On the Revision of Argumentation Systems: Minimal Change of Arguments Status

Size: px
Start display at page:

Download "On the Revision of Argumentation Systems: Minimal Change of Arguments Status"

Transcription

1 On the Revision of Argumenttion Systems: Miniml Chnge of Arguments Sttus Sylvie Coste-Mrquis, Séstien Koniezny, Jen-Guy Milly, n Pierre Mrquis CRIL Université Artois CNRS Lens, Frne {oste,koniezny,milly,mrquis}@ril.fr Astrt. In this pper, we investigte the revision issue for rgumenttion systems à l Dung. We fous on revision s miniml hnge of the rguments sttus. Contrrily to most of the previous works on the topi, the ition of new rguments is not llowe in the revision proess, so tht the revise system hs to e otine y moifying the ttk reltion, only. We introue lnguge of revision formule whih is expressive enough for enling the representtion of omplex onitions on the eptility of rguments in the revise system. We show how AGM elief revision postultes n e trnslte to the se of rgumenttion systems. We provie orresponing representtion theorem in terms of miniml hnge of the rguments sttus. Severl istne-se revision opertors stisfying the postultes re lso pointe out. Keywors: rgumenttion, elief revision 1 Introution In this pper, we investigte the revision issue for strt rgumenttion systems à l Dung [1]. Argumenttion systems re irete grphs, where noes orrespon to rguments n rs to ttks etween rguments. In suh systems, the sttus (eptne) of eh rgument epens on the hosen eptility semntis (groune, preferre, stle mong others). In his ook [2] Gärenfors introue strtly elief hnge s the opertion llowing to hnge the epistemi sttus of piee of informtion with respet to the epistemi stte of n gent. There re three possile sttus: epte, refuse or unefine. An revision, ontrtion n expnsion re efine s the possile trnsitions etween these sttus, s illustrte y Figure 1. Then Gärenfors instntites this generl efinition within logil frmework. But it is interesting to note tht efore efining elief hnge opertors, one hs to mke preise the logil setting into whih the sttus epte, refuse n unefine re efine. Similrly, if one wnts to instntite Gärenfors generl efinition of elief hnge within Dung s rgumenttion theory, it is first neessry to efine wht

2 2 Unefine Expnsion Contrtion Expnsion Contrtion Aepte Revision Revision Refuse Fig. 1. Gärenfors epistemi trnsitions re the ville piees of informtion n wht these sttus men. In Dung s rgumenttion theory, the si piees of informtion re the rguments of the system, n their sttus epens on the eptility semntis uner onsiertion. Thus, it oes not mke sense to stuy the revision of rgumenttion systems iretly on the ttk grph, inepenently of ny semntis. Stte otherwise, the revision of given rgumenttion system uner two ifferent semntis my esily le to two ifferent results. For instne, in the se of the rgumenttion system given on Figure 2, we note tht uner the stle n preferre semntis, elongs to every extension, wheres oes not elong to ny extension in the se of the groune semntis. So, revise to ept oes not nee ny hnge for stle n preferre semntis, ut hnge is require for the groune semntis. Fig. 2. The hnge neee to revise this system is not the sme oring to the semntis. In this pper, we fous on revision s miniml hnge of the rguments sttus. To e more preise, uner hosen semntis, n given n rgumenttion system n revision formul expressing how the sttus of some rguments hs to e hnge, we wnt to erive one or severl rgumenttion systems whih stisfy the revision formul, n re suh tht the orresponing extensions re s lose s possile to the extensions of the input system. Contrrily to most of the previous works on the topi, the ition of new rguments is not llowe in the revision proess, so tht the revise system hs to e otine y moifying the ttk reltion, only. Espeilly, the revision formul oes not inite why the sttus of rguments hve hnge.

3 3 Miniml hnge of the ttk grph n e onsiere s riterion for efining the revise systems, ut not s the min one, sine, s expline ove, the eptne sttus of rguments is more funmentl informtion. Aoringly, ensuring miniml hnge of these sttus is more importnt thn (n ifferent from) ensuring miniml hnge of the ttk grph. Suh revision opertors, where miniml hnge ers on the rguments sttus, n e very useful for pplitions of rgumenttion on soil network etes [3]. When n gent A initites ete out n rgument α, if nother gent B oes not gree with A out α ut onsiers tht A is trustworthy, B hs to revise her eliefs to inlue α in t lest one of her extensions. This kin of resoning uses reulous inferene, ut it n e reple y skeptil inferene n so the revise system n e ompute with one of the opertors efine in this pper. The rest of the pper is orgnize s follows. After short introution to the Dung s theory of strt rgumenttion in Setion 2, we introue lnguge of revision formule whih is expressive enough for enling the representtion of omplex onitions on the eptility of rguments in the revise system in Setion 3. In Setion 4 we show how AGM elief revision postultes n e trnslte to the se of rgumenttion systems. An we provie orresponing representtion theorem in terms of miniml hnge of the rguments sttus. In Setion 5 severl istne-se revision opertors stisfying the postultes re pointe out. Then Setion 6 isusses how to ssoite rgumenttion systems to the otine sets of extensions, n isuss the issue of miniml hnge of the ttk grph. Setion 7 isusses some relte work. Setion 8 onlues the pper. Proofs re omitte for spe resons. 2 Preliminries We strt with very short introution to Dung s theory of rgumenttion (see [1] for more etils). A (finite) rgumenttion system (lso referre to s n rgumenttion frmework) is pir AF = A, R where A is (finite) set of so-lle rguments n R is inry reltion over A ( suset of A A). In the following, A is suppose to ontin t lest two elements n the ttk reltion R is suppose to e irreflexive, i.e., self-ontriting rguments re rejete. AFs A enotes the set of ll suh systems on the set of rguments A. An rgument A is eptle with respet to set of rguments S A whenever it is efene y the set, i.e., for every A s.t. (, ) R, there exists S suh tht (, ) R. We sy tht suset S of A is onflit-free if n only if for every, S, we hve (, ) R. A suset S of A is missile for AF if n only if S is onflit-free n eptle with respet to S. Solutions of n rgumenttion systems re sets S of rguments tht n e, so to sy, epte together. Severl semntis σ (espeilly, the omplete semntis, the preferre semntis, the stle semntis, the groune semntis) n e onsiere for pturing formlly this notion, n eh of them gives rise to speifi notion of extensions. For instne:

4 4 S is omplete extension of AF if n only if it is n missile set n every rgument whih is eptle w.r.t. S elongs to S, S is preferre extension of AF if n only if it is mximl (with respet to set inlusion) in the set of missile sets for AF, S is stle extension of AF if n only if S is onflit-free n A \ S, S suh tht (, ) R, S is the (unique) groune extension of AF if n only if it is the smllest element (with respet to set inlusion) mong the omplete extensions. Ext σ (AF ) enotes the set of extensions of AF for the semntis σ. The epistemi sttus of ny rgument A with respet to the epistemi stte represente y AF is then given y: is epte if elongs to every ε Ext σ (AF ), is refuse if oes not elong to ny ε Ext σ (AF ), n is unefine in the remining se. Moreover, one introue nottion out miniml elements of set. First, < enotes the strit prt of n enotes the inifferene reltion ssoite. Given set E n pre-orer, the miniml elements of E w.r.t. this pre-orer re min(e, ) = {e E e E, e < e}. 3 On Revision Formule We wnt to efine revision setting for Dung s rgumenttion systems in whih sophistite revision formule n e tken into ount, n not only the ft tht given rgument shoul e epte or refuse. To this en, we onsier logil lnguge L A, where negtion is use to enote the ft tht given rgument shoul e refuse, n formule n e onnete using onjuntion n isjuntion. Definition 1 Given A = {α 1,..., α k } set of rguments, L A is the lnguge generte y the following ontext-free grmmr in BNF: rg ::= α 1... α k Φ ::= rg Φ (Φ Φ) (Φ Φ) For instne, ϕ 1 = ( (( ) ( ))) expresses tht in the revise epistemi stte one wnts to e epte n n to e oth epte or oth refuse. The epistemi sttus of suh formule ϕ 1 from L A in n rgumenttion system AF AFs A for given semntis σ is given y: Definition 2 Let ε A n ϕ L A. The onept of stisftion of ϕ y ε, note ε ϕ, is efine inutively s follows: If ϕ = A, then ε ϕ iff ε, If ϕ = (ϕ 1 ϕ 2 ), ε ϕ iff ε ϕ 1 n ε ϕ 2, If ϕ = (ϕ 1 ϕ 2 ), ε ϕ iff ε ϕ 1 or ε ϕ 2, If ϕ = ψ, ε ϕ iff ε ψ.

5 5 Then for ny AF in AFs A, n ny semntis σ, we sy tht: ϕ is epte w.r.t. AF, note AF σ ϕ, if ε ϕ for every ε Ext σ (AF ), ϕ is refuse w.r.t. AF, note AF σ ϕ, if ε ϕ for no ε Ext σ (AF ), ϕ is unefine w.r.t. AF in the remining se. From now on we ll nite 1 ny suset ε of A. Cnites n e interprete s moels or ounter-moels of revision formule. Continuing the previous exmple, if A = {,, }, ϕ 1 is stisfie y the nites from {{}, {,, }}. Thus, for the groune semntis, ϕ 1 is epte w.r.t. AF 1 with R 1 = {(, ), (, )} ut is refuse w.r.t. AF 2 with R 2 = {(, ), (, )}. Oviously enough, for ny set M = {ε 1,..., ε k } of nites, there exists formul ϕ L A so tht M = A ϕ, where A ϕ = {ε A ε ϕ} is the set of nites whih stisfy ϕ. However, in the generl se, A ϕ is not the set of ll σ extensions of n AF in AFs A. Consier for instne, A = {,, } n ϕ 1 = ( ) ( ) 2. {} n {,, } re the two nites stisfying ϕ 1, n there is no AF in AFs A suh tht Ext σ (AF ) = {{}, {,, }} for σ = groune, σ = preferre or σ = stle. A onept of σ-onsisteny n then e efine s follows: Definition 3 A formul ϕ L A is σ-onsistent 3 iff there exists set S of rgumenttion systems AF in AFs A suh tht A ϕ = AF S Ext σ(af ). When A = {,, }, ϕ 1 = ( (( ) ( ))) is σ onsistent for σ = groune, σ = preferre or σ = stle sine {{}, {,, }} = Ext σ (AF 3 ) Ext σ (AF 4 ) where R 3 = {(, ), (, )} n R 4 =. Contrstingly, ϕ 2 = is groune-onsistent n preferre-onsistent ut not stle-onsistent. ϕ 3 = neither is groune-onsistent nor is preferre-onsistent, ut is stle-onsistent (onsier AF 5 suh tht R 5 = {(, ), (, ), (, )}.) 4 On the Revision of Argumenttion Systems A revision opertor on rgumenttion systems is mpping ssoiting set of rgumenttion systems to the input rgumenttion system n the input revision formul: Definition 4 Given ny set of rguments A, revision opertor on rgumenttion systems is mpping from AFs A L A to 2 AFs A. Clerly, the result of the revision of n rgumenttion system is not unique rgumenttion system in the generl se, ut set of rgumenttion systems. The reson is quite simple: there n e severl possile results whih hve extly the sme mximum plusiility. So in this se there is no reson to 1 Tht is to sy nite to e n extension 2 Equivlent to ( (( ) ( ))). 3 or simply onsistent if the semntis is fixe.

6 6 hoose priori one of them (we will return to this point lter on.) If this is prolemti for prtiulr pplition, seletion funtion n e use s tie-rek rule for ensuring the uniity of the result (just like, for instne, the mxihoie seletion funtion is onsiere in AGM elief revision [2].) In orer to efine revision opertors, our pproh follows two-step proess. Intuitively, one first selets from the nites stisfying the revision formul ϕ those whih re s lose s possile to the σ-extensions of AF. Then, one genertes some rgumenttion systems suh tht the union of their σ extensions preisely oinies with the selete nites. Of ourse, it is not the se tht eh mpping from AFs A L A to 2 AFs A is resonle revision opertor. For instne, the onstnt, yet trivil opertor efine y AF ϕ = shoul e isre. In orer to ientify interesting revision opertors, one hs to ientify the logil properties tht gurntee rtionl ehviour. Suh n xiomti pproh is stnr in logi n the AGM postultes [4,5] hve een pointe out for hrterizing vlule revision opertors in logil setting. As in [6], we n revisit these postultes in set-theoreti frmework, here suite to the rgumenttion se. Let S e set of rgumenttion systems AF in AFs A. For eh semntis σ, we efine the set Ext σ (S) of σ-extensions of S s AF S Ext σ(af ). The ounterprt of AGM postultes in the rgumenttion se is given y: (AE1) Ext σ (AF ϕ) A ϕ (AE2) If Ext σ (AF ) A ϕ, then Ext σ (AF ϕ) = Ext σ (AF ) A ϕ (AE3) If ϕ is σ-onsistent, then Ext σ (AF ϕ) (AE4) If A ϕ = A ψ, then Ext σ (AF ϕ) = Ext σ (AF ψ) (AE5) Ext σ (AF ϕ) A ψ Ext σ (AF (ϕ ψ)) (AE6) If Ext σ (AF ϕ) A ψ, then Ext σ (AF (ϕ ψ)) Ext σ (AF ϕ) A ψ (AE1) sttes tht the σ-extensions of the resulting set of rgumenttion systems must e mong the nites stisfying ϕ. (AE2) emns tht if there re σ-extensions of the input system stisfying ϕ, then the resulting σ- extensions must oinie with them. (AE3) requires the resulting set of σ- extensions to e non-empty s soon ϕ is σ-onsistent. (AE4) sys tht the revision y equivlent formule must le to the sme results. The lst two postultes (AE5) n (AE6) express miniml hnge priniple with respet to the rguments sttus: one expets to hnge s few s possile the sttus of rguments in the input system. Interestingly, s in the logil se, we n erive representtion theorem whih hrterizes extly the revision opertors stisfying the postultes in more onstrutive wy. To this en, we first nee to exten the notion of fithful ssignment [5]: Definition 5 A fithful ssignment is mpping ssoiting ny rgumenttion system AF = A, R (uner semntis σ) with totl pre-orer σ AF on the set of nites suh tht: 1. if ε 1 Ext σ (AF ) n ε 2 Ext σ (AF ), then ε 1 σ AF ε 2, 2. if ε 1 Ext σ (AF ) n ε 2 Ext σ (AF ), then ε 1 < σ AF ε 2.

7 7 The representtion theorem n then e stte s follows: Proposition 1 Given semntis σ, revision opertor stisfies the rtionlity postultes (AE1) - (AE6) iff there exists fithful ssignment whih mthes every system AF = A, R to totl pre-orer σ AF so tht Ext σ (AF ϕ) = min(a ϕ, σ AF ) This theorem is useful for efining opertors stisfying the rtionlity postultes, s those presente in the next setion. 5 Distne-Bse Revision Let us now present some istne-se revision opertors stisfying the rtionlity postultes (AE1) - (AE6). Let e ny istne on 2 A, for instne, the Hmming istne given y H (ε 1, ε 2 ) = (ε 1 \ ε 2 ) (ε 2 \ ε 1 ). Given ε 2 A n E 2 A, n e extene to istne etween ε n E, y stting tht (ε, E) = min ε E (ε, ε ). For ny rgumenttion system AF AFs A, this istne inues totl pre-orer etween nites ε 1, ε 2 2 A given y ε 1 σ, AF ε 2 iff (ε 1, Ext σ (AF )) (ε 2, Ext σ (AF )). On this groun, revision opertors n e efine y: Definition 6 Let σ e ny given semntis. A istne-se revision opertor is ny revision opertor for whih there exists istne on 2 A suh tht for every AF n every ϕ, we hve Ext σ (AF ϕ) = min(a ϕ, σ, AF ). Proposition 2 Let σ e ny semntis. Any istne-se revision opertor stisfies the rtionlity postultes (AE1) - (AE6). Let us now efine nother fmily of istne-se opertors, whih tke vntge of lellings. Let us first rell tht, inste of using extensions, the solutions of n rgumenttion system n e expresse using the onept of lelling [7]. Formlly, lelling is mpping L ssoiting lel in, une or out with every rgument of the set A. The stronger notion of reinsttement lelling epens on the ttk reltion R: n rgument is lelle in iff every rgument ttking is out; n rgument is out iff there exists n rgument in ttking ; n rgument is une iff it is neither in nor out. These reinsttement lellings orrespon to Dung s omplete extensions in ijetive wy. Thus, for ny omplete extension ε, the ssoite reinsttement lelling is suh tht every rgument ε is in, every rgument ttke y n rgument in is out, every other rgument is une. Conversely, for every reinsttement lelling L, the orresponing extension E(L) is the set of rguments lelle in y the lelling. Other semntis n lso e enoe with lellings. We introue some nottions: L ϕ is the set of lellings L suh tht E(L) A ϕ. Given set of lellings L, E(L) = {E(L) L L}. Finlly, given system AF

8 8 n semntis σ, Ls σ (AF ) enotes the set of lellings orresponing to the σ-extensions of AF. Lellings, whih ring riher informtion thn extensions, n e use to efine interesting istne-se revision opertors. Inee, onsier the following notion of eition istne: Definition 7 Let m, n, o e three integers, let L 1 n L 2 e two lellings, n let X n Y e ny of in, out n une. An eition istne (m,n,o) etween lellings is efine s: (m,n,o) (L 1, L 2 ) = A (L 1 (), L 2 ()), where (in, out) = m (in, une) = n (out, une) = o (X, Y ) = (Y, X) (X, X) = 0 Proposition 3 Let m, n, o e three integers. (m,n,o) is istne. An interesting point to note is tht these eition istnes re not neessrily neutrl or symmetril. We ll neutrl istne suh tht (in, une) + (une, out) = (in, out) n symmetril istne suh tht (in, une) = (une, out). Defining non symmetril istnes is wy for instne to fvor eptne of rguments over rejet, y hoosing (in, une) = 1, (out, une) = 9, n (in, out) = 10. For ny istne L etween lellings, we n efine pre-orer σ, L AF etween lellings s we i it for nites: L 1 σ, L AF L 2 iff L (L 1, L σ (AF )) L (L 2, L σ (AF )). Definition 8 Let σ e ny given semntis. A lelling-istne-se revision opertor L is ny revision opertor for whih there exists istne L = (m,n,o) on 2 A suh tht for every AF n every ϕ, we hve Ls σ (AF L ϕ) = min(l ϕ, σ, L AF ). The following exmple illustrtes the impt of the hosen istne on the revise system: Exmple 1 Let σ e the stle semntis. We revise the system AF 6 elow y the formul ϕ = e. e Ext σ (AF 6 ) = {{,, e}, {,, e}}, the ssoite stle lellings re {(, in), (, out), (, out), (, in), (e, in)} n {(, out), (, in), (, out), (, in),

9 (e, in)}. When we revise AF 6 y ϕ using the istne-se opertor inue y the istne (1,9,10) on lellings, one gets s result system of whom the lellings re {(, in), (, out), (, out), (, out), (e, out)} n {(, out), (, in), (, out), (, out), (e, out)}. When the istne (9,1,10) is use, one otins {(, in), (, out), (, out), (, une), (e, une)} n {(, out), (, in), (, out), (, une), (e, une)} s lellings of the result systems. If the genertion of the systems tke ount of the lellings, the struture of the result grph will e ifferent : when the refuse rguments re out, it mens tht there exists n ttk from n epte rgument to refuse rgument. When the rguments re une, those ttks o not exist. With the first istne (1,9,10), it is less ostly to hnge n rgument from in to out thn to une. Suh istne llow to hoose nites whih refuses rguments y. Contrrily, the istne (9,1,10) llow to hoose nites whih ept more rguments. The hoie of prtiulr istne llow to influene result of the revision. Like opertors se on extensions, istne-se opertors using leling exhiit goo logil properties: Proposition 4 Let σ e ny semntis. Any lelling-istne-se revision opertor L stisfies the rtionlity postultes (AE1) - (AE6). 9 6 Revision t the System Level The opertors efine in the previous setion fous on the nites tht re s lose s possile to the extensions of the input system. However, they o not inite how to generte the orresponing rgumenttion systems, i.e., the rgumenttion systems suh tht the union of their extensions oinies with the selete nites 4. In orer to o this jo, we onsier mpping AF σ from 2 2A to 2 AFs A, lle genertion opertor, tht ssoites with ny set C of nites set of rgumenttion systems suh tht Ext σ (AF σ (C)) = C. Oserve tht, whtever the semntis σ, suh mpping AF σ exists. This omes esily from the ft tht: Proposition 5 Whtever the semntis σ, for every non empty set C of nites from 2 A, suh tht C, there exists finite set S AFs A suh tht C = AF S Ext σ(af ). The point is tht every nite C n e ssoite with n rgumenttion system AF suh tht C is the unique σ-extension of it. For instne, if A = {,, } n C = {, }, AF given y R = {(, ), (, )} oes the jo whtever the semntis σ. This metho llows to prove tht set of systems exists, 4 The onstrution of systems from lellings is still n open question, this setion only els with genertion of systems from nites.

10 10 ut it oes not stuy the genertion of miniml set of systems orresponing to the nites. We give first pproh to this prolem in the rest. On this groun, revision opertors n then e efine s follows: Definition 9 Given semntis σ, fithful ssignment tht mthes every rgumenttion system to totl pre-orer σ AF, n genertion opertor AF σ, the orresponing si revision opertor is efine y: AF ϕ = AF σ (min(a ϕ, σ AF )) One of the key results of the pper is tht: Proposition 6 Every si revision opertor stisfies the postultes (AE1)- (AE6). Bsi opertors el only with minimlity of hnge of rguments sttus. Inee, the rtionlity postultes sks for preserving s muh s possile the sttus of rguments in the input system: oing so while ensuring tht the revision formul is stisfie oes not usully imply miniml hnge of the ttk reltion, n vie-vers. As mtter of illustrtion, onsier the rgumenttion systems AF 7, AF 8, AF 9, n AF 10 represente respetively in Figure 3., 3., 3., 3.. e (3.) e (3.) e (3.) e (3.) Fig. 3. Miniml Chnge Suppose tht our gol is to rejet e, tht is to get system so tht e oes not pper in ny extension. We onsier the revision formul ϕ = e. A miniml hnge on the ttk reltion of AF 7 les to AF 8 or AF 9 : eh of them iffers with AF 7 on single ttk. This ontrsts with AF 10 sine the hnge on the ttk reltion require to go from AF 7 to AF 10 is stritly greter thn the hnge on the ttk reltion require to go from AF 7 to AF 9. Eh of these four systems hs unique extension whtever the semntis: {,, e} for AF 7, {,, } for AF 8, n {, } for AF 9 n AF 10. Hene, the hnge on the sttus of rguments hieve when going from AF 7 to AF 9 or AF 10 is stritly smller thn the hnge on the sttus of rguments hieve when going from AF 7 to AF 8. A simple genertion opertor AF σ onsists in generting sets S of inresing rinlity n until the onition C = AF S Ext σ(af ) is stisfie n then returns the union of ll the miniml-size S whih stisfies it. However, using this simple genertion opertor oes not ensure to otin n optiml set of rgumenttion systems, when optimlity is unerstoo either s the miniml

11 11 numer of rgumenttion systems require to generte the nites, or s miniml hnge of the ttk reltion. Minimizing the hnge of the ttk reltion n nevertheless e tken into ount in the efinition of the genertion opertor (hene s seon riterion, with smller priority thn the riterion pturing the miniml hnge of the rguments sttus.) This n e esily one y onsiering istne g on the rgumenttion grphs. One simple exmple is the Hmming istne, given y g H (AF 1, AF 2 ) = (R 1 \ R 2 ) (R 2 \ R 1 ). But one n lso hoose more elorte eition istnes suh s those given in [8]. The g H istne etween two rgumenttion systems orrespons to the numer of ttks tht must e e or remove to mke them ientil. Eh istne g inues pre-orer etween rgumenttion systems, efine y AF 1 g AF AF 2 iff g(af 1, AF ) g(af 2, AF ). This pre-orer n e use to filter out unneessry rgumenttion systems proue y the genertion opertor. However, simple minimiztion w.r.t. g AF of the output of the genertion opertor is not suffiient in generl, s illustrte y the following exmple: Exmple 2 Suppose tht the nites re C = {C 1, C 2 }, n the genertion opertor AF σ pplie on C gives AF σ (C) = {AF 11, AF 12 } so tht, for the onsiere semntis σ, Ext σ (AF 11 ) = {C 1 } n Ext σ (AF 12 ) = {C 2 }. If AF 11 n AF 12 re not t equl istne from the input system AF (tht is AF 11 < AF AF 12 or AF 12 < AF AF 11 ), one of the systems is not miniml n must e remove. So n extension is lost. To tkle this prolem, we onsier seletion funtions removing rgumenttion systems when this oes not hnge the set of extensions: Definition 10 Given semntis σ, set of nites C, pre-orer AF n genertion opertor AF σ, let us efine the C-minimum-over seletion funtion γ C y: γ C (AF σ (C)) AF σ (C) Ext σ (γ C (AF σ (C))) = Ext σ (AF σ (C)) AF AF σ (C) n AF γ C (AF σ (C)) only if AF AF σ (C) so tht AF < AF AF Bse on this notion, full revision opertors n e efine s follows: Definition 11 Given semntis σ, fithful ssignment σ, AF, genertion opertor AF σ, pre-orer g AF over AFs A n C-minimum-over seletion funtion γ, the orresponing full revision opertor σ, AF, g AF,γ is efine y: AF σ, AF, g AF,γ ϕ = γ min(aϕ, σ, AF )(AF σ(min(a ϕ, σ, AF ))) Clerly full revision opertors re si revision opertors. Sine the minimiztion of the ttk reltion is one without moifying the selete nites, we get tht:

12 12 Proposition 7 Every full revision opertor σ, AF, g AF,γ stisfies the postultes (AE1)-(AE6). For illustrtion purposes, we now provie some exmples of revision opertors. For these exmples we will use the following C-minimum-over seletion funtion γ g AF 1 : V is n orere list efine from AF σ (C) y sorting it in esening orer 5 w.r.t. g AF. For i from 1 to n o if V j V s.t. V j < g AF V i n Ext σ (V \V i ) = Ext σ (V ), then V := V \V i. γ g AF 1 := V. With this metho, the systems remove from V re those whih re the frthest from the input AF. Fig. 4. The system AF 13 Let us now illustrte those onepts y onsiering the revision of the rgumenttion system AF 13 represente t Figure 4, using the full revision opertor efine from the Hmming istne etween nites, the Hmming istne etween grphs n the previous seletion funtion γ g AF 1. The set of extensions of AF 13 is {{, }} for the preferre n stle semntis, n its groune extension is. Hene, whtever the hosen semntis, we hve AF 13. Suppose now tht we wnt to e epte, so we mke revision with ϕ =. For the preferre semntis n the stle semntis, we first uil the set of nites whih stisfy so tht the Hmming istne with {{, }} is miniml. This set is {{,, }}. Then we uil the rgumenttion systems whih over this nite, fousing on those whih re t miniml istne to AF 13. The result is AF 14, given t Figure 5.. (5.) (5.) Fig. 5. The result of the revision of AF 13 y 5 There exists severl orere lists, epening on the wy to sort elements whih re equls w.r.t. the pre-orer. We hoose ritrrily one of these lists.

13 13 We proee similrly for the groune semntis: the set of extensions {{}} is first ompute, n then the unique system, AF 15, represente on Figure 5. is generte. A lst point we woul like to isuss is the ft tht si revision opertor outputs set of rgumenttion systems, n not single rgumenttion system in the generl se. Atully, this is onsequene of the expressiveness of the lnguge of revision formule we wnt to onsier. In orer to illustrte it, onsier A = {,,, }, n AF 16 s represente in Figure 6. Fig. 6. The system AF 16 (7.) (7.) Fig. 7. Revision of AF 16 The extensions of AF 16 re the sme for the groune, stle n preferre semntis, Ext(AF 16 ) = {{, }}. Let ϕ =. Oserve tht n ply symmetri roles, oth in AF 16 n in ϕ. When omputing the result of the revision with the full revision opertor se on Hmming istne etween nites, Hmming istne on the grph n the seletion funtion γ g AF 1, we otin two nites {,, } n {,, }, n two orresponing rgumenttion systems AF 17 n AF 18 (given respetively t Figure 7. n Figure 7.). Choosing one of these systems woul require to ept some ritrriness given the symmetri roles of n. Finlly, few wors out the itertion issue for revision. Given tht the output of revision opertor is not single system in the generl se ut set of suh systems, revision nnot e iretly iterte. Nevertheless, it is esy to exten revision opertors so tht sets of rgumenttion systems n e epte s input. Bsilly, S = {AF 1,..., AF n } ϕ n e efine s AF i S AF AF i ϕ AF. 7 Relte Work Some previous works hve lrey onsiere the hnge issue for rgumenttion systems à l Dung.

14 14 Thus, Boell, Ki n Vn er Torre, [9,10] hve stuie strtion n refinement priniples. An strtion is reution of the ttk reltion or the set of rguments, wheres refinement is the ition of ttks or rguments to the system. The uthors fouse on the stuy of semntis whih ensure the existene of unique extension (for instne, the groune extension), n they formulte some priniples of the form if we o this prtiulr hnge, then the extension of the result is like this. They ientifie some priniples stisfie y the groune semntis. Cyrol, Dupin e Sint-Cyr n Lgsquie-Shiex [11] stuie the ition of n rgument to n rgumenttion system. They stte some properties tht n e stisfie when hnge ours in n rgumenttion system, n pointe out those whih re stisfie (n uner whih onitions) when n rgument (n the ttks onerning it) is e to the grph. With Bisquert, they i similr stuy out the eletion of n rgument [12]. Bumnn [13] lso stuie the miniml hnge prolem in strt rgumenttion. He reporte some ouns on the numer of moifitions to mke on n rgumenttion system so s to enfore given set of rguments. These ouns epen on the semntis n the type of hnge llowe. All these works re silly onerne y the moifition of the ttk reltion. As suh, they iffer in signifint wy from the hnge prolem s stuie in this pper, where hnge primrily lies on the sttus of rguments (n seonry only on the ttk reltion.) 8 Conlusion In this pper, we investigte the revision prolem for strt rgumenttion systems à l Dung. We fouse on revision s miniml hnge of the rguments sttus. We introue lnguge of revision formule whih is expressive enough for enling the representtion of omplex onitions on the eptility of rguments in the revise system. We showe how AGM elief revision postultes n e trnslte to the se of rgumenttion systems. We provie orresponing representtion theorem in terms of miniml hnge of the rguments sttus, n pointe out severl istne-se revision opertors stisfying the postultes. As future work we first pln to enoe our revision opertors y representing rgumenttion systems with logil onstrints (in similr wy to Besnr n Doutre [14]), so s to e le to enefit from the power of onstrint solvers to ompute revise systems. The stuy of other hnge opertions on rgumenttion systems is nother perspetive for further reserh. Moreover, the ssoition of miniml set of rgumenttion systems to set of nites is very interesting, inluing for other pplitions thn revision. So we n eepen this question. The sme question for the se of lellings (see Exmple 1) is still open n will e stuie.

15 15 Referenes 1. Dung, P.M.: On the eptility of rguments n its funmentl role in nonmonotoni resoning, logi progrmming, n n-person gmes. Artifiil Intelligene 77(2) (1995) Gärenfors, P.: Knowlege In Flux. Cmrige University Press, Cmrige, UK (1988) 3. Griellini, S., Torroni, P.: MS Dilogues: Persuing n getting persue, A moel of soil network etes tht reoniles rguments n trust. (2013) 4. Alhourrón, C.E., Gärenfors, P., Mkinson, D.: On the logi of theory hnge : Prtil meet ontrtion n revision funtions. Journl of Symoli Logi 50 (1985) Ktsuno, H., Menelzon, A.O.: Propositionl knowlege se revision n miniml hnge. Artifiil Intelligene 52 (1991) Qi, G., Liu, W., Bell, D.A.: Knowlege se revision in esription logis. In: Proeeings of the Europen Conferene on Logis in Artifiil Intelligene (JELIA 06). Volume 4160 of Leture Notes in Computer Siene., Springer (2006) Cmin, M.: On the issue of reinsttement in rgumenttion. In: Proeeings of the Europen Conferene on Logis in Artifiil Intelligene (JELIA 06), Springer (2006) Coste-Mrquis, S., Devre, C., Koniezny, S., Lgsquie-Shiex, M.C., Mrquis, P.: On the merging of Dung s rgumenttion systems. Artifiil Intelligene Journl 171 (2007) Boell, G., Ki, S., vn er Torre, L.: Dynmis in rgumenttion with single extensions: ttk refinement n the groune extension. In: Proeeings of the Interntionl Conferene on Autonomous Agents n Multigents Systems (AA- MAS 09). (2009) Boell, G., Ki, S., vn er Torre, L.: Dynmis in rgumenttion with single extensions: Astrtion priniples n the groune extension. In: Proeeings of the Europen Conferenes on Symoli n Quntittive Approhes to Resoning with Unertinty (ECSQARU 09). Volume 5590 of Leture Notes in Computer Siene., Springer (2009) Cyrol, C., e Sint-Cyr, F.D., Lgsquie-Shiex, M.C.: Chnge in strt rgumenttion frmeworks: Aing n rgument. Journl of Artifiil Intelligene Reserh 38 (2010) Bisquert, P., Cyrol, C., e Sint-Cyr, F.D., Lgsquie-Shiex, M.C.: Chnge in rgumenttion systems: Exploring the interest of removing n rgument. In: Proeeings of the Interntionl Conferene on Slle Unertinty Mngement (SUM 11). Volume 6929 of Leture Notes in Computer Siene., Springer (2011) Bumnn, R.: Wht oes it tke to enfore n rgument? miniml hnge in strt rgumenttion. In: Proeeings of the Europen Conferene on Artifiil Intelligene (ECAI 12). (2012) Besnr, P., Doutre, S.: Cheking the eptility of set of rguments. In: Proeeings of the 10th Interntionl Workshop on Non-Monotoni Resoning (NMR 04). (2004) 59 64

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

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

Lecture 6: Coding theory

Lecture 6: Coding theory Leture 6: Coing theory Biology 429 Crl Bergstrom Ferury 4, 2008 Soures: This leture loosely follows Cover n Thoms Chpter 5 n Yeung Chpter 3. As usul, some of the text n equtions re tken iretly from those

More information

Solutions to Problem Set #1

Solutions to Problem Set #1 CSE 233 Spring, 2016 Solutions to Prolem Set #1 1. The movie tse onsists of the following two reltions movie: title, iretor, tor sheule: theter, title The first reltion provies titles, iretors, n tors

More information

Logic, Set Theory and Computability [M. Coppenbarger]

Logic, Set Theory and Computability [M. Coppenbarger] 14 Orer (Hnout) Definition 7-11: A reltion is qusi-orering (or preorer) if it is reflexive n trnsitive. A quisi-orering tht is symmetri is n equivlene reltion. A qusi-orering tht is nti-symmetri is n orer

More information

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106

18.06 Problem Set 4 Due Wednesday, Oct. 11, 2006 at 4:00 p.m. in 2-106 8. Problem Set Due Wenesy, Ot., t : p.m. in - Problem Mony / Consier the eight vetors 5, 5, 5,..., () List ll of the one-element, linerly epenent sets forme from these. (b) Wht re the two-element, linerly

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

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

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

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

Mid-Term Examination - Spring 2014 Mathematical Programming with Applications to Economics Total Score: 45; Time: 3 hours

Mid-Term Examination - Spring 2014 Mathematical Programming with Applications to Economics Total Score: 45; Time: 3 hours Mi-Term Exmintion - Spring 0 Mthemtil Progrmming with Applitions to Eonomis Totl Sore: 5; Time: hours. Let G = (N, E) e irete grph. Define the inegree of vertex i N s the numer of eges tht re oming into

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

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

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

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

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

SOME INTEGRAL INEQUALITIES FOR HARMONICALLY CONVEX STOCHASTIC PROCESSES ON THE CO-ORDINATES

SOME INTEGRAL INEQUALITIES FOR HARMONICALLY CONVEX STOCHASTIC PROCESSES ON THE CO-ORDINATES Avne Mth Moels & Applitions Vol3 No 8 pp63-75 SOME INTEGRAL INEQUALITIES FOR HARMONICALLY CONVE STOCHASTIC PROCESSES ON THE CO-ORDINATES Nurgül Okur * Imt Işn Yusuf Ust 3 3 Giresun University Deprtment

More information

CIT 596 Theory of Computation 1. Graphs and Digraphs

CIT 596 Theory of Computation 1. Graphs and Digraphs CIT 596 Theory of Computtion 1 A grph G = (V (G), E(G)) onsists of two finite sets: V (G), the vertex set of the grph, often enote y just V, whih is nonempty set of elements lle verties, n E(G), the ege

More information

The DOACROSS statement

The DOACROSS statement The DOACROSS sttement Is prllel loop similr to DOALL, ut it llows prouer-onsumer type of synhroniztion. Synhroniztion is llowe from lower to higher itertions sine it is ssume tht lower itertions re selete

More information

CSE 332. Sorting. Data Abstractions. CSE 332: Data Abstractions. QuickSort Cutoff 1. Where We Are 2. Bounding The MAXIMUM Problem 4

CSE 332. Sorting. Data Abstractions. CSE 332: Data Abstractions. QuickSort Cutoff 1. Where We Are 2. Bounding The MAXIMUM Problem 4 Am Blnk Leture 13 Winter 2016 CSE 332 CSE 332: Dt Astrtions Sorting Dt Astrtions QuikSort Cutoff 1 Where We Are 2 For smll n, the reursion is wste. The onstnts on quik/merge sort re higher thn the ones

More information

CSC2542 State-Space Planning

CSC2542 State-Space Planning CSC2542 Stte-Spe Plnning Sheil MIlrith Deprtment of Computer Siene University of Toronto Fll 2010 1 Aknowlegements Some the slies use in this ourse re moifitions of Dn Nu s leture slies for the textook

More information

Unfoldings of Networks of Timed Automata

Unfoldings of Networks of Timed Automata Unfolings of Networks of Time Automt Frnk Cssez Thoms Chtin Clue Jr Ptrii Bouyer Serge H Pierre-Alin Reynier Rennes, Deemer 3, 2008 Unfolings [MMilln 93] First efine for Petri nets Then extene to other

More information

Lecture 2: Cayley Graphs

Lecture 2: Cayley Graphs Mth 137B Professor: Pri Brtlett Leture 2: Cyley Grphs Week 3 UCSB 2014 (Relevnt soure mteril: Setion VIII.1 of Bollos s Moern Grph Theory; 3.7 of Gosil n Royle s Algeri Grph Theory; vrious ppers I ve re

More information

Surds and Indices. Surds and Indices. Curriculum Ready ACMNA: 233,

Surds and Indices. Surds and Indices. Curriculum Ready ACMNA: 233, Surs n Inies Surs n Inies Curriulum Rey ACMNA:, 6 www.mthletis.om Surs SURDS & & Inies INDICES Inies n surs re very losely relte. A numer uner (squre root sign) is lle sur if the squre root n t e simplifie.

More information

Lecture 8: Abstract Algebra

Lecture 8: Abstract Algebra Mth 94 Professor: Pri Brtlett Leture 8: Astrt Alger Week 8 UCSB 2015 This is the eighth week of the Mthemtis Sujet Test GRE prep ourse; here, we run very rough-n-tumle review of strt lger! As lwys, this

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

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of:

22: Union Find. CS 473u - Algorithms - Spring April 14, We want to maintain a collection of sets, under the operations of: 22: Union Fin CS 473u - Algorithms - Spring 2005 April 14, 2005 1 Union-Fin We wnt to mintin olletion of sets, uner the opertions of: 1. MkeSet(x) - rete set tht ontins the single element x. 2. Fin(x)

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

Maximum size of a minimum watching system and the graphs achieving the bound

Maximum size of a minimum watching system and the graphs achieving the bound Mximum size of minimum wthing system n the grphs hieving the oun Tille mximum un système e ontrôle minimum et les grphes tteignnt l orne Dvi Auger Irène Chron Olivier Hury Antoine Lostein 00D0 Mrs 00 Déprtement

More information

Lecture 11 Binary Decision Diagrams (BDDs)

Lecture 11 Binary Decision Diagrams (BDDs) C 474A/57A Computer-Aie Logi Design Leture Binry Deision Digrms (BDDs) C 474/575 Susn Lyseky o 3 Boolen Logi untions Representtions untion n e represente in ierent wys ruth tle, eqution, K-mp, iruit, et

More information

Now we must transform the original model so we can use the new parameters. = S max. Recruits

Now we must transform the original model so we can use the new parameters. = S max. Recruits MODEL FOR VARIABLE RECRUITMENT (ontinue) Alterntive Prmeteriztions of the pwner-reruit Moels We n write ny moel in numerous ifferent ut equivlent forms. Uner ertin irumstnes it is onvenient to work with

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

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

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

Particle Physics. Michaelmas Term 2011 Prof Mark Thomson. Handout 3 : Interaction by Particle Exchange and QED. Recap

Particle Physics. Michaelmas Term 2011 Prof Mark Thomson. Handout 3 : Interaction by Particle Exchange and QED. Recap Prtile Physis Mihelms Term 2011 Prof Mrk Thomson g X g X g g Hnout 3 : Intertion y Prtile Exhnge n QED Prof. M.A. Thomson Mihelms 2011 101 Rep Working towrs proper lultion of ey n sttering proesses lnitilly

More information

Common intervals of genomes. Mathieu Raffinot CNRS LIAFA

Common intervals of genomes. Mathieu Raffinot CNRS LIAFA Common intervls of genomes Mthieu Rffinot CNRS LIF Context: omprtive genomis. set of genomes prtilly/totlly nnotte Informtive group of genes or omins? Ex: COG tse Mny iffiulties! iology Wht re two similr

More information

A Disambiguation Algorithm for Finite Automata and Functional Transducers

A Disambiguation Algorithm for Finite Automata and Functional Transducers A Dismigution Algorithm for Finite Automt n Funtionl Trnsuers Mehryr Mohri Cournt Institute of Mthemtil Sienes n Google Reserh 51 Merer Street, New York, NY 1001, USA Astrt. We present new ismigution lgorithm

More information

arxiv: v2 [math.co] 31 Oct 2016

arxiv: v2 [math.co] 31 Oct 2016 On exlue minors of onnetivity 2 for the lss of frme mtrois rxiv:1502.06896v2 [mth.co] 31 Ot 2016 Mtt DeVos Dryl Funk Irene Pivotto Astrt We investigte the set of exlue minors of onnetivity 2 for the lss

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

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

Monochromatic Plane Matchings in Bicolored Point Set

Monochromatic Plane Matchings in Bicolored Point Set CCCG 2017, Ottw, Ontrio, July 26 28, 2017 Monohromti Plne Mthings in Biolore Point Set A. Krim Au-Affsh Sujoy Bhore Pz Crmi Astrt Motivte y networks interply, we stuy the prolem of omputing monohromti

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

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx

for all x in [a,b], then the area of the region bounded by the graphs of f and g and the vertical lines x = a and x = b is b [ ( ) ( )] A= f x g x dx Applitions of Integrtion Are of Region Between Two Curves Ojetive: Fin the re of region etween two urves using integrtion. Fin the re of region etween interseting urves using integrtion. Desrie integrtion

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

If the numbering is a,b,c,d 1,2,3,4, then the matrix representation is as follows:

If the numbering is a,b,c,d 1,2,3,4, then the matrix representation is as follows: Reltions. Solutions 1. ) true; ) true; ) flse; ) true; e) flse; f) true; g) flse; h) true; 2. 2 A B 3. Consier ll reltions tht o not inlue the given pir s n element. Oviously, the rest of the reltions

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

Factorising FACTORISING.

Factorising FACTORISING. Ftorising FACTORISING www.mthletis.om.u Ftorising FACTORISING Ftorising is the opposite of expning. It is the proess of putting expressions into rkets rther thn expning them out. In this setion you will

More information

CS261: A Second Course in Algorithms Lecture #5: Minimum-Cost Bipartite Matching

CS261: A Second Course in Algorithms Lecture #5: Minimum-Cost Bipartite Matching CS261: A Seon Course in Algorithms Leture #5: Minimum-Cost Biprtite Mthing Tim Roughgren Jnury 19, 2016 1 Preliminries Figure 1: Exmple of iprtite grph. The eges {, } n {, } onstitute mthing. Lst leture

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

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

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 Skeptil Rtionl Extensions Artur Mikitiuk nd Miros lw Truszzynski University of Kentuky, Deprtment of Computer Siene, Lexington, KY 40506{0046, frtur mirekg@s.engr.uky.edu Astrt. In this pper we propose

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

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

Separable discrete functions: recognition and sufficient conditions

Separable discrete functions: recognition and sufficient conditions Seprle isrete funtions: reognition n suffiient onitions Enre Boros Onřej Čepek Vlimir Gurvih Novemer 21, 217 rxiv:1711.6772v1 [mth.co] 17 Nov 217 Astrt A isrete funtion of n vriles is mpping g : X 1...

More information

On a Class of Planar Graphs with Straight-Line Grid Drawings on Linear Area

On a Class of Planar Graphs with Straight-Line Grid Drawings on Linear Area Journl of Grph Algorithms n Applitions http://jg.info/ vol. 13, no. 2, pp. 153 177 (2009) On Clss of Plnr Grphs with Stright-Line Gri Drwings on Liner Are M. Rezul Krim 1,2 M. Siur Rhmn 1 1 Deprtment of

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

The vertex leafage of chordal graphs

The vertex leafage of chordal graphs The vertex lefge of horl grphs Steven Chplik, Jurj Stho b Deprtment of Physis n Computer Siene, Wilfri Lurier University, 75 University Ave. West, Wterloo, Ontrio N2L 3C5, Cn b DIMAP n Mthemtis Institute,

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

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

= 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

CARLETON UNIVERSITY. 1.0 Problems and Most Solutions, Sect B, 2005

CARLETON UNIVERSITY. 1.0 Problems and Most Solutions, Sect B, 2005 RLETON UNIVERSIT eprtment of Eletronis ELE 2607 Swithing iruits erury 28, 05; 0 pm.0 Prolems n Most Solutions, Set, 2005 Jn. 2, #8 n #0; Simplify, Prove Prolem. #8 Simplify + + + Reue to four letters (literls).

More information

SEMI-EXCIRCLE OF QUADRILATERAL

SEMI-EXCIRCLE OF QUADRILATERAL JP Journl of Mthemtil Sienes Volume 5, Issue &, 05, Pges - 05 Ishn Pulishing House This pper is ville online t http://wwwiphsiom SEMI-EXCIRCLE OF QUADRILATERAL MASHADI, SRI GEMAWATI, HASRIATI AND HESY

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

Automata and Regular Languages

Automata and Regular Languages Chpter 9 Automt n Regulr Lnguges 9. Introution This hpter looks t mthemtil moels of omputtion n lnguges tht esrie them. The moel-lnguge reltionship hs multiple levels. We shll explore the simplest level,

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

Undecidability for arbitrary public announcement logic

Undecidability for arbitrary public announcement logic Uneiility for ritrry puli nnounement logi Tim Frenh n Hns vn Ditmrsh strt. Aritrry puli nnounement logi (AP AL) is n extension of multi-gent epistemi logi tht llows gents knowlege sttes to e upte y the

More information

I 3 2 = I I 4 = 2A

I 3 2 = I I 4 = 2A ECE 210 Eletril Ciruit Anlysis University of llinois t Chigo 2.13 We re ske to use KCL to fin urrents 1 4. The key point in pplying KCL in this prolem is to strt with noe where only one of the urrents

More information

CS 2204 DIGITAL LOGIC & STATE MACHINE DESIGN SPRING 2014

CS 2204 DIGITAL LOGIC & STATE MACHINE DESIGN SPRING 2014 S 224 DIGITAL LOGI & STATE MAHINE DESIGN SPRING 214 DUE : Mrh 27, 214 HOMEWORK III READ : Relte portions of hpters VII n VIII ASSIGNMENT : There re three questions. Solve ll homework n exm prolems s shown

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

Technology Mapping Method for Low Power Consumption and High Performance in General-Synchronous Framework

Technology Mapping Method for Low Power Consumption and High Performance in General-Synchronous Framework R-17 SASIMI 015 Proeeings Tehnology Mpping Metho for Low Power Consumption n High Performne in Generl-Synhronous Frmework Junki Kwguhi Yukihie Kohir Shool of Computer Siene, the University of Aizu Aizu-Wkmtsu

More information

On the Spectra of Bipartite Directed Subgraphs of K 4

On the Spectra of Bipartite Directed Subgraphs of K 4 On the Spetr of Biprtite Direte Sugrphs of K 4 R. C. Bunge, 1 S. I. El-Znti, 1, H. J. Fry, 1 K. S. Kruss, 2 D. P. Roerts, 3 C. A. Sullivn, 4 A. A. Unsiker, 5 N. E. Witt 6 1 Illinois Stte University, Norml,

More information

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point

Numbers and indices. 1.1 Fractions. GCSE C Example 1. Handy hint. Key point GCSE C Emple 7 Work out 9 Give your nswer in its simplest form Numers n inies Reiprote mens invert or turn upsie own The reiprol of is 9 9 Mke sure you only invert the frtion you re iviing y 7 You multiply

More information

Generalized Kronecker Product and Its Application

Generalized Kronecker Product and Its Application Vol. 1, No. 1 ISSN: 1916-9795 Generlize Kroneker Prout n Its Applition Xingxing Liu Shool of mthemtis n omputer Siene Ynn University Shnxi 716000, Chin E-mil: lxx6407@163.om Astrt In this pper, we promote

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

Analysis of Temporal Interactions with Link Streams and Stream Graphs

Analysis of Temporal Interactions with Link Streams and Stream Graphs Anlysis of Temporl Intertions with n Strem Grphs, Tiphine Vir, Clémene Mgnien http:// ltpy@ LIP6 CNRS n Soronne Université Pris, Frne 1/23 intertions over time 0 2 4 6 8,,, n for 10 time units time 2/23

More information

Subsequence Automata with Default Transitions

Subsequence Automata with Default Transitions Susequene Automt with Defult Trnsitions Philip Bille, Inge Li Gørtz, n Freerik Rye Skjoljensen Tehnil University of Denmrk {phi,inge,fskj}@tu.k Astrt. Let S e string of length n with hrters from n lphet

More information

Eigenvectors and Eigenvalues

Eigenvectors and Eigenvalues MTB 050 1 ORIGIN 1 Eigenvets n Eigenvlues This wksheet esries the lger use to lulte "prinipl" "hrteristi" iretions lle Eigenvets n the "prinipl" "hrteristi" vlues lle Eigenvlues ssoite with these iretions.

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

SOME COPLANAR POINTS IN TETRAHEDRON

SOME COPLANAR POINTS IN TETRAHEDRON Journl of Pure n Applie Mthemtis: Avnes n Applitions Volume 16, Numer 2, 2016, Pges 109-114 Aville t http://sientifivnes.o.in DOI: http://x.oi.org/10.18642/jpm_7100121752 SOME COPLANAR POINTS IN TETRAHEDRON

More information

Bounded single-peaked width and proportional representation 1

Bounded single-peaked width and proportional representation 1 Boune single-peke with n proportionl representtion 1 Denis Cornz, Luie Gln n Olivier Spnjr Astrt This pper is evote to the proportionl representtion (PR) prolem when the preferenes re lustere single-peke.

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

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

Outline Data Structures and Algorithms. Data compression. Data compression. Lossy vs. Lossless. Data Compression

Outline Data Structures and Algorithms. Data compression. Data compression. Lossy vs. Lossless. Data Compression 5-2 Dt Strutures n Algorithms Dt Compression n Huffmn s Algorithm th Fe 2003 Rjshekr Rey Outline Dt ompression Lossy n lossless Exmples Forml view Coes Definition Fixe length vs. vrile length Huffmn s

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

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

Deciding the Consistency of Branching Time Interval Networks

Deciding the Consistency of Branching Time Interval Networks Deiing the Consisteny of Brnhing Time Intervl Networks Mro Gvnelli Deprtment of Engineering University of Ferrr, Itly mro.gvnelli@unife.it https://ori.org/0000-0001-7433-5899 Alessnro Pssntino Deprtment

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

Graph Theory. Simple Graph G = (V, E). V={a,b,c,d,e,f,g,h,k} E={(a,b),(a,g),( a,h),(a,k),(b,c),(b,k),...,(h,k)}

Graph Theory. Simple Graph G = (V, E). V={a,b,c,d,e,f,g,h,k} E={(a,b),(a,g),( a,h),(a,k),(b,c),(b,k),...,(h,k)} Grph Theory Simple Grph G = (V, E). V ={verties}, E={eges}. h k g f e V={,,,,e,f,g,h,k} E={(,),(,g),(,h),(,k),(,),(,k),...,(h,k)} E =16. 1 Grph or Multi-Grph We llow loops n multiple eges. G = (V, E.ψ)

More information

COMPUTING THE QUARTET DISTANCE BETWEEN EVOLUTIONARY TREES OF BOUNDED DEGREE

COMPUTING THE QUARTET DISTANCE BETWEEN EVOLUTIONARY TREES OF BOUNDED DEGREE COMPUTING THE QUARTET DISTANCE BETWEEN EVOLUTIONARY TREES OF BOUNDED DEGREE M. STISSING, C. N. S. PEDERSEN, T. MAILUND AND G. S. BRODAL Bioinformtis Reserh Center, n Dept. of Computer Siene, University

More information

INTRODUCTION TO AUTOMATA THEORY

INTRODUCTION TO AUTOMATA THEORY Chpter 3 INTRODUCTION TO AUTOMATA THEORY In this hpter we stuy the most si strt moel of omputtion. This moel els with mhines tht hve finite memory pity. Setion 3. els with mhines tht operte eterministilly

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

XML and Databases. Exam Preperation Discuss Answers to last year s exam. Sebastian Maneth NICTA and UNSW

XML and Databases. Exam Preperation Discuss Answers to last year s exam. Sebastian Maneth NICTA and UNSW XML n Dtses Exm Prepertion Disuss Answers to lst yer s exm Sestin Mneth NICTA n UNSW CSE@UNSW -- Semester 1, 2008 (1) For eh of the following, explin why it is not well-forme XML (is WFC or the XML grmmr

More information

A Short Introduction to Self-similar Groups

A Short Introduction to Self-similar Groups A Short Introution to Self-similr Groups Murry Eler* Asi Pifi Mthemtis Newsletter Astrt. Self-similr groups re fsinting re of urrent reserh. Here we give short, n hopefully essile, introution to them.

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

Section 2.3. Matrix Inverses

Section 2.3. Matrix Inverses Mtri lger Mtri nverses Setion.. Mtri nverses hree si opertions on mtries, ition, multiplition, n sutrtion, re nlogues for mtries of the sme opertions for numers. n this setion we introue the mtri nlogue

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

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

Situation Calculus. Situation Calculus Building Blocks. Sheila McIlraith, CSC384, University of Toronto, Winter Situations Fluents Actions

Situation Calculus. Situation Calculus Building Blocks. Sheila McIlraith, CSC384, University of Toronto, Winter Situations Fluents Actions Plnning gent: single gent or multi-gent Stte: complete or Incomplete (logicl/probbilistic) stte of the worl n/or gent s stte of knowlege ctions: worl-ltering n/or knowlege-ltering (e.g. sensing) eterministic

More information

GNFA GNFA GNFA GNFA GNFA

GNFA GNFA GNFA GNFA GNFA DFA RE NFA DFA -NFA REX GNFA Definition GNFA A generlize noneterministic finite utomton (GNFA) is grph whose eges re lele y regulr expressions, with unique strt stte with in-egree, n unique finl stte with

More information

Computing the Quartet Distance between Evolutionary Trees in Time O(n log n)

Computing the Quartet Distance between Evolutionary Trees in Time O(n log n) Computing the Qurtet Distne etween Evolutionry Trees in Time O(n log n) Gerth Stølting Brol, Rolf Fgererg Christin N. S. Peersen Mrh 3, 2003 Astrt Evolutionry trees esriing the reltionship for set of speies

More information

Lecture 4: Graph Theory and the Four-Color Theorem

Lecture 4: Graph Theory and the Four-Color Theorem CCS Disrete II Professor: Pri Brtlett Leture 4: Grph Theory n the Four-Color Theorem Week 4 UCSB 2015 Through the rest of this lss, we re going to refer frequently to things lle grphs! If you hen t seen

More information