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Automaten Und Formale Sprachen Allrode (Harz), 27 HEORIE- TTAG 2011 21. Theorietag Automaten und Formale Sprachen Allrode (Harz), 27. – 29. September 2011 Tagungsband Jürgen Dassow, Bianca Truthe (Hrsg.) Titel: 21. Theorietag „Automaten und Formale Sprachen“, Allrode (Harz), 27. – 29.9.2011, Tagungsband Veröffentlicht durch die Otto-von-Guericke-Universität Magdeburg Fakultät für Informatik Universitätsplatz 2 39106 Magdeburg Herausgegeben von Jürgen Dassow und Bianca Truthe, 2011 Das Copyright liegt bei den Autoren der Beiträge. Vorwort Der Theorietag ist die Jahrestagung der Fachgruppe Automaten und Formale Sprachen der Ge- sellschaft für Informatik. Er wurde vor 20 Jahren in Magdeburg ins Leben gerufen. Seit dem Jahre 1996 wird der Theorietag von einem eintägigen Workshop mit eingeladenen Vorträgen begleitet. Im Laufe des Theorietags findet auch die jährliche Fachgruppensitzung statt. Die bisherigen Theorietage wurden in Magdeburg (1991), in Kiel (1992), auf Schloß Dag- stuhl (1993), in Herrsching bei München (1994 und 2003), auf Schloß Rauischholzhausen (1995), in Cunnersdorf in der Sächsischen Schweiz (1996), in Barnstorf bei Bremen (1997), in Riveris bei Trier (1998), in Schauenburg-Elmshagen bei Kassel (1999), in Wien (2000 und 2006), in Wendgräben bei Magdeburg (2001), in der Lutherstadt Wittenberg (2002 und 2009), in Caputh bei Potsdam (2004), in Lauterbad bei Freudenstadt (2005), in Leipzig (2007), in Wettenberg-Launsbach bei Gießen (2008) und in Baunatal bei Kassel (2010) ausgerichtet. Der diesjährige Theorietag wird nach 1991 und 2001 wieder von der Arbeitsgruppe „For- male Sprachen und Automaten“ der Otto-von-Guericke-Universität Magdeburg organisiert. Er findet mit dem vorangehenden Workshop vom 27. bis 29. September 2011 in Allrode im Harz statt. Auf dem Workshop tragen • Frank Drewes aus Umeå, • Manfred Droste aus Leipzig, • Florin Manea aus Bukarest, • Sergey Verlan aus Paris und • Georg Zetzsche aus Kaiserslautern vor. Auf dem Programm des Theorietags stehen 21 weitere Vorträge. Der vorliegende Tagungs- band enthält Kurzfassungen aller 26 Beiträge. Die Teilnehmer kommen aus sieben verschie- denen Ländern: Frankreich, Österreich, Rumänien, Schweden, Tschechien, dem Vereinigten Königreich und Deutschland. Wir danken der Gesellschaft für Informatik, der Otto-von-Guericke-Universität Magdeburg und der METOP GmbH für die Unterstützung dieses Theorietags. Wir wünschen allen Teilneh- mern eine interessante und anregende Tagung sowie einen angenehmen Aufenthalt im Harz. Magdeburg, im September 2011 Jürgen Dassow und Bianca Truthe Inhalt BEGLEITENDER WORKSHOP FRANK DREWES: Varianten eines Algorithmus zum Lernen von Baumreihen . 5 MANFRED DROSTE: Weighted Automata and Quantitative Logics . 9 FLORIN MANEA: Turing Machines Deciding According to the Shortest Computations and Deciding Networks of Evolutionary Processors . 11 SERGEY VERLAN: An Overview of Insertion-Deletion Systems . 15 GEORG ZETZSCHE: Recent Results on Erasing in Regulated Rewriting . 17 THEORIETAG „AUTOMATEN UND FORMALE SPRACHEN“ STEPHAN BARTH,MARTIN HOFMANN: SAT-basiertes Minimieren von Büchi-Automaten . 21 STANISLAV BASOVNÍK,FRANTIŠEK MRÁZ: Learning Limited Context Restarting Automata by Genetic Algorithms . 25 JÜRGEN DASSOW,FLORIN MANEA,BIANCA TRUTHE: Netze evolutionärer Prozessoren mit subregulären Filtern . 29 HENNING FERNAU,RALF STIEBE: Über CD Grammatiksysteme mit Valenzregeln . 33 RUDOLF FREUND: A General Framework for Regulated Rewriting . 37 DOMINIK D. FREYDENBERGER: Entscheidungsprobleme für erweiterte reguläre Ausdrücke . 43 STEFAN GULAN: Unäre Operatoren in regulären Ausdrücken . 47 RONNY HARBICH: Beschreibungskomplexität kontextfreier Sprachen bezüglich der AFL-Operationen . 51 MARKUS HOLZER,SEBASTIAN JAKOBI: Chop Operations and Expressions: Descriptional Complexity Considerations . 55 MARKUS HOLZER,MARTIN KUTRIB,KATJA MECKEL: Nondeterministic State Complexity of Star-Free Languages . 59 NORBERT HUNDESHAGEN,FRIEDRICH OTTO: Restarting Automata and Rational Relations . 63 MARIAN KOGLER: On the Complexity of Pushdown Transducers and Two-Way Transducers . 67 MARTIN KUTRIB,MATTHIAS WENDLANDT: String Assembling Systems . 71 ANDREAS MALCHER,CARLO MEREGHETTI,BEATRICE PALANO: Descriptional Complexity of Two-Way Pushdown Automata With Restricted Head Reversals . 77 FLORIN MANEA,ROBERT MERCA ¸S,CAT˘ ALIN˘ TISEANU: Algorithms and Pseudo-Periodicity in Words . 81 FLORIN MANEA,ROBERT MERCA ¸S,CAT˘ ALIN˘ TISEANU: On Periodic Partial Words . 85 BENEDEK NAGY,FRIEDRICH OTTO,MARCEL VOLLWEILER: Pushdown Automata with Translucent Pushdown Symbols . 89 KARIN QUAAS: On the Interval-Bound Problem for Weighted Timed Automata . 93 HENDRIK RADKE: HR∗ Graph Conditions Versus Counting Monadic Second-Order Graph Formulas . 97 DANIEL REIDENBACH,MARKUS L. SCHMID: Automata for Languages Defined by Backreferencing . 101 GEORG ZETZSCHE: Monoid Control for Grammars, Automata, and Transducers . 105 Autorenverzeichnis . 109 HEORIE- J. Dassow und B. Truthe (Hrsg.): Theorietag 2011, Allrode (Harz), 27.– 29.9.2011 TTAG 2011 Otto-von-Guericke-UniversitätMagdeburg S.5–7 Varianten eines Algorithmus zum Lernen von Baumreihen Frank Drewes Institutionen för datavetenskap, Umeå universitet (Schweden) [email protected] Auf dem Gebiet der grammatischen Inferenz ist das Ziel traditionell, aus einer gegebenen In- formationsquelle über eine Sprache eine geeignete formelle Definition dieser Sprache abzulei- ten (zu „lernen“), also einen entsprechenden Automaten oder eine Grammatik zu konstruieren. Während es traditionell um das Lernen von Wortsprachen geht, werde ich mich in diesem Vor- trag auf das Lernen von Baumreihen konzentrieren, und insbesondere auf die Ergebnisse des Artikels [3]. Zur Erinnerung: Ein (kommutativer) Semiring ist eine Menge S mit einer Addition, einer Multiplikation und Elementen 0 und 1, sodass (S,+,0) und (S,·,1) kommutative Monoide sind und Multiplikation distributiv über Addition ist (sowohl von links als auch von rechts). Eine Baumreihe ist nun eine Abbildung ψ : TΣ → S der Menge TΣ aller Bäume über ei- ner gegebenen Signatur Σ (also einem Alphabet mit Stelligkeiten) in einen Semiring S. Der Wert ψ(t) eines Baumes t wird auch sein Koeffizient genannt. Das Konzept verallgemeinert in natürlicher Weise das der Sprache, denn wenn wir als S den booleschen Semiring wählen, ist ψ gerade die charakteristische Funktion einer Sprache (in diesem Fall einer Baumsprache). Baum- reihen werden durch gewichtete Baumautomaten erkannt. In einem solchen Automaten ist jeder Transition ein Gewicht in S\{0} zugeordnet. Zusätzlich hat jeder Zustand ein sog. Endgewicht in S, was den Begriff des Endzustandes verallgemeinert. Das Gewicht einer Berechnung auf einem Eingabebaum t ist das Produkt der Gewichte der angewendeten Transitionen, multipli- ziert mit dem Endgewicht des an der Wurzel erreichten Zustandes. Das Gewicht von t ist die Summe der Gewichte aller Berechnungen auf t. Eine sehr gute und umfassende Einführung in die vielfältigen Ergebnisse der Theorie der gewichteten Baumautomaten findet sich in [4]. Im Vortrag werden in erster Linie deterministische gewichtete Baumautomaten von Interes- se sein. Bei diesen entfällt also das Bilden der Summe der Gewichte aller möglichen Berechnun- gen, da es für jeden Eingabebaum t maximal eine Berechnung gibt, sodass vom Semiring S nur das kommutative Monoid (S,·,1) von Interesse ist. Die formale Definition gewichteter Baum- automaten sieht damit wie folgt aus: Definition 0.1 Ein deterministischer gewichteter Baumautomat ist ein Tupel A =(Σ,Q,δ,λ), bestehend aus • der Eingabesignatur Σ, 6 Frank Drewes • der endlichen Menge Q von Zuständen, welche als Symbole der Stelligkeit 0 angesehen werden, • der partiellen Transitionsfunktion δ : Σ(Q) → Q × (S \{0}) 1 und • der Zuordnung λ: Q → S von Endgewichten zu Zuständen. Die Arbeitsweise eines solchen Automaten ist wie folgt definiert. Die Transitionsfunktion δ wird rekursiv zu einer Funktion δˆ : TΣ → Q × (S \{0}) fortgesetzt. Sei dazu f[t1,...,tk] ∈ TΣ (d.h. f hat die Stelligkeit k) und t1,...,tk ∈ TΣ. Wenn sowohl alle δˆ(ti)=(qi,ai) für i = 1,...,k ˆ k als auch δ(f[q1,...,qk])=(q,a) definiert sind, setzen wir δ(f[t1,...,tk])=(q,a·∏i=1 ai). An- dernfalls ist δˆ(f[t1,...,tk]) undefiniert. Die von A berechnete (oder erkannte) Baumreihe ist damit wie folgt gegeben: a · λ(q) falls δˆ(t)=(q,a) definiert ist A(t) = 0 sonst. Das Ziel ist also, einen solchen gewichteten Baumautomaten (algorithmisch) zu erlernen. Dazu gibt es eine Reihe unterschiedlicher Modelle, die zum einen die zur Verfügung stehen- de Information und zum anderen das genaue Ziel definieren. Im Vortrag konzentriere ich mich im Wesentlichen auf Angluins Minimal-Adequate-Teacher-Modell (MAT).2 Bei diesem ist das Ziel, eine deterministisch erkennbare Baumreihe effizient von einem „Lehrer“ zu erlernen, also möglichst in polynomieller Zeit einen Automaten zu konstruieren, der die gewünschte Baum- reihe berechnet. Der Lehrer ist ein Orakel, das folgende Typen von Fragen beantwortet: (1) Gegeben einen Baum t, welchen Koeffizienten hat t? (2) Gegeben einen deterministischen gewichteten Baumautomaten A, ist A der gesuchte Au- tomat? Falls nicht, liefere ein Gegenbeispiel, also einen Baum t, sodass A(t) nicht der korrekte Koeffizient ist. Angluins Originalarbeit [1] zeigt, wie in diesem Modell unter Ausnutzung des Myhill-Nerode- Theorems in polynomieller Zeit eine reguläre Sprache L erlernt werden kann. Die Grundstruk- tur des Algorithmus ist dabei recht einfach und läuft darauf hinaus, iterativ die Äquivalenz- klassen der Myhill-Nerode-Äquivalenzrelation zu ermitteln. Beginnend mit einem trivialen Au- tomaten
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