On Persistent Reachability in Petri Nets *

Size: px
Start display at page:

Download "On Persistent Reachability in Petri Nets *"

Transcription

1 On Persistent Rehility in Petri Nets * Kmil Brylsk 1, Łuksz Mikulski 1, Edwrd Ohmnski 1,2 1 Fulty of Mthemtis nd Computer Siene, Niolus Copernius University, Torun 2 Institute of Computer Siene, Polish Ademy of Sienes, Wrszw, Polnd {khm,frodo,edoh}@mtunitorunpl Astrt The notion of persisteny, sed on the rule no tion n disle nother one is one of the lssil notions in onurreny theory In this pper, we del with ritrry ple/trnsition nets, ut onentrte on their persistent omputtions It leds to n interesting deision prolem: Is given mrking rehle with persistent run? In order to study the persistent-rehility prolem we define lss of nets, lled nonviolene nets We show tht inhiitor nets n e simulted y the nonviolene nets, nd tht rehility nd overility prolems re undeidle in the lss of the nonviolene nets Then we prove more: nonviolene nets n e simulted y the inhiitor nets, thus they re omputtionlly equivlent to Turing mhines 1 Introdution An tion of onurrent system is sid to e persistent if, whenever it eomes enled, it remins enled until exeuted This lssil notion, introdued y Krp/Miller [9], is one of the most frequently disussed issues in the Petri net theory (ppers [1,2,3,6,8,11,12] mo) A net is sid to e persistent if eh of its tions is persistent And most of the ppers out persisteny del with this sulss of ple/trnsition nets) In this pper, we del with ritrry ple/trnsition nets, ut onentrte on their persistent omputtions It leds to n interesting persistentrehility prolems: Is given mrking rehle (overle) with persistent run? It is well known tht the lssil versions of the prolems (Is given mrking rehle (overle) in given ple/trnsition net?) re deidle (overility: Krp/Miller [9], Hk [8]; rehility: Myr [13], Kosrju [10]) In order to study the persistent-rehility prolem we introdue lss of nets, lled nonviolene nets (Definition 31) They differ from ple/trnsition nets only y the exeution rule Nmely, only persistent exeutions re permitted We show tht inhiitor nets n e simulted y nonviolene nets (Proposition 44) Using this ft we prove tht the rehility nd overility prolems re undeidle in the lss of the nonviolene nets (Propositions 45 nd 47, respetively) Then we prove more: nonviolene nets n e simulted y the inhiitor nets (Proposition 48), thus the oth re omputtionlly equivlent to Turing mhines * The reserh supported y Ministry of Siene nd Higher Edution of Polnd grnt N N Reent Advnes in Petri Nets nd Conurreny, S Dontelli, J Kleijn, RJ Mhdo, JM Fernndes (eds), CEUR Workshop Proeedings, ISSN , Jn/2012, pp

2 374 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski Mny extensions of Petri nets re known to e Turing powerful: inhiitor nets, priority nets (Hk [7]), self-modifying nets (Vlk [17]), for instne There is lso Turing powerful model restriting the stndrd exeution rules to mximl onurrent steps (Burkhrd [4], see lso Strke [16]) But ll the models llow fight for shring resoures (tokens), wheres our model works in ompletely peeful wy In the onluding setion we notie tht the free-hoie nonviolene nets re esy trnsformle to ple/trnsition nets (not neessrily free-hoie ones) Hene, the overility nd rehility prolems re deidle in the lss of the free-hoie nonviolene nets 2 Petri Nets Bsi Definitions The set of non-negtive integers is denoted y Given set X, the rdinlity (numer of elements) of X is denoted y X, the powerset (set of ll susets) y 2 X, the rdinlity of the powerset is 2 X Multisets over X re memers of X, ie funtions from X into For onveniene, if the set X is finite, multisets of X will e represented y vetors of X 21 Petri Nets nd Their Computtions The definitions onerning Petri nets re mostly sed on Desel/Reisig [5] Net is triple N = (P,T,F), where: P nd T re finite disjoint sets, of ples nd trnsitions, respetively; F P T T P is reltion, lled the flow reltion For ll T we denote: = {p P (p,) F} the set of entries to = {p P (,p) F} the set of exits from Petri nets dmit nturl grphil representtion Nodes represent ples nd trnsitions, rs represent the flow reltion Ples re depited y irles, nd trnsitions y oxes The set of ll finite strings of trnsitions is denoted y T*, the empty string is denoted y ε, the length of w T* is denoted y w, numer of ourrenes of trnsition in string w is denoted y w Ple/trnsition net (shortly, p/t-net) is qudruple S = (P,T,F,M 0 ), where: N = (P,T,F) is net, s defined ove; M 0 P is multiset of ples, nmed the initil mrking; it is mrked y tokens inside the irles, pity of ples is unlimited Multisets of ples re nmed mrkings In the ontext of ple/trnsition nets, they re mostly represented y nonnegtive integer vetors of dimension P, ssuming tht P is stritly ordered The nturl generliztions, for vetors, of rithmeti opertions + nd, s well s the prtil order, ll defined omponentwise, re well known nd their forml definitions re omitted

3 Persistent rehility Petri Nets & Conurreny 375 A trnsition T is enled in mrking M whenever M (ll its entries re mrked) If is enled in M, then it n e exeuted, ut the exeution is not fored The exeution of trnsition hnges the urrent mrking M to the new mrking M'=(M )+ (tokens re removed from entries, then put to exits) We shll denote: M for is enled in M nd MM' for is enled in M nd M' is the resulting mrking Then we sy tht MM' is step This denottion we extend to strings of trnsitions: the empty string ε is enled in ny mrking (lwys MεM), string w=u ( T, u T*) is enled in mrking M whenever MM' nd u is enled in M' Predites Mw nd MwM' re defined like those for single trnsitions If MwM' then we sy tht MwM' is omputtion from M to M' Note tht ny omputtion MwM' unmiguously defines ll intermedite mrkings etween M nd M' If MwM', for some w T*, then M' is sid to e rehle from M The set of ll mrkings rehle from M is denoted y [M Given ple/trnsition net S=(P,T,F,M 0 ), the set [M 0 of ll mrkings rehle from the initil mrking M 0 is lled the rehility set of S, nd mrkings in [M 0 re sid to e rehle in S We ssume tht the notions of rehility nd overility grphs re known to the reder Their definitions n e found in ny monogrph or survey out Petri nets (see [5,16] or ritrry else) Let us rell only tht rehility grphs represent ompletely ehviours of nets, ut re mostly infinite, while overility grphs represent ehviours only prtilly, ut re lwys finite In Exmples 22 nd 23 we lso use notion of persisteny grph the rehility grph restrited to persistent steps 22 Persistent Computtions of Ple/Trnsition Nets The notion of persisteny, proposed y Krp/Miller [9], elongs to the most importnt notions in onurreny theory It is sed on the ehviourlly oriented rule no tion n disle nother one, nd generlizes the struturlly defined notion of onflitfreeness Let S=(P,T,F,M 0 ) e ple/trnsition net, nd let M e mrking The step MM' is persistent iff ( ) if M then M' The empty omputtion MεM is persistent; the omputtion MM'uM" is persistent iff the step MM' is persistent nd the omputtion M'uM" is persistent [In words: A omputtion is sid to e persistent if ny trnsition one enled during this omputtion remins enled until exeuted] A p/t net is sid to e persistent if it dmits only persistent omputtions

4 376 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski Exmple 21 Non-persistent nd persistent nets Fig 1 A non-persistent (left) nd persistent (right) ple/trnsition nets 23 Persistent Rehility Prolem The prolem of persisteny ( Is ple/trnsition net persistent? ), rised y Lndweer nd Roertson in [11], hs een proved to e deidle y Growski [6] nd Myr [12] Most of p/t-nets, however, re not persistent, ut some of their omputtions re persistent In this pper, we re interested in mrkings tht re rehle with persistent omputtions Let S=(P,T,F,M 0 ) e ple/trnsition net, nd let M P e mrking Rehility Prolem: Is there omputtion M 0 wm? In other words: Is the mrking M rehle in the net S? The Rehility Prolem hs een proved to e deidle y Myr [13] nd Kosrju [10], fter yers of mny uthor s efforts A rod disussion, with detiled proof, n e found in the ook [15] of Reutenuer Let S=(P,T,F,M 0 ) e ple/trnsition net, nd let M P e mrking Persistent-Rehility Prolem: Is there persistent omputtion M 0 wm? In other words: Is the mrking M rehle in the net S with persistent run? Oviously, if p/t-net is persistent, then the persistent-rehility prolem is equivlent to the lssil one, thus deidle We shll study the prolem in generl, for ritrry p/t-nets The following exmples show differene etween omplete ehviours nd persistent ehviours

5 Persistent rehility Petri Nets & Conurreny 377 Exmple 22 Comprison of the omplete nd persistent ehviours d d d d 0-2 Fig 2 A ple/trnsition net nd its rehility nd persisteny grphs The ove net is ounded (ie its rehility set is finite) nd hs infinite set of persistent omputtions The exmple elow shows n unounded net (ie with infinite rehility set) with finite set ( singleton) of persistent omputtions Exmple 23 Unounded p/t-net with finite persisteny grph ω 1-0-ω ω Fig 3 A ple/trnsition net nd its rehility, overility nd persisteny grphs 3 Nonviolene Petri Nets In this setion, we introdue the notion of nonviolene Petri nets They differ from ple/trnsition nets only y the exeution rule Nmely, n enled trnsition n e exeuted only if it is exeutle persistently (ie if its exeution does not disle ny other enled trnsition) Therefore, we hve to distinguish the notion enled nd exeutle, tht re synonymi in ple/trnsition nets, ut not in nonviolene nets

6 378 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski Definition 31 Nonviolene Petri Nets Nonviolene net is qudruple S = (P,T,F,M 0 ), extly the sme s in definition of ple/trnsition nets It differs from p/t-net y exeution rules: A trnsition T is enled in mrking M whenever M (ll its entries re mrked) A trnsition T is exeutle in M if it is enled in M, nd moreover the step MM' is persistent The exeution of leds to the resulting mrking M'=(M )+ (extly sme s in p/tnets) We shll denote: M for is exeutle in M nd MM' for is exeutle in M nd M' is the resulting mrking Then we sy tht MM' is nonviolent step This denottion is nturlly extended to strings w T* If MwM' then we sy tht MwM' is nonviolent omputtion Only nonviolent steps nd omputtions re permitted in the nonviolene nets And now we n formulte the rehility nd overility prolems for the nonviolene nets Let S = (P,T,F,M 0 ) e nonviolene net, nd let M P e mrking NV-Rehility Prolem: Is there nonviolene omputtion M 0 wm in S? NV-Coverility Prolem: Is there mrking M' M nd nonviolene omputtion M 0 wm' in S? 32 From Ple/Trnsition Nets to Nonviolene Nets We shll show tht every p/t-net n e simulted y nonviolene net It will e done y joining n externl ontrol to eh trnsition of the net Let us onsider n ritrry p/t-net S We trnsform it to the nonviolene net S' in the following wy To eh trnsition in the net S we join swithing trnsition ' nd two new ples p nd q We dd the ple q to the set of entries to nd to the set of exits from ' We lso dd the ple p to the set of exits from nd to the set of entries to ' In initil mrking we dd one token to the ple p One n tret the onstruted loop s preprtion of the trnsition to exeution Net S: Net S': p ' Fig 4 Trnsforming ple/trnsition net into nonviolene net Let us lso define, for every mrking M in the net S, the mrking 10M in the net S' s follows For eh ple p in the net S we set 10M(p)=M(p), for eh new ple p we q

7 Persistent rehility Petri Nets & Conurreny 379 set 10M(p )=1 nd for eh new ple q we set 10M(q )=0 With suh definition, the initil mrking in the net S' is 10M 0, where M 0 is the initil mrking in S An ovious oservtion is tht if trnsition is exeutle in mrking M in the net S, then the sequene ' is exeutle in the mrking 10M in the net S' Proposition 32 A mrking M is rehle in ple/trnsition net S if nd only if the mrking 10M is rehle in the nonviolene net S' Proof ( ) Let M 0 wm e omputtion in S Then repling eh in w y ' we get omputtion 10M 0 w'10m in the nonviolene net S' ( ) Let 10M 0 w'10m in the nonviolene net S' The only differene etween ehviours of S nd S' is tht efore every trnsition trnsition ' must e exeuted Susequent exeution of two (or more) primed tions my sometimes disle the nonviolene exeution of tions tht were exeutle in S However, it would not mke ny new tion exeutle Therefore, ersing ll primed tions in w', we get omputtion w suh tht M 0 wm is omputtion in the p/t-net S 4 Comprison of Nonviolene Nets nd Inhiitor Nets In this setion, we rell the notion of inhiitor nets nd some of their properties (undeidility of the the rehility nd overility prolems) Then we show tht their omputtionl power is equl to tht of the nonviolene nets Definition 41 Inhiitor Petri Nets Inhiitor net is quintuple S = (P,T,F,I,M 0 ), where (P,T,F,M 0 ) is ple/trnsition net nd I P T is the set of inhiitor rs (depited y edges ended with smll empty irle) Sets of entries nd exits re denoted y nd, s in p/t-nets; the set of inhiitor entries to is denoted y ={p P (p,) I} A trnsition T is enled in mrking M whenever M (ll its entries re mrked) nd ( p ) M(p)= 0 ll inhiitor entries to re empty And exeutle mens enled, like in p/t-nets The exeution of leds to the resulting mrking M'= (M )+ It is known tht the inhiitor nets re omputtionlly equivlent to Turing mhines nd the rehility prolem in them is undeidle (Minsky [14], Hk [7]) Ft 42 Rehility Prolem is undeidle in the lss of inhiitor nets Also the overility prolem is known to e undeidle in the lss of inhiitor nets We rell here the proving onstrution Let S = (P,T,F,I,M 0 ) e n ritrry inhiitor net with P = {p 1,, p k }, nd let M = [i 1,, i k ] e mrking to e heked to e rehle We extend it to n inhiitor net S', s follows: We dd three new ples p 0, p k+1, p k+2 nd two new trnsitions x, y, onneted p 0 x p k+1 y p k+2 (see figure 5) Moreover, we join the

8 380 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski ple p 0 with every trnsition of the net S y self-loop (it is depited symolilly on Figure 5), we dd the rs from p n to x, weighted y i n (for n=1,,k), [We use here the weighted rs; see remrk elow] nd the inhiitory rs from ll originl ples of S to y And the initil mrking M' 0 in S' is the following: M' 0 (p 0 )=1, M' 0 (p n )=M 0 (p n ) for n=1,,k nd M' 0 (p k+1 )=M' 0 (p k+2 )=0 Net S: Net S': p 0 p 1 p k p 1 p k i 1 i k x y p k+1 p k+2 Fig 5 Cheking rehility with overility in inhiitor nets Remrk In this onstrution, we hve used weighted (multiple) rs They re not mentioned, for simpliity, in our definitions; we ssume tht the notion is ommonly known Moreover, (ple/trnsition or inhiitor) nets with multiple rs n e trnsformed to the equivlent nets without them (Hk [8], Strke [16]) Clerly, the mrking M = [i 1,, i k ] is rehle in S if nd only if the mrking M'(p 0 )=M'(p 1 )= =M'(p k )=M'(p k+1 )=0 nd M'(p k+2 )=1 is overle in S' Hene, euse of Ft 42, we hve got Ft 43 Coverility Prolem is undeidle in the lss of inhiitor nets 41 From Inhiitor Nets to Nonviolene Nets Let us onsider n ritrry inhiitor net S In the trnsformtion to the nonviolene net S' we will use the sme ide s in the previous trnsformtion Like in tht one, to eh trnsition, we dd trnsition ' nd ples p nd q Moreover, to eh ple p, in the net S, elonging to (ie eing n inhiitor entry to ), we dd new trnsition p Both ples, p nd q, re joined y self-loops with the new trnsition p Finlly, we remove ll inhiitor rs

9 Persistent rehility Petri Nets & Conurreny 381 Net S: Net S': p ' q p p p Fig 6 Trnsforming n inhiitor net into nonviolene net Similrly to the onstrution of figure 4, for every mrking M in the net S we define the mrking 10M in the net S', in the sme wy And the initil mrking in the net S' is 10M 0, where M 0 is the initil mrking in the net S In the sme mnner s in the previous se, if the trnsition is exeutle in the mrking M in the inhiitor net S, then the omputtion ' is exeutle in the mrking 10M in the nonviolene net S' Proposition 44 The mrking M is rehle in the inhiitor net S if nd only if the mrking 10M is rehle in the nonviolene net S' Proof The proof is similr to tht of Proposition 32 Remrk tht if n tion ' is exeuted while token resides in the ple p (so is not enled in S), then token will stuk in the ple q nd no mrking of the form 10M will e rehle Corollry 45 The NV-Rehility Prolem is undeidle Proof Diretly from Proposition 44 nd Ft 42 Proposition 46 The mrking M is overle in the inhiitor net S if nd only if the mrking 10M is overle in the nonviolene net S' Proof ( ) If M is overle in S then there is mrking M' M rehle in S Hene, y Proposition 44, the mrking 10M' is rehle in the nonviolene net S' And lerly, 10M' overs 10M ( ) Notie tht ny mrking (rehle in S') overing 10M is of the form 10M' And then M' M nd M' is rehle in S (Proposition 44) So M is overle in S Corollry 47 The NV-Coverility Prolem is undeidle Proof Diretly from Proposition 46 nd Ft 43

10 382 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski 42 From Nonviolene Nets to Inhiitor Nets The inverse onstrution, trnsforming nonviolene net into n inhiitor net, is more involved One more, we use the ide of prediting n exeutlement of trnsitions s Net S: Net S': ' q q x p 2 t q p p 2 t p y p Fig 7 Trnsforming nonviolene net into n inhiitor net Let S e nonviolene net; we extend it to n inhiitor net S', s follows First, we dd one glol ple s, lled the swith, whih is n exit from every trnsition of the net S Then, for every trnsition of the net S, we dd trnsition '; the swith ple s is n entry to eh of these primed trnsitions An exeution of trnsition ' mens elief in the exeutlement of trnsition in the nonviolene net S After exeuting the trnsition ', the net S' heks, if the trnsition ws relly exeutle in the nonviolene net S It mens tht trnsition is enled nd no other trnsition loks its exeution In order to hek it, we dd, for every pir (p,) suh tht nd the ple p is ommon entry to the trnsitions nd, the ples x p nd y p nd the trnsition t p, s depited on figure 7 ove The trnsition t p is le to move the token from x p to y p only if t lest two tokens reside in the ple p [We use here the weighted rs; see remrk fter figure 5] By the nonviolene rules, trnsition loks nothing if it is not enled; it mens tht one of its entries is empty In order to hek it, we dd the trnsitions t q, for every entry q to trnsition, different from p Eh of the trnsitions hs one entry x p, one exit y p nd one inhiitor r from the ple q, heking if q is empty This onstrution llows to hek, whether the trnsition loks the exeution of or not If not, then token moves from x p to y p, enling in S' if nd only if it ws exeutle in S For every mrking M in the nonviolene net S we define mrking 10M in the inhiitor net S' s follows For eh ple p inside the net S we set 10M(p)=M(p) For

11 Persistent rehility Petri Nets & Conurreny 383 dditionl swith ple s we set 10M(s)=1 nd for every ple r dded y the onstrution (ie for ll ples x p nd y p ) we set 10M(r)=0 Diretly from our onstrution, if trnsition is exeutle in mrking M in nonviolene net S then it is potentilly exeutle in the mrking 10M in inhiitor net S' (efore exeuting trnsition we exeute trnsition ' nd positively hek ll onditions to fill ll ples y p ) The initil mrking of S' is ssumed to e 10M 0 Proposition 48 The mrking M in the nonviolene net S is rehle if nd only if the mrking 10M is rehle in the inhiitor net S' Proof ( ) In the net S' we n reh mrking 10M, from the initil mrking 10M 0, y exeuting trnsition ' efore eh trnsition nd heking the onditions ( ) Exeuting ny trnsition from the originl net S is possile only y prediting this exeution y exeuting the trnsition ' If we do mistke, mking wrong predition, our net S' would reh ded mrking nd stops It mens tht if mrking 10M in the inhiitor net S' is rehle, then the only senrio of rehing tht mrking is orretly prediting nd exeuting trnsitions from the net S The orretness of our proess of prediting mens tht we ould just exeute these trnsitions in the originl, nonviolene net S, rehing mrking M Finlly, mrking M is rehle in the nonviolene net S, whih ends the proof Conlusions We hve proved (Propositions ) tht nonviolene nets re equivlent (in the mrking rehility sense) to inhiitor nets As the ltter re Turing powerful, one n sy tht the former llow to do everything wht possile without ny fight It is quite surprising, euse persistent exeutions re only prt of ritrry exeutions But the prie for the pee is undeidility We hve shown (Corollry 47) tht even overility, deidle in mny extensions of ple/trnsition nets, is undeidle in the lss of the nonviolene nets Notie tht free-hoie (if then = ) nonviolene nets n e simulted y ple/trnsition nets (Figure 8), thus the lssil deision prolems (rehility, overility) re deidle in the lss of free-hoie nonviolene nets Net S: Net S': 2 Fig 8 Trnsforming free-hoie nonviolene net into ple/trnsition net Let S e free-hoie nonviolene net We reple every r from ple, eing ommon entry of two (or more) trnsitions nd is not prt of self-loop, y two rs: n r from the ple to the trnsition, weighted with 2, nd n r from the

12 384 Petri Nets & Conurreny Brylsk, Mikulski, nd Ohmnski trnsition to the ple, weighted with 1 And self-loops remin not hnged And the initil mrking remins the sme Clerly, the ple/trnsition net S' uilt this wy works extly s the free-hoie nonviolene net S A se of the free-hoie nonviolene net is shown y Exmple 22 The ove onstrution does not work for non-free-hoie nonviolene nets, see Exmple 23, for instne It would e interesting to study some other sulsses of the lss of nonviolene nets Espeilly, to find sulss of the lss of nonviolene nets, omputtionlly equivlent to the lss of ple/trnsition nets Aknowledgments The pper ws inspired y the Exmple 22 Gret thnks re due to Ull Goltz, who relled to us tht very old exmple Referenes 1 E Best: A Note on Persistent Petri Nets Conurreny, Grphs nd Models, LNCS 5065, pp Springer E Best, P Drondeu: Deomposition Theorems for Bounded Persistent Petri Nets Petri Nets 2008, LNCS 5062, pp Springer E Best, P Drondeu: Seprility in Persistent Petri Nets Petri Nets 2010, LNCS 6128, pp Springer H-D Burkhrd: Ordered Firing in Petri Nets Elektronishe Informtionsverreitung und Kyernetik 17(2/3), pp 71-86, J Desel, W Reisig: Ple/Trnsition Petri Nets Letures on Petri Nets, LNCS 1491, pp Springer J Growski: The Deidility of Persistene for Vetor Addition Systems Informtion Proessing Letters 11(1), pp 20-23, M Hk: Petri Net Lnguges Report MIT 124, M Hk: Deidility Questions for Petri Nets Ph D Thesis, MIT RM Krp, RE Miller: Prllel progrm shemt JCSS 3, pp , SR Kosrju: Deidility of Rehility in Vetor Addition Systems Pro of the 14th Annul ACM Symposium on Theory of Computing, pp , LH Lndweer, EL Roertson: Properties of onflit-free nd persistent Petri nets Journl of ACM 25, pp , E Myr: Persistene of Vetor Replement Systems is Deidle At Informti 15, pp , E Myr: An lgorithm for the generl Petri net rehility prolem Pro of the 13th Annul ACM Symposium on Theory of Computing, pp , M Minsky: Computtion: Finite nd Infinite Mhines Prentie-Hll C Reutenuer: The Mthemtis of Petri Nets Prentie-Hll P H Strke: Petri-Netze VEB Berlin R Vlk: Self-Modifying Nets, Nturl Extension of Petri Nets ICALP 1978, LNCS 62, pp Springer 1978

Petri Nets. Rebecca Albrecht. Seminar: Automata Theory Chair of Software Engeneering

Petri Nets. Rebecca Albrecht. Seminar: Automata Theory Chair of Software Engeneering Petri Nets Ree Alreht Seminr: Automt Theory Chir of Softwre Engeneering Overview 1. Motivtion: Why not just using finite utomt for everything? Wht re Petri Nets nd when do we use them? 2. Introdution:

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

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

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

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

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

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

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

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

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

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

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

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

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

#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

Convert the NFA into DFA

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

More information

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

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

More information

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

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

1 From NFA to regular expression

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

More information

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

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

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

= 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

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

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

CS 373, Spring Solutions to Mock midterm 1 (Based on first midterm in CS 273, Fall 2008.)

CS 373, Spring Solutions to Mock midterm 1 (Based on first midterm in CS 273, Fall 2008.) CS 373, Spring 29. Solutions to Mock midterm (sed on first midterm in CS 273, Fll 28.) Prolem : Short nswer (8 points) The nswers to these prolems should e short nd not complicted. () If n NF M ccepts

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

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

Regular expressions, Finite Automata, transition graphs are all the same!!

Regular expressions, Finite Automata, transition graphs are all the same!! CSI 3104 /Winter 2011: Introduction to Forml Lnguges Chpter 7: Kleene s Theorem Chpter 7: Kleene s Theorem Regulr expressions, Finite Automt, trnsition grphs re ll the sme!! Dr. Neji Zgui CSI3104-W11 1

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

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

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

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

ANALYSIS AND MODELLING OF RAINFALL EVENTS

ANALYSIS AND MODELLING OF RAINFALL EVENTS Proeedings of the 14 th Interntionl Conferene on Environmentl Siene nd Tehnology Athens, Greee, 3-5 Septemer 215 ANALYSIS AND MODELLING OF RAINFALL EVENTS IOANNIDIS K., KARAGRIGORIOU A. nd LEKKAS D.F.

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

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

Behavior Composition in the Presence of Failure

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

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

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

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

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

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

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 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

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

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

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

1.3 SCALARS AND VECTORS

1.3 SCALARS AND VECTORS Bridge Course Phy I PUC 24 1.3 SCLRS ND VECTORS Introdution: Physis is the study of nturl phenomen. The study of ny nturl phenomenon involves mesurements. For exmple, the distne etween the plnet erth nd

More information

1 Nondeterministic Finite Automata

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

More information

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

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

Converting Regular Expressions to Discrete Finite Automata: A Tutorial

Converting Regular Expressions to Discrete Finite Automata: A Tutorial Converting Regulr Expressions to Discrete Finite Automt: A Tutoril Dvid Christinsen 2013-01-03 This is tutoril on how to convert regulr expressions to nondeterministic finite utomt (NFA) nd how to convert

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

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

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

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

Ling 3701H / Psych 3371H: Lecture Notes 9 Hierarchic Sequential Prediction

Ling 3701H / Psych 3371H: Lecture Notes 9 Hierarchic Sequential Prediction Ling 3701H / Psyh 3371H: Leture Notes 9 Hierrhi Sequentil Predition Contents 9.1 Complex events.................................... 1 9.2 Reognition of omplex events using event frgments................

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

First Midterm Examination

First Midterm Examination 24-25 Fll Semester First Midterm Exmintion ) Give the stte digrm of DFA tht recognizes the lnguge A over lphet Σ = {, } where A = {w w contins or } 2) The following DFA recognizes the lnguge B over lphet

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

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

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

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

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

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

More information

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

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

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

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

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

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

Can one hear the shape of a drum?

Can one hear the shape of a drum? Cn one her the shpe of drum? After M. K, C. Gordon, D. We, nd S. Wolpert Corentin Lén Università Degli Studi di Torino Diprtimento di Mtemti Giuseppe Peno UNITO Mthemtis Ph.D Seminrs Mondy 23 My 2016 Motivtion:

More information

CSCI 340: Computational Models. Kleene s Theorem. Department of Computer Science

CSCI 340: Computational Models. Kleene s Theorem. Department of Computer Science CSCI 340: Computtionl Models Kleene s Theorem Chpter 7 Deprtment of Computer Science Unifiction In 1954, Kleene presented (nd proved) theorem which (in our version) sttes tht if lnguge cn e defined y ny

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

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

First Midterm Examination

First Midterm Examination Çnky University Deprtment of Computer Engineering 203-204 Fll Semester First Midterm Exmintion ) Design DFA for ll strings over the lphet Σ = {,, c} in which there is no, no nd no cc. 2) Wht lnguge does

More information

Formal Languages and Automata

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

More information

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

12.1 Nondeterminism Nondeterministic Finite Automata. a a b ε. CS125 Lecture 12 Fall 2016

12.1 Nondeterminism Nondeterministic Finite Automata. a a b ε. CS125 Lecture 12 Fall 2016 CS125 Lecture 12 Fll 2016 12.1 Nondeterminism The ide of nondeterministic computtions is to llow our lgorithms to mke guesses, nd only require tht they ccept when the guesses re correct. For exmple, simple

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

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

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

Global alignment. Genome Rearrangements Finding preserved genes. Lecture 18

Global alignment. Genome Rearrangements Finding preserved genes. Lecture 18 Computt onl Biology Leture 18 Genome Rerrngements Finding preserved genes We hve seen before how to rerrnge genome to obtin nother one bsed on: Reversls Knowledge of preserved bloks (or genes) Now we re

More information

Quadratic Forms. Quadratic Forms

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

More information

Automatic Synthesis of New Behaviors from a Library of Available Behaviors

Automatic Synthesis of New Behaviors from a Library of Available Behaviors Automti Synthesis of New Behviors from Lirry of Aville Behviors Giuseppe De Giomo Università di Rom L Spienz, Rom, Itly degiomo@dis.unirom1.it Sestin Srdin RMIT University, Melourne, Austrli ssrdin@s.rmit.edu.u

More information

Formal languages, automata, and theory of computation

Formal languages, automata, and theory of computation Mälrdlen University TEN1 DVA337 2015 School of Innovtion, Design nd Engineering Forml lnguges, utomt, nd theory of computtion Thursdy, Novemer 5, 14:10-18:30 Techer: Dniel Hedin, phone 021-107052 The exm

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

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

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

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

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

Chapter 2 Finite Automata

Chapter 2 Finite Automata Chpter 2 Finite Automt 28 2.1 Introduction Finite utomt: first model of the notion of effective procedure. (They lso hve mny other pplictions). The concept of finite utomton cn e derived y exmining wht

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

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

DFA minimisation using the Myhill-Nerode theorem

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

More information

2.4 Linear Inequalities and Interval Notation

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

More information

Alpha Algorithm: A Process Discovery Algorithm

Alpha Algorithm: A Process Discovery Algorithm Proess Mining: Dt Siene in Ation Alph Algorithm: A Proess Disovery Algorithm prof.dr.ir. Wil vn der Alst www.proessmining.org Proess disovery = Ply-In Ply-In event log proess model Ply-Out Reply proess

More information

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

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

More information

Trigonometry Revision Sheet Q5 of Paper 2

Trigonometry Revision Sheet Q5 of Paper 2 Trigonometry Revision Sheet Q of Pper The Bsis - The Trigonometry setion is ll out tringles. We will normlly e given some of the sides or ngles of tringle nd we use formule nd rules to find the others.

More information