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Prof.Neeraj Bhargava
Abhishek Kumar
Department of Computer Science
School of Engineering & System Sciences,
MDS, University Ajmer, Rajasthan, India
1
Some basics
• Automaton = A self-operating machine or
mechanism (Dictionary definition), plural is
Automata.
• Automata = abstract computing devices
• Automata theory = the study of abstract
machines (or more appropriately, abstract
'mathematical' machines or systems, and the
computational problems that can be solved
using these machines.
• Mathematical models of computation
• Finite automata
• Push-down automata
• Turing machines
2
History
• 1930s : Alan Turing defined machines more
powerful than any in existence, or even any that
we could imagine – Goal was to establish the
boundary between what was and was not
computable.
• 1940s/150s : In an attempt to model “Brain
function” researchers defined finite state
machines.
• Late 1950s : Linguist Noam Chomsky began the
study of Formal Grammars.
• 1960s : A convergence of all this into a formal
theory of computer science, with very deep
philosophical implications as well as practical
applications (compilers, web searching, hardware,
A.I., algorithm design, software engineering,…) 3
Computation
CPU memory
4
Study and mathematically model
various abstract computing machines
that serve as models for computations
and examine the relationship between
these automata and formal languages.
Regular expressions, NFAs.
 Core concepts of Regular Languages and
Finite Automata; Decidability for Regular
Languages; Non-regular Languages; Context-
free Languages and Pushdown Automata;
Decidability for Context-free Languages;
Non-context-free Languages; Turing
Machines and Their Languages are important
part of the course. Transducers (automata
with output).
5
CPU
input memory
output memory
Program memory
temporary memory
6
CPU
input memory
output memory
Program memory
temporary memory
3
)( xxf 
compute xx
compute xx 2
Example:
7

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LECTURE SERIES TOC

  • 1. Prof.Neeraj Bhargava Abhishek Kumar Department of Computer Science School of Engineering & System Sciences, MDS, University Ajmer, Rajasthan, India 1
  • 2. Some basics • Automaton = A self-operating machine or mechanism (Dictionary definition), plural is Automata. • Automata = abstract computing devices • Automata theory = the study of abstract machines (or more appropriately, abstract 'mathematical' machines or systems, and the computational problems that can be solved using these machines. • Mathematical models of computation • Finite automata • Push-down automata • Turing machines 2
  • 3. History • 1930s : Alan Turing defined machines more powerful than any in existence, or even any that we could imagine – Goal was to establish the boundary between what was and was not computable. • 1940s/150s : In an attempt to model “Brain function” researchers defined finite state machines. • Late 1950s : Linguist Noam Chomsky began the study of Formal Grammars. • 1960s : A convergence of all this into a formal theory of computer science, with very deep philosophical implications as well as practical applications (compilers, web searching, hardware, A.I., algorithm design, software engineering,…) 3
  • 4. Computation CPU memory 4 Study and mathematically model various abstract computing machines that serve as models for computations and examine the relationship between these automata and formal languages. Regular expressions, NFAs.
  • 5.  Core concepts of Regular Languages and Finite Automata; Decidability for Regular Languages; Non-regular Languages; Context- free Languages and Pushdown Automata; Decidability for Context-free Languages; Non-context-free Languages; Turing Machines and Their Languages are important part of the course. Transducers (automata with output). 5
  • 6. CPU input memory output memory Program memory temporary memory 6
  • 7. CPU input memory output memory Program memory temporary memory 3 )( xxf  compute xx compute xx 2 Example: 7