PPT-Chapter 2 FINITE AUTOMATA

Learning Objectives At the conclusion of the chapter the student will be able to Describe the components of a deterministic finite accepter dfa State whether an input string is accepted by a dfa. Rational . A. utomata. : . a . bridge unifying . 1d and. . 2d. language. . theory. Marcella Anselmo Dora . Giammarresi. Maria . Madonia. . Univ. . . of. Salerno. . . Univ. . Roma . THEORY. II B. Questions Answers(DFA-NFA) . Dept. of Computer Science & IT, FUUAST Automata Theory . 2. Automata Theory II B. For .  = {a, b} construct DFA that accepts all strings with exactly one ‘a’ .. THEORY. I. Introduction. What is Automata. Automaton and types of automata. History, Turing Machine. Why study Automata Theory. e) Applications & Uses. Dept. of Computer Science & IT, FUUAST Automata Theory . Introduce finite state automata. Able to capture state, events and dynamic behavior of “man-made systems”. Present logical properties. Textbook :. C. . Cassandras. and S. . Lafortune. , Introduction to Discrete Event Systems, Springer, 2007. Presented By:. Loris D’Antoni . Joint work with:. Margus. . Veanes. Outline. Symbolic Automata and Transducers. Extended Symbolic Automata and Transducers. Some negative results. Some positive results. Ashish Srivastava. Harshil Pathak. Introduction to Probabilistic Automaton. Deterministic Probabilistic Finite Automata. Probabilistic Finite Automaton. Probably Approximately Correct (PAC) learnability. Reading: Chapter 1. 2. What is Automata Theory?. Study of abstract computing devices, or “machines”. Automaton = an abstract computing device. Note:. A “device” need not even be a physical hardware!. Ashish Srivastava. Harshil Pathak. Introduction to Probabilistic Automaton. Deterministic Probabilistic Finite Automata. Probabilistic Finite Automaton. Probably Approximately Correct (PAC) learnability. Sambhav. . Jain. IIIT Hyderabad. Think !!!. How to store a dictionary in computer?. How to search for an entry in that dictionary?. Say you have each word length exactly equal to 10 characters and can take any letter from ‘a-z’. Pierre Bourhis . CNRS . CRIStAL. , Equipe LINKS. Joint . works. . with. . M.Benedikt. , . M.Krötzsch. , S. Rudolph, P. Senellart, M. Van Den Boom. 1. Querying a database . Database : a labelled graph or hypergraph. Systems. Model Checking Timed Automata . Sayan. . Mitra. Lecture 09. What we have seen so far . A very general modeling framework (Lynch et al.’s Hybrid Automata[1]) . Complex discrete dynamics. Possibly nonlinear continuous dynamics. This course: A study of . abstract. . models of computers and computation.. Why theory, when computer field is so practical?. Theory provides concepts and principles, for both hardware and software that help us understand the general nature of the field.. 2. Finite Automaton (FA). Informally, a state diagram that comprehensively captures all possible states and transitions that a machine can take while responding to a stream or sequence of input symbols. Chapter 2 FINITE AUTOMATA Learning Objectives At the conclusion of the chapter, the student will be able to: Describe the components of a deterministic finite accepter ( dfa ) State whether an input string is accepted by a dfa