Weighted finite automata are classical nondeterministic finite automata in which the transitions carry weights. These weights may model, for example, the cost involved when executing a transition, the resources or time needed for this, or the probability or reliability of its successful execution. Weights can also be added to classical automata with infinite state sets like pushdown automata, and this extension constitutes the general concept of weighted automata. Since their introduction in the 1960s they have stimulated research in related areas of theoretical computer science, including formal language theory, algebra, logic, and discrete structures. Moreover, weighted automata and weighted context-free grammars have found application in natural-language processing, speech recognition, and digital image compression.

This book covers all the main aspects of weighted automata and formal power series methods, ranging from theory to applications. The contributors are the leading experts in their respective areas, and each chapter presents a detailed survey of the state of the art and pointers to future research. The chapters in Part I cover the foundations of the theory of weighted automata, specifically addressing semirings, power series, and fixed point theory. Part II investigates different concepts of weighted recognizability. Part III examines alternative types of weighted automata and various discrete structures other than words. Finally, Part IV deals with applications of weighted automata, including digital image compression, fuzzy languages, model checking, and natural-language processing.

Computer scientists and mathematicians will find this book an excellent survey and reference volume, and it will also be a valuable resource for students exploring this exciting research area.

Weighted finite automata are classical nondeterministic finite automata in which the transitions carry weights. These weights may model, for example, the cost involved when executing a transition, the resources or time needed for this, or the probability or reliability of its successful execution. Weights can also be added to classical automata with infinite state sets like pushdown automata, and this extension constitutes the general concept of weighted automata. Since their introduction in the 1960s they have stimulated research in related areas of theoretical computer science, including formal language theory, algebra, logic, and discrete structures. Moreover, weighted automata and weighted context-free grammars have found application in natural-language processing, speech recognition, and digital image compression.

This book covers all the main aspects of weighted automata and formal power series methods, ranging from theory to applications. The contributors are the leading experts in their respective areas, and each chapter presents a detailed survey of the state of the art and pointers to future research. The chapters in Part I cover the foundations of the theory of weighted automata, specifically addressing semirings, power series, and fixed point theory. Part II investigates different concepts of weighted recognizability. Part III examines alternative types of weighted automata and various discrete structures other than words. Finally, Part IV deals with applications of weighted automata, including digital image compression, fuzzy languages, model checking, and natural-language processing.

Computer scientists and mathematicians will find this book an excellent survey and reference volume, and it will also be a valuable resource for students exploring this exciting research area.

This is a motivated presentation of recent results on tree transducers, applied to studying the general properties of formal models and for providing semantics to context-free languages. The authors consider top-down tree transducers, macro tree transducers, attributed tree transducers, and macro attributed tree transducers. A unified terminology is used to define them, and their transformational capacities are compared. This handbook on tree transducers will serve as a base for further research.

Das Buch bietet eine grundlegende Einfuhrung in die Technik der Attributgrammatiken. Im Compilerbau haben sich Attributgrammatiken als nutzliches Werkzeug zur Spezifikation kontextsensitiver Nebenbedingungen und der Ubersetzung von Programmiersprachen erwiesen. Im Mittelpunkt des Buches stehen die Algorithmen zur Attributauswertung und die Beziehungen zu anderen Programmierparadigmen. Das Buch zeichnet sich durch seine formale Darstellung aus und kann sehr gut als Grundlage fur Lehrveranstaltungen in Informatik, Mathematik und ingenieurwissenschaftlichen Fachern benutzt werden. Durch die vielen begleitenden Beispiele und Ubungsaufgaben ist es auch zum Selbststudium geeignet.
Nicht nur Dozenten und Studenten, sondern auch der erfahrene Compilerdesigner und der Entwickler von Programmierumgebungen werden intensiven Nutzen aus diesem Buch ziehen konnen."