Introduction to Formal Languages-E2

Numbering Code U-LAS30 20044 LE10 Year/Term 2021 ・ Second semester
Number of Credits 2 Course Type Lecture
Target Year All students Target Student For all majors
Language English Day/Period Mon.1
Instructor name Not fixed
Outline and Purpose of the Course Formal language theory is a fundamental area of theoretical computer science that studies (among other things) different ways of representing possibly infinite collections of words having some shared structure.
It is closely related to computability, computational complexity, and mathematical logic, and has practical applications in linguistics, artificial intelligence, and the design of programming languages.
The purpose of this course is to provide an introduction to formal language theory to non-computer science students.
The main topics include finite-state automata, regular languages, pushdown automata, context-free languages, Turing machines, and decidability.
Course Goals After completing this course, the student should be able to:
-Explain the relationships between different classes of formal languages, automata, and grammars.
-Design an automaton or a grammar that accepts or generates a specified formal language, and conversely,determine the formal language that is accepted or generated by a specified automaton or grammar.
-Prove or disprove mathematical properties of formal languages, grammars, and automata.
-Use the diagonalization method or reductions to establish that certain languages are undecidable.
-Understand how the concept of "information" can be defined using computability theory.
Schedule and Contents The course will consist of the following topics:
2.Finite-state automata, regular languages, nondeterminism (1)
3.Finite-state automata, regular languages, nondeterminism (2)
4.Finite-state automata, regular languages, nondeterminism (3)
5.Pushdown automata, context-free languages, grammars (1)
6.Pushdown automata, context-free languages, grammars (2)
7.Pushdown automata, context-free languages, grammars (3)
8.Turing machines (1)
9.Turing machines (2)
10.Decidability, reductions (1)
11.Decidability, reductions (2)
12.Decidability, reductions (3)
13.Advanced topics in computability theory: descriptive complexity
14.Course summary
15. Feedback
Evaluation Methods and Policy A written examination at the end of the course.
Course Requirements An ability to think abstractly and to solve problems of a mathematical nature will be required for this course.
No programming skills are needed.
Study outside of Class (preparation and review) Students will be expected to spend about 5 hours per week to prepare for and review the lessons.
Textbooks Textbooks/References Introduction to the Theory of Computation, Third Edition, M. Sipser, (Cengage Learning), ISBN:978-1133187790, 2012