine A AD =, A = AD. If j(ad) [ S i is onsistent then, sine S S i, j(ad) [ S is onsistent. By Lemm 3, AD 2 A(D W S). By the mximlity of A, we get A = AD. Hene, in oth ses (j(ad) =, or j(ad) [ S i is onsistent) A S = AD, tht is, A 2 MA(D W S i ) for some i 2 I. Thus, MA(D W S) i2i MA(D W S i ). Moreover, we proved tht for every A 2 MA(D W S) there is i 2 I suh tht Cn AS (W ) = Cn(W [ (A)) = S i nd A 2 MA(D W S i ) (3) Thus, Cn AS (W ) = A2MA(DWS) i2i 0 S i for some I 0 I. We will show tht I 0 = I, tht is, tht for every i 2 I, there is B 2 MA(D W S) suh tht S i = Cn BS (W ). Sine S i is rtionl extension for (D W ), there is B 2 MA(D W S i ) suh tht S i = Cn BS i (W ). Sine S S i, then y Lemm 3, B 2 A(D W S). Hene, there is C 2 MA(D W S) suh tht B C. By (3), there is j 2 I suh tht C 2 MA(D W S j ) nd Cn CS (W ) = S j. It is esy to see tht C Sj = Mon(C) = C S. Hene, S j = Cn CS j (W ). By Proposition 14, B = C, tht is, B 2 MA(D W S). Moreover, B S = Mon(B) = B Si. Thus, S i = Cn BS i (W ) = Cn BS (W ). Hene, we hve shown tht I 0 = I, tht is, T A2MA(DWS) CnAS (W ) = S. Thus, S is skeptil rtionl extension for (D W ). 2 Corollry 16. Every seminorml defult theory hs skeptil rtionl extension. 2 Exmple 2 shows tht Corollry 16 is not true for generl defult theories. Theorem 15 shows tht the intersetion of ll rtionl extensions is skeptil rtionl extension. This is not true for n ritrry fmily of rtionl extensions of seminorml defult theory, even if the theory is nite (f. Theorem 20). Exmple 6. Let M( ^ ) D = M( ^ ) M( ^ ) The defult theory (D ) is lssil exmple of seminorml defult theory without extensions. This theory hs three rtionl extensions S 1 = Cn(fg), S 2 = Cn(fg) nd S 3 = Cn(fg). Aording to Theorem 15, their intersetion S = S 1 S 2 S 3 = Cn(f g) is skeptil rtionl extension for (D ).

12 However, the intersetions of ny two rtionl extensions, S 12 = S 1 S 2 = Cn(f _ g), S 13 = S 1 S 3 = Cn(f _ g) nd S 23 = S 2 S 3 = Cn(f _ g), re not skeptil rtionl extensions. Indeed, it is esy to see tht for ny i j (1 i < j 3), MA(D S ij ) = M( ^ ) Hene, A2MA(DS ij) M( ^ ) M( ^ ) Cn AS ij () = Cn(f g) = S 6= Sij Let us lso oserve tht none of S 1, S 2, S 3 is skeptil rtionl extension. 2 Theorem 15 implies the following orollry. Corollry 17. A formul ' elongs to ll skeptil rtionl extensions of seminorml defult theory (D W ) if nd only if ' elongs to ll rtionl extensions of (D W ). 2 The omplexity of resoning with rtionl extensions ws studied in [7]. In prtiulr, we proved tht the prolem of deiding whether formul elongs to ll rtionl extensions of nite defult theory is P 2 -omplete. It remins P 2 -omplete even under the restrition to the lss of norml defult theories. Sine every norml defult theory is seminorml, we otin the following result. Corollry 18. The prolem IN-ALL Given nite seminorml defult theory (D W ) nd formul ', deide if ' is in ll skeptil rtionl extensions of (D W ), is P 2 -omplete. 2 The omplexity of the prolem of deiding whether formul elongs to t lest one skeptil rtionl extension of seminorml defult theory remins open. The rgument we used for the prolem IN-ALL does not work here. 6 Norml Defult Theories The results otined in the previous setion for seminorml defult theories lerly extend to the se of norml defult theories. In this se, however, we n still strengthen some of them. We strt this setion with simple proposition. Proposition 19. Let S e n extension of norml defult theory (D W ). Then MA(D W S) = fgd(d S)g. Proof. If S is inonsistent then MA(D W S) = fg nd GD(D S) =, so the ssertion holds. Assume now tht S is onsistent. Aording to Lemm 6, it is suient to prove tht GD(D S) 2 A(D W S) nd this ft is proven in the proof of Theorem 3.1 in [7]. 2

13 The min result of this setion shows tht nite intersetions of extensions (or rtionl extensions - for norml defult theories these notions oinide, see [7]) re skeptil rtionl extensions. In prtiulr, (rtionl) extensions re lso skeptil rtionl extensions for norml defult theories (unlike in the se of seminorml ones). Theorem 20. Let (D W ) e norml defult theory. 1. Let S 1,,S k (k 1) e extensions of (D W ). Then S = T k i=1 S i is skeptil rtionl extension for (D W ). 2. Every skeptil rtionl extension of (D W ) n e represented s the intersetion of ertin numer (possily innitely mny) of extensions. Proof. The rst ssertion follows from Proposition 19 nd Corollry 10. The seond ssertion follows from Theorem 12 nd from the ft tht for norml defult theories extensions nd rtionl extensions oinide. 2 Corollry 21. Let (D W ) e norml defult theory with nite numer of extensions. Then the fmily of ll skeptil rtionl extensions of (D W ) is losed under intersetion. In prtiulr, the fmily of ll skeptil rtionl extensions of nite norml defult theory is losed under intersetion. 2 The question whether the intersetion of n ritrry olletion of extensions of norml defult theory is skeptil rtionl extension remins open. However, Theorem 15 nd the ft tht for norml defult theories extensions oinide with rtionl extensions imply weker result. Theorem 22. The intersetion of ll extensions of norml defult theory is the lest skeptil rtionl extension for this theory. 2 The following exmple shows tht Theorem 22 is not true for seminorml defult theories. Exmple 7. Let D = M M M( ^ ) The defult theory (D ) hs one extension S 1 = Cn(f g). This theory hs two rtionl extensions S 1 nd S 2 = Cn(f g). It hs lso two skeptil rtionl extensions S 1 nd S 3 = Cn(f _g). Hene, S 1 is the intersetion of ll extensions while S 3 is the lest skeptil rtionl extension (whih, ording to Theorem 15, oinides with the intersetion of ll rtionl extensions) nd S 1 6= S 3. 2 Theorems 20 nd 22 imply the following orollry. Corollry 23. A formul ' elongs to some (resp. ll) skeptil rtionl extension(s) of norml defult theory (D W ) if nd only if ' elongs to some (resp. ll) extension(s) of (D W ). 2

14 Using Corollry 23 nd the results from [5] on the omplexity of the prolems IN-SOME nd IN-ALL for extensions of norml defult theories we get the following omplexity result. Corollry 24. The prolem IN-SOME Given nite norml defult theory (D W ) nd formul ', deide if ' is in some skeptil rtionl extension of (D W ), is P 2 -omplete. The prolem IN-ALL Given nite norml defult theory (D W ) nd formul ', deide if ' is in ll skeptil rtionl extensions of (D W ), is P 2 -omplete. 2 7 Conlusions In this pper we proposed new version of defult logi. It is sed on the onept of skeptil rtionl extension. We showed tht in the se of norml defult theories our version of defult logi oinides with the stndrd skeptil resoning with extensions. In the se of seminorml defult theories it oinides with the stndrd skeptil resoning with rtionl extensions. We presented some generl properties of skeptil rtionl extensions, n lgorithm to ompute them nd some omplexity results. However, the omplexity of resoning with skeptil rtionl extensions from ritrry defult theories is n open prolem. Referenes 1. P. Besnrd. An introdution to defult logi. Springer-Verlg, Berlin, G. Brewk. Cumultive defult logi in defense of nonmonotoni inferene rules. Artiil Intelligene, 50183{205, G. Brewk. Nonmonotoni resoning logil foundtions of ommonsense. Cmridge University Press, Cmridge, UK, M. Gelfond, V. Lifshitz, H. Przymusinsk, nd M. Truszzynski. Disjuntive defults. In Seond interntionl onferene on priniples of knowledge representtion nd resoning, KR '91, Cmridge, MA, G. Gottlo. Complexity results for nonmonotoni logis. Journl of Logi nd Computtion, 2397{425, W. Mrek nd M. Truszzynski. Nonmonotoni logis ontext-dependent resoning. Berlin Springer-Verlg, A. Mikitiuk nd M. Truszzynski. Rtionl defult logi nd disjuntive logi progrmming. In A. Nerode nd L. Pereir, editors, Logi progrmming nd nonmonotoni resoning, pges 283{299. MIT Press, A. Mikitiuk nd M. Truszzynski. Constrined nd rtionl defult logi. In preprtion, D. Poole. Wht the lottery prdox tells us out defult resoning. In Proeedings of the 2nd onferene on priniples of knowledge representtion nd resoning, KR '89, pges 333{340, Sn Mteo, CA., Morgn Kufmnn. 10. R. Reiter. A logi for defult resoning. Artiil Intelligene, 1381{132, T. Shu. Considertions on Defult Logis. PhD thesis, Tehnishen Hohshule Drmstdt, 1992.

CS 573 Automata Theory and Formal Languages

CS 573 Automata Theory and Formal Languages Non-determinism Automt Theory nd Forml Lnguges Professor Leslie Lnder Leture # 3 Septemer 6, 2 To hieve our gol, we need the onept of Non-deterministi Finite Automton with -moves (NFA) An NFA is tuple

More information

Bisimulation, Games & Hennessy Milner logic

Bisimulation, Games & Hennessy Milner logic Bisimultion, Gmes & Hennessy Milner logi Leture 1 of Modelli Mtemtii dei Proessi Conorrenti Pweł Soboiński Univeristy of Southmpton, UK Bisimultion, Gmes & Hennessy Milner logi p.1/32 Clssil lnguge theory

More information

NON-DETERMINISTIC FSA

NON-DETERMINISTIC FSA Tw o types of non-determinism: NON-DETERMINISTIC FS () Multiple strt-sttes; strt-sttes S Q. The lnguge L(M) ={x:x tkes M from some strt-stte to some finl-stte nd ll of x is proessed}. The string x = is

More information

Technische Universität München Winter term 2009/10 I7 Prof. J. Esparza / J. Křetínský / M. Luttenberger 11. Februar Solution

Technische Universität München Winter term 2009/10 I7 Prof. J. Esparza / J. Křetínský / M. Luttenberger 11. Februar Solution Tehnishe Universität Münhen Winter term 29/ I7 Prof. J. Esprz / J. Křetínský / M. Luttenerger. Ferur 2 Solution Automt nd Forml Lnguges Homework 2 Due 5..29. Exerise 2. Let A e the following finite utomton:

More information

Arrow s Impossibility Theorem

Arrow s Impossibility Theorem Rep Voting Prdoxes Properties Arrow s Theorem Arrow s Impossiility Theorem Leture 12 Arrow s Impossiility Theorem Leture 12, Slide 1 Rep Voting Prdoxes Properties Arrow s Theorem Leture Overview 1 Rep

More information

MAT 403 NOTES 4. f + f =

MAT 403 NOTES 4. f + f = MAT 403 NOTES 4 1. Fundmentl Theorem o Clulus We will proo more generl version o the FTC thn the textook. But just like the textook, we strt with the ollowing proposition. Let R[, ] e the set o Riemnn

More information

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras

On Implicative and Strong Implicative Filters of Lattice Wajsberg Algebras Glol Journl of Mthemtil Sienes: Theory nd Prtil. ISSN 974-32 Volume 9, Numer 3 (27), pp. 387-397 Interntionl Reserh Pulition House http://www.irphouse.om On Implitive nd Strong Implitive Filters of Lttie

More information

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides.

1 PYTHAGORAS THEOREM 1. Given a right angled triangle, the square of the hypotenuse is equal to the sum of the squares of the other two sides. 1 PYTHAGORAS THEOREM 1 1 Pythgors Theorem In this setion we will present geometri proof of the fmous theorem of Pythgors. Given right ngled tringle, the squre of the hypotenuse is equl to the sum of the

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

where the box contains a finite number of gates from the given collection. Examples of gates that are commonly used are the following: a b

where the box contains a finite number of gates from the given collection. Examples of gates that are commonly used are the following: a b CS 294-2 9/11/04 Quntum Ciruit Model, Solovy-Kitev Theorem, BQP Fll 2004 Leture 4 1 Quntum Ciruit Model 1.1 Clssil Ciruits - Universl Gte Sets A lssil iruit implements multi-output oolen funtion f : {0,1}

More information

CS 491G Combinatorial Optimization Lecture Notes

CS 491G Combinatorial Optimization Lecture Notes CS 491G Comintoril Optimiztion Leture Notes Dvi Owen July 30, August 1 1 Mthings Figure 1: two possile mthings in simple grph. Definition 1 Given grph G = V, E, mthing is olletion of eges M suh tht e i,

More information

A Lower Bound for the Length of a Partial Transversal in a Latin Square, Revised Version

A Lower Bound for the Length of a Partial Transversal in a Latin Square, Revised Version A Lower Bound for the Length of Prtil Trnsversl in Ltin Squre, Revised Version Pooy Htmi nd Peter W. Shor Deprtment of Mthemtil Sienes, Shrif University of Tehnology, P.O.Bo 11365-9415, Tehrn, Irn Deprtment

More information

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6

CS311 Computational Structures Regular Languages and Regular Grammars. Lecture 6 CS311 Computtionl Strutures Regulr Lnguges nd Regulr Grmmrs Leture 6 1 Wht we know so fr: RLs re losed under produt, union nd * Every RL n e written s RE, nd every RE represents RL Every RL n e reognized

More information

Introduction to Olympiad Inequalities

Introduction to Olympiad Inequalities Introdution to Olympid Inequlities Edutionl Studies Progrm HSSP Msshusetts Institute of Tehnology Snj Simonovikj Spring 207 Contents Wrm up nd Am-Gm inequlity 2. Elementry inequlities......................

More information

6.5 Improper integrals

6.5 Improper integrals Eerpt from "Clulus" 3 AoPS In. www.rtofprolemsolving.om 6.5. IMPROPER INTEGRALS 6.5 Improper integrls As we ve seen, we use the definite integrl R f to ompute the re of the region under the grph of y =

More information

#A42 INTEGERS 11 (2011) ON THE CONDITIONED BINOMIAL COEFFICIENTS

#A42 INTEGERS 11 (2011) ON THE CONDITIONED BINOMIAL COEFFICIENTS #A42 INTEGERS 11 (2011 ON THE CONDITIONED BINOMIAL COEFFICIENTS Liqun To Shool of Mthemtil Sienes, Luoyng Norml University, Luoyng, Chin lqto@lynuedun Reeived: 12/24/10, Revised: 5/11/11, Aepted: 5/16/11,

More information

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

The University of Nottingham SCHOOL OF COMPUTER SCIENCE A LEVEL 2 MODULE, SPRING SEMESTER MACHINES AND THEIR LANGUAGES ANSWERS The University of ottinghm SCHOOL OF COMPUTR SCIC A LVL 2 MODUL, SPRIG SMSTR 2015 2016 MACHIS AD THIR LAGUAGS ASWRS Time llowed TWO hours Cndidtes my omplete the front over of their nswer ook nd sign their

More information

More Properties of the Riemann Integral

More Properties of the Riemann Integral More Properties of the Riemnn Integrl Jmes K. Peterson Deprtment of Biologil Sienes nd Deprtment of Mthemtil Sienes Clemson University Februry 15, 2018 Outline More Riemnn Integrl Properties The Fundmentl

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

TOPIC: LINEAR ALGEBRA MATRICES

TOPIC: LINEAR ALGEBRA MATRICES Interntionl Blurete LECTUE NOTES for FUTHE MATHEMATICS Dr TOPIC: LINEA ALGEBA MATICES. DEFINITION OF A MATIX MATIX OPEATIONS.. THE DETEMINANT deta THE INVESE A -... SYSTEMS OF LINEA EQUATIONS. 8. THE AUGMENTED

More information

Arrow s Impossibility Theorem

Arrow s Impossibility Theorem Rep Fun Gme Properties Arrow s Theorem Arrow s Impossiility Theorem Leture 12 Arrow s Impossiility Theorem Leture 12, Slide 1 Rep Fun Gme Properties Arrow s Theorem Leture Overview 1 Rep 2 Fun Gme 3 Properties

More information

LIP. Laboratoire de l Informatique du Parallélisme. Ecole Normale Supérieure de Lyon

LIP. Laboratoire de l Informatique du Parallélisme. Ecole Normale Supérieure de Lyon LIP Lortoire de l Informtique du Prllélisme Eole Normle Supérieure de Lyon Institut IMAG Unité de reherhe ssoiée u CNRS n 1398 One-wy Cellulr Automt on Cyley Grphs Zsuzsnn Rok Mrs 1993 Reserh Report N

More information

Discrete Structures Lecture 11

Discrete Structures Lecture 11 Introdution Good morning. In this setion we study funtions. A funtion is mpping from one set to nother set or, perhps, from one set to itself. We study the properties of funtions. A mpping my not e funtion.

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

Nondeterministic Automata vs Deterministic Automata

Nondeterministic Automata vs Deterministic Automata Nondeterministi Automt vs Deterministi Automt We lerned tht NFA is onvenient model for showing the reltionships mong regulr grmmrs, FA, nd regulr expressions, nd designing them. However, we know tht n

More information

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs

Counting Paths Between Vertices. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs. Isomorphism of Graphs Isomorphism of Grphs Definition The simple grphs G 1 = (V 1, E 1 ) n G = (V, E ) re isomorphi if there is ijetion (n oneto-one n onto funtion) f from V 1 to V with the property tht n re jent in G 1 if

More information

TIME AND STATE IN DISTRIBUTED SYSTEMS

TIME AND STATE IN DISTRIBUTED SYSTEMS Distriuted Systems Fö 5-1 Distriuted Systems Fö 5-2 TIME ND STTE IN DISTRIUTED SYSTEMS 1. Time in Distriuted Systems Time in Distriuted Systems euse eh mhine in distriuted system hs its own lok there is

More information

Chapter 4 State-Space Planning

Chapter 4 State-Space Planning Leture slides for Automted Plnning: Theory nd Prtie Chpter 4 Stte-Spe Plnning Dn S. Nu CMSC 722, AI Plnning University of Mrylnd, Spring 2008 1 Motivtion Nerly ll plnning proedures re serh proedures Different

More information

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic

Chapter 3. Vector Spaces. 3.1 Images and Image Arithmetic Chpter 3 Vetor Spes In Chpter 2, we sw tht the set of imges possessed numer of onvenient properties. It turns out tht ny set tht possesses similr onvenient properties n e nlyzed in similr wy. In liner

More information

= state, a = reading and q j

= state, a = reading and q j 4 Finite Automt CHAPTER 2 Finite Automt (FA) (i) Derterministi Finite Automt (DFA) A DFA, M Q, q,, F, Where, Q = set of sttes (finite) q Q = the strt/initil stte = input lphet (finite) (use only those

More information

Lecture Notes No. 10

Lecture Notes No. 10 2.6 System Identifition, Estimtion, nd Lerning Leture otes o. Mrh 3, 26 6 Model Struture of Liner ime Invrint Systems 6. Model Struture In representing dynmil system, the first step is to find n pproprite

More information

Nondeterministic Finite Automata

Nondeterministic Finite Automata Nondeterministi Finite utomt The Power of Guessing Tuesdy, Otoer 4, 2 Reding: Sipser.2 (first prt); Stoughton 3.3 3.5 S235 Lnguges nd utomt eprtment of omputer Siene Wellesley ollege Finite utomton (F)

More information

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES

PAIR OF LINEAR EQUATIONS IN TWO VARIABLES PAIR OF LINEAR EQUATIONS IN TWO VARIABLES. Two liner equtions in the sme two vriles re lled pir of liner equtions in two vriles. The most generl form of pir of liner equtions is x + y + 0 x + y + 0 where,,,,,,

More information

System Validation (IN4387) November 2, 2012, 14:00-17:00

System Validation (IN4387) November 2, 2012, 14:00-17:00 System Vlidtion (IN4387) Novemer 2, 2012, 14:00-17:00 Importnt Notes. The exmintion omprises 5 question in 4 pges. Give omplete explntion nd do not onfine yourself to giving the finl nswer. Good luk! Exerise

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

Logic Synthesis and Verification

Logic Synthesis and Verification Logi Synthesis nd Verifition SOPs nd Inompletely Speified Funtions Jie-Hong Rolnd Jing 江介宏 Deprtment of Eletril Engineering Ntionl Tiwn University Fll 2010 Reding: Logi Synthesis in Nutshell Setion 2 most

More information

Symmetrical Components 1

Symmetrical Components 1 Symmetril Components. Introdution These notes should e red together with Setion. of your text. When performing stedy-stte nlysis of high voltge trnsmission systems, we mke use of the per-phse equivlent

More information

Lesson 2: The Pythagorean Theorem and Similar Triangles. A Brief Review of the Pythagorean Theorem.

Lesson 2: The Pythagorean Theorem and Similar Triangles. A Brief Review of the Pythagorean Theorem. 27 Lesson 2: The Pythgoren Theorem nd Similr Tringles A Brief Review of the Pythgoren Theorem. Rell tht n ngle whih mesures 90º is lled right ngle. If one of the ngles of tringle is right ngle, then we

More information

POSITIVE IMPLICATIVE AND ASSOCIATIVE FILTERS OF LATTICE IMPLICATION ALGEBRAS

POSITIVE IMPLICATIVE AND ASSOCIATIVE FILTERS OF LATTICE IMPLICATION ALGEBRAS Bull. Koren Mth. So. 35 (998), No., pp. 53 6 POSITIVE IMPLICATIVE AND ASSOCIATIVE FILTERS OF LATTICE IMPLICATION ALGEBRAS YOUNG BAE JUN*, YANG XU AND KEYUN QIN ABSTRACT. We introue the onepts of positive

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

Hyers-Ulam stability of Pielou logistic difference equation

Hyers-Ulam stability of Pielou logistic difference equation vilble online t wwwisr-publitionsom/jns J Nonliner Si ppl, 0 (207, 35 322 Reserh rtile Journl Homepge: wwwtjnsom - wwwisr-publitionsom/jns Hyers-Ulm stbility of Pielou logisti differene eqution Soon-Mo

More information

Section 1.3 Triangles

Section 1.3 Triangles Se 1.3 Tringles 21 Setion 1.3 Tringles LELING TRINGLE The line segments tht form tringle re lled the sides of the tringle. Eh pir of sides forms n ngle, lled n interior ngle, nd eh tringle hs three interior

More information

Transition systems (motivation)

Transition systems (motivation) Trnsition systems (motivtion) Course Modelling of Conurrent Systems ( Modellierung neenläufiger Systeme ) Winter Semester 2009/0 University of Duisurg-Essen Brr König Tehing ssistnt: Christoph Blume In

More information

A Study on the Properties of Rational Triangles

A Study on the Properties of Rational Triangles Interntionl Journl of Mthemtis Reserh. ISSN 0976-5840 Volume 6, Numer (04), pp. 8-9 Interntionl Reserh Pulition House http://www.irphouse.om Study on the Properties of Rtionl Tringles M. Q. lm, M.R. Hssn

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

Pre-Lie algebras, rooted trees and related algebraic structures

Pre-Lie algebras, rooted trees and related algebraic structures Pre-Lie lgers, rooted trees nd relted lgeri strutures Mrh 23, 2004 Definition 1 A pre-lie lger is vetor spe W with mp : W W W suh tht (x y) z x (y z) = (x z) y x (z y). (1) Exmple 2 All ssoitive lgers

More information

The Word Problem in Quandles

The Word Problem in Quandles The Word Prolem in Qundles Benjmin Fish Advisor: Ren Levitt April 5, 2013 1 1 Introdution A word over n lger A is finite sequene of elements of A, prentheses, nd opertions of A defined reursively: Given

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

A CLASS OF GENERAL SUPERTREE METHODS FOR NESTED TAXA

A CLASS OF GENERAL SUPERTREE METHODS FOR NESTED TAXA A CLASS OF GENERAL SUPERTREE METHODS FOR NESTED TAXA PHILIP DANIEL AND CHARLES SEMPLE Astrt. Amlgmting smller evolutionry trees into single prent tree is n importnt tsk in evolutionry iology. Trditionlly,

More information

Co-ordinated s-convex Function in the First Sense with Some Hadamard-Type Inequalities

Co-ordinated s-convex Function in the First Sense with Some Hadamard-Type Inequalities Int. J. Contemp. Mth. Sienes, Vol. 3, 008, no. 3, 557-567 Co-ordinted s-convex Funtion in the First Sense with Some Hdmrd-Type Inequlities Mohmmd Alomri nd Mslin Drus Shool o Mthemtil Sienes Fulty o Siene

More information

Ch. 2.3 Counting Sample Points. Cardinality of a Set

Ch. 2.3 Counting Sample Points. Cardinality of a Set Ch..3 Counting Smple Points CH 8 Crdinlity of Set Let S e set. If there re extly n distint elements in S, where n is nonnegtive integer, we sy S is finite set nd n is the rdinlity of S. The rdinlity of

More information

, if x 1 and f(x) = x, if x 0.

, if x 1 and f(x) = x, if x 0. Indin Institute of Informtion Technology Design nd Mnufcturing, Kncheepurm Chenni 600 7, Indi An Autonomous Institute under MHRD, Govt of Indi An Institute of Ntionl Importnce wwwiiitdmcin COM05T Discrete

More information

Behavior Composition in the Presence of Failure

Behavior Composition in the Presence of Failure Behvior Composition in the Presene of Filure Sestin Srdin RMIT University, Melourne, Austrli Fio Ptrizi & Giuseppe De Giomo Spienz Univ. Rom, Itly KR 08, Sept. 2008, Sydney Austrli Introdution There re

More information

Project 6: Minigoals Towards Simplifying and Rewriting Expressions

Project 6: Minigoals Towards Simplifying and Rewriting Expressions MAT 51 Wldis Projet 6: Minigols Towrds Simplifying nd Rewriting Expressions The distriutive property nd like terms You hve proly lerned in previous lsses out dding like terms ut one prolem with the wy

More information

(a) A partition P of [a, b] is a finite subset of [a, b] containing a and b. If Q is another partition and P Q, then Q is a refinement of P.

(a) A partition P of [a, b] is a finite subset of [a, b] containing a and b. If Q is another partition and P Q, then Q is a refinement of P. Chpter 7: The Riemnn Integrl When the derivtive is introdued, it is not hrd to see tht the it of the differene quotient should be equl to the slope of the tngent line, or when the horizontl xis is time

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

Compression of Palindromes and Regularity.

Compression of Palindromes and Regularity. Compression of Plinromes n Regulrity. Kyoko Shikishim-Tsuji Center for Lierl Arts Eution n Reserh Tenri University 1 Introution In [1], property of likstrem t t view of tse is isusse n it is shown tht

More information

Part I: Study the theorem statement.

Part I: Study the theorem statement. Nme 1 Nme 2 Nme 3 A STUDY OF PYTHAGORAS THEOREM Instrutions: Together in groups of 2 or 3, fill out the following worksheet. You my lift nswers from the reding, or nswer on your own. Turn in one pket for

More information

Finite State Automata and Determinisation

Finite State Automata and Determinisation Finite Stte Automt nd Deterministion Tim Dworn Jnury, 2016 Lnguges fs nf re df Deterministion 2 Outline 1 Lnguges 2 Finite Stte Automt (fs) 3 Non-deterministi Finite Stte Automt (nf) 4 Regulr Expressions

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

Algorithm Design and Analysis

Algorithm Design and Analysis Algorithm Design nd Anlysis LECTURE 8 Mx. lteness ont d Optiml Ching Adm Smith 9/12/2008 A. Smith; sed on slides y E. Demine, C. Leiserson, S. Rskhodnikov, K. Wyne Sheduling to Minimizing Lteness Minimizing

More information

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite!

Solutions for HW9. Bipartite: put the red vertices in V 1 and the black in V 2. Not bipartite! Solutions for HW9 Exerise 28. () Drw C 6, W 6 K 6, n K 5,3. C 6 : W 6 : K 6 : K 5,3 : () Whih of the following re iprtite? Justify your nswer. Biprtite: put the re verties in V 1 n the lk in V 2. Biprtite:

More information

Discrete Structures, Test 2 Monday, March 28, 2016 SOLUTIONS, VERSION α

Discrete Structures, Test 2 Monday, March 28, 2016 SOLUTIONS, VERSION α Disrete Strutures, Test 2 Mondy, Mrh 28, 2016 SOLUTIONS, VERSION α α 1. (18 pts) Short nswer. Put your nswer in the ox. No prtil redit. () Consider the reltion R on {,,, d with mtrix digrph of R.. Drw

More information

On Determinism in Modal Transition Systems

On Determinism in Modal Transition Systems On Determinism in Modl Trnsition Systems N. Beneš,2, J. Křetínský,3, K. G. Lrsen 5, J. Sr,4 Deprtment of Computer Siene, Alorg University, Selm Lgerlöfs Vej 300, 9220 Alorg Øst, Denmrk Astrt Modl trnsition

More information

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then.

April 8, 2017 Math 9. Geometry. Solving vector problems. Problem. Prove that if vectors and satisfy, then. pril 8, 2017 Mth 9 Geometry Solving vetor prolems Prolem Prove tht if vetors nd stisfy, then Solution 1 onsider the vetor ddition prllelogrm shown in the Figure Sine its digonls hve equl length,, the prllelogrm

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

Lecture 1 - Introduction and Basic Facts about PDEs

Lecture 1 - Introduction and Basic Facts about PDEs * 18.15 - Introdution to PDEs, Fll 004 Prof. Gigliol Stffilni Leture 1 - Introdution nd Bsi Fts bout PDEs The Content of the Course Definition of Prtil Differentil Eqution (PDE) Liner PDEs VVVVVVVVVVVVVVVVVVVV

More information

2.4 Theoretical Foundations

2.4 Theoretical Foundations 2 Progrmming Lnguge Syntx 2.4 Theoretil Fountions As note in the min text, snners n prsers re se on the finite utomt n pushown utomt tht form the ottom two levels of the Chomsky lnguge hierrhy. At eh level

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

Linearly Similar Polynomials

Linearly Similar Polynomials Linerly Similr Polynomils rthur Holshouser 3600 Bullrd St. Chrlotte, NC, US Hrold Reiter Deprtment of Mthemticl Sciences University of North Crolin Chrlotte, Chrlotte, NC 28223, US hbreiter@uncc.edu stndrd

More information

THE PYTHAGOREAN THEOREM

THE PYTHAGOREAN THEOREM THE PYTHAGOREAN THEOREM The Pythgoren Theorem is one of the most well-known nd widely used theorems in mthemtis. We will first look t n informl investigtion of the Pythgoren Theorem, nd then pply this

More information

Topologie en Meetkunde 2011 Lecturers: Marius Crainic and Ivan Struchiner

Topologie en Meetkunde 2011 Lecturers: Marius Crainic and Ivan Struchiner Topologie en Meetkunde 21 Leturers: Mrius Crini nd Ivn Struhiner CHAPTER 1 The Clssifition Prolem for Compt Surfes 1. Introdution In this Chpter we will introdue nd strt deling with the lssifition prolem

More information

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions

Activities. 4.1 Pythagoras' Theorem 4.2 Spirals 4.3 Clinometers 4.4 Radar 4.5 Posting Parcels 4.6 Interlocking Pipes 4.7 Sine Rule Notes and Solutions MEP: Demonstrtion Projet UNIT 4: Trigonometry UNIT 4 Trigonometry tivities tivities 4. Pythgors' Theorem 4.2 Spirls 4.3 linometers 4.4 Rdr 4.5 Posting Prels 4.6 Interloking Pipes 4.7 Sine Rule Notes nd

More information

Algorithm Design and Analysis

Algorithm Design and Analysis Algorithm Design nd Anlysis LECTURE 5 Supplement Greedy Algorithms Cont d Minimizing lteness Ching (NOT overed in leture) Adm Smith 9/8/10 A. Smith; sed on slides y E. Demine, C. Leiserson, S. Rskhodnikov,

More information

Section 4.4. Green s Theorem

Section 4.4. Green s Theorem The Clulus of Funtions of Severl Vriles Setion 4.4 Green s Theorem Green s theorem is n exmple from fmily of theorems whih onnet line integrls (nd their higher-dimensionl nlogues) with the definite integrls

More information

CHENG Chun Chor Litwin The Hong Kong Institute of Education

CHENG Chun Chor Litwin The Hong Kong Institute of Education PE-hing Mi terntionl onferene IV: novtion of Mthemtis Tehing nd Lerning through Lesson Study- onnetion etween ssessment nd Sujet Mtter HENG hun hor Litwin The Hong Kong stitute of Edution Report on using

More information

CONTROLLABILITY and observability are the central

CONTROLLABILITY and observability are the central 1 Complexity of Infiml Oservle Superlnguges Tomáš Msopust Astrt The infiml prefix-losed, ontrollle nd oservle superlnguge plys n essentil role in the reltionship etween ontrollility, oservility nd o-oservility

More information

Centrum voor Wiskunde en Informatica REPORTRAPPORT. Supervisory control for nondeterministic systems

Centrum voor Wiskunde en Informatica REPORTRAPPORT. Supervisory control for nondeterministic systems Centrum voor Wiskunde en Informtic REPORTRAPPORT Supervisory control for nondeterministic systems A. Overkmp Deprtment of Opertions Reserch, Sttistics, nd System Theory BS-R9411 1994 Supervisory Control

More information

5. Every rational number have either terminating or repeating (recurring) decimal representation.

5. Every rational number have either terminating or repeating (recurring) decimal representation. CHAPTER NUMBER SYSTEMS Points to Rememer :. Numer used for ounting,,,,... re known s Nturl numers.. All nturl numers together with zero i.e. 0,,,,,... re known s whole numers.. All nturl numers, zero nd

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

T b a(f) [f ] +. P b a(f) = Conclude that if f is in AC then it is the difference of two monotone absolutely continuous functions.

T b a(f) [f ] +. P b a(f) = Conclude that if f is in AC then it is the difference of two monotone absolutely continuous functions. Rel Vribles, Fll 2014 Problem set 5 Solution suggestions Exerise 1. Let f be bsolutely ontinuous on [, b] Show tht nd T b (f) P b (f) f (x) dx [f ] +. Conlude tht if f is in AC then it is the differene

More information

Alpha Algorithm: Limitations

Alpha Algorithm: Limitations Proess Mining: Dt Siene in Ation Alph Algorithm: Limittions prof.dr.ir. Wil vn der Alst www.proessmining.org Let L e n event log over T. α(l) is defined s follows. 1. T L = { t T σ L t σ}, 2. T I = { t

More information

Figure 1. The left-handed and right-handed trefoils

Figure 1. The left-handed and right-handed trefoils The Knot Group A knot is n emedding of the irle into R 3 (or S 3 ), k : S 1 R 3. We shll ssume our knots re tme, mening the emedding n e extended to solid torus, K : S 1 D 2 R 3. The imge is lled tuulr

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

Propositional models. Historical models of computation. Application: binary addition. Boolean functions. Implementation using switches.

Propositional models. Historical models of computation. Application: binary addition. Boolean functions. Implementation using switches. Propositionl models Historil models of omputtion Steven Lindell Hverford College USA 1/22/2010 ISLA 2010 1 Strt with fixed numer of oolen vriles lled the voulry: e.g.,,. Eh oolen vrile represents proposition,

More information

Algorithms & Data Structures Homework 8 HS 18 Exercise Class (Room & TA): Submitted by: Peer Feedback by: Points:

Algorithms & Data Structures Homework 8 HS 18 Exercise Class (Room & TA): Submitted by: Peer Feedback by: Points: Eidgenössishe Tehnishe Hohshule Zürih Eole polytehnique fédérle de Zurih Politenio federle di Zurigo Federl Institute of Tehnology t Zurih Deprtement of Computer Siene. Novemer 0 Mrkus Püshel, Dvid Steurer

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

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

Necessary and sucient conditions for some two. Abstract. Further we show that the necessary conditions for the existence of an OD(44 s 1 s 2 )

Necessary and sucient conditions for some two. Abstract. Further we show that the necessary conditions for the existence of an OD(44 s 1 s 2 ) Neessry n suient onitions for some two vrile orthogonl esigns in orer 44 C. Koukouvinos, M. Mitrouli y, n Jennifer Seerry z Deite to Professor Anne Penfol Street Astrt We give new lgorithm whih llows us

More information

Electromagnetism Notes, NYU Spring 2018

Electromagnetism Notes, NYU Spring 2018 Eletromgnetism Notes, NYU Spring 208 April 2, 208 Ation formultion of EM. Free field desription Let us first onsider the free EM field, i.e. in the bsene of ny hrges or urrents. To tret this s mehnil system

More information

State Minimization for DFAs

State Minimization for DFAs Stte Minimiztion for DFAs Red K & S 2.7 Do Homework 10. Consider: Stte Minimiztion 4 5 Is this miniml mchine? Step (1): Get rid of unrechle sttes. Stte Minimiztion 6, Stte is unrechle. Step (2): Get rid

More information

Engr354: Digital Logic Circuits

Engr354: Digital Logic Circuits Engr354: Digitl Logi Ciruits Chpter 4: Logi Optimiztion Curtis Nelson Logi Optimiztion In hpter 4 you will lern out: Synthesis of logi funtions; Anlysis of logi iruits; Tehniques for deriving minimum-ost

More information

Linear choosability of graphs

Linear choosability of graphs Liner hoosility of grphs Louis Esperet, Mikel Montssier, André Rspud To ite this version: Louis Esperet, Mikel Montssier, André Rspud. Liner hoosility of grphs. Stefn Felsner. 2005 Europen Conferene on

More information

Model Reduction of Finite State Machines by Contraction

Model Reduction of Finite State Machines by Contraction Model Reduction of Finite Stte Mchines y Contrction Alessndro Giu Dip. di Ingegneri Elettric ed Elettronic, Università di Cgliri, Pizz d Armi, 09123 Cgliri, Itly Phone: +39-070-675-5892 Fx: +39-070-675-5900

More information

Solutions to Assignment 1

Solutions to Assignment 1 MTHE 237 Fll 2015 Solutions to Assignment 1 Problem 1 Find the order of the differentil eqution: t d3 y dt 3 +t2 y = os(t. Is the differentil eqution liner? Is the eqution homogeneous? b Repet the bove

More information

QUADRATIC EQUATION. Contents

QUADRATIC EQUATION. Contents QUADRATIC EQUATION Contents Topi Pge No. Theory 0-04 Exerise - 05-09 Exerise - 09-3 Exerise - 3 4-5 Exerise - 4 6 Answer Key 7-8 Syllus Qudrti equtions with rel oeffiients, reltions etween roots nd oeffiients,

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

Part 4. Integration (with Proofs)

Part 4. Integration (with Proofs) Prt 4. Integrtion (with Proofs) 4.1 Definition Definition A prtition P of [, b] is finite set of points {x 0, x 1,..., x n } with = x 0 < x 1

More information

ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups. Sang Keun Lee

ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups. Sang Keun Lee Kngweon-Kyungki Mth. Jour. 10 (2002), No. 2, pp. 117 122 ON LEFT(RIGHT) SEMI-REGULAR AND g-reguar po-semigroups Sng Keun Lee Astrt. In this pper, we give some properties of left(right) semi-regulr nd g-regulr

More information

arxiv: v1 [math.ca] 21 Aug 2018

arxiv: v1 [math.ca] 21 Aug 2018 rxiv:1808.07159v1 [mth.ca] 1 Aug 018 Clulus on Dul Rel Numbers Keqin Liu Deprtment of Mthemtis The University of British Columbi Vnouver, BC Cnd, V6T 1Z Augest, 018 Abstrt We present the bsi theory of

More information