**Automata Theory** is a branch of computer science that deals with designing abstract computing devices and automata, as well as computational problems that can be solved using them, so that all follow a predetermined sequence of operations automatically.

**With Automata Theory,** computer scientists are able to understand how machines compute functions and solve problems and more importantly, what it means for a function to be defined as computable or for a question to be described as decidable.

**Automatons are abstract models** of machines that perform computations on input by moving through a series of states or configurations. It's simply a limited representation of a formal language that may be an infinite set and they are often grouped by the class of formal languages they can recognize.

**An Automaton with a finite number of states** is called a Finite Automaton, while an infinite number of states is called Automaton.

**There are four major families of automaton** and can be interpreted in a hierarchal form, where the finite-state machine is the simplest automata and the Turing machine is the most complex.

**Finite-state Machine:** An automaton in which the state set Q contains only a finite number of elements is called a finite-state machine (FSM). These are abstract machines, consisting of a set of states (set Q), set of input events (set I), a set of output events (set Z) and a state transition function. They are mostly used in designing of lexical analysis of a compiler

**Pushdown Automata:** Pushdown Automata is a finite automata with extra memory called stack which helps Pushdown automata to recognize Context-Free Languages. They are used in designing the parsing phase of a compiler, implementation of stack applications, evaluating the arithmetic expressions and solving the Tower of Hanoi Problem.

**Linear-bounded Automata:** A linear bounded automata is basically a multi-track non-deterministic Turing machine with a tape of some bounded finite length. The computation is restricted to the constant bounded area. They are basically used for the implementation of genetic programming, constructing syntactic parse trees for semantic analysis of the compiler.

**Turing Machine:** Turing machine is a finite automaton or control unit equipped with infinite storage (memory). Its "memory" consists of an infinite number of a one-dimensional array of cells. Turing's machine is basically an abstract model of modern-day computer execution and storage, developed in order to provide a precise mathematical definition of an algorithm or mechanical procedure. A Turing machine consists of a tape of infinite length on which read and writes operation can be performed. The tape consists of infinite cells on which each cell either contains an input symbol or a special symbol called blank.

**There is are so many benefits in learning about Automata Theory:**

1. Automata applications are endless, basically, Automata Theory helps you understand what computation means, from the basics of elementary models of computations all the way up to the Turing machine and its applications.

2. Studying Automata Theory makes you understand and shows you how to solve certain problems with these computational models, for example; learning about the fundamentals of compilers.

3. Automata Theory allows computer scientists to learn how machines compute functions and solve problems.

4. It also helps them to understand what it means for a function to be defined as computable or for a question to be described as decidable.

5. Benefits of learning about automata theory also include understanding the underlying principles between Web Search which is on the theory of pattern matching, Sequential Circuit which is on the theory of automata, Cryptography which is on the theory of computational complexity, Data Compression which is on the theory of information and a whole lot more. As a computer scientist, you can't do without Automata Theory.

6. It interprets the state of movement of machines using discrete graphs.

7. It analyzes the logic behind the computations of computer programs.

8. It explains the abstraction behind the movement of machines.

9. It is highly applicable in engineering fields such as mechanical engineering, electrical engineering and computer artificial intelligence (AI).

10. It is applicable in writing the logic for the production and research of new mechanical and electrical devices.

**The features of Automata Theory includes the following but not limited to:**

**1. Deterministic Finite Automation:**

In Deterministic Finite Automation, for each symbol you enter, one can find out the state to which the machine will move. Hence, it is called Deterministic Automaton. Seeing that it has a finite number of states, the machine is called Deterministic Finite Machine or Deterministic Finite Automaton**. **Deterministic here refers to the uniqueness of the computation.

A Deterministic Finite Automaton is defined as an abstract mathematical concept but is use cases are often seen in hardware and software for solving various specific problems. For example, a Deterministic finite model can model software that decides whether or not online user inputs such as email addresses are valid.

Finite (DFA) can be seen as a special kind of NFA, in which for each state and alphabet, the transition function has exactly one state.

**2. Non-deterministic Finite Automaton:**

In Non-deterministic Finite Automation, for a particular input symbol, the machine can move to any combination of the states in the machine. In other words, the exact state to which the machine moves cannot be determined. Hence, it is called Automaton. As it has of states, the machine is called Non-deterministic Finite Machine or Non-deterministic Finite Automaton.

A Non-Deterministic Finite Automaton (NFA), or Non-Deterministic Finite State Machine, does not need to obey these restrictions. In particular, every DFA is also an NFA. Sometimes the term NFA is used in a narrower sense, referring to an NFA that is *not* a deterministic Finite Automaton.

**Some of the things you will learn in this course include: **

**You will learn about Automaton Theories** and how they operate. The Automaton is a self-propelled device that satisfies every condition of the Automata Theory.

**The concept of Finite state machines,** you will understand how they work. The Finite state machines are devices that tend to change their state when input is been made into the machine. An example is the Turnstile machine.

**You will understand how the schematic** of a Finite state machine is being obtained from a table of languages or strings and how possible it will be for the schematic to change its state if an input defined within the schematic is made.

**You will understand DFA** also known as the Deterministic Finite Automaton and non-DFA. The languages and grammar, how to write a string of codes that serve as algorithms for the automatic computational process of a machine.

**Turing machines and their types such as:**

Non-Deterministic Turing Machines,

Semi Infinite Tape,

Turine Machines,

Multi Tape and

Multi-Track Turing Machines.

**Decidability such as: **

The Decidable languages and

The unDecidable languages.

You will also understand the Fundamentals of Automata Theory and a lot more.

**In the Full Course, you will learn everything you need to know** about **Automata Theory** with **Diploma Certificate** to showcase your knowledge and competence.

Automata Theory - Introduction

Automata Theory - Deterministic Finite Automaton

Automata Theory - Non-deterministic Finite Automaton

Automata Theory - NDFA to DFA Conversion

Automata Theory - DFA Minimization

Automata Theory - Moore & Mealy Machines

Automata Theory - Introduction to Grammars

Automata Theory - Classification of Grammars

Automata Theory - Language Generated by Grammars

Automata Theory - Chomsky Grammar Classification

Automata Theory - Regular Grammar

Automata Theory - Regular Expressions

Automata Theory - Regular Sets

Automata Theory - Arden's Theorem

Automata Theory - Constructing FA from RE

Automata Theory - Pumping Lemma for Regular Grammar

Automata Theory - DFA Complement

Automata Theory - Context-Free Grammar

Automata Theory - Ambiguity in Grammar

Automata Theory - CFL Closure Properties

Automata Theory - CFG Simplification

Automata Theory - Chomsky Normal Form

Automata Theory - Greibach Normal Form

Automata Theory - Pumping Lemma for CFG

Automata Theory - Pushdown Automata

Automata Theory - Pushdown Automata Acceptance

Automata Theory - PDA & Context-Free Grammar

Automata Theory - PDA & Parsing

Automata Theory - Turing Machine

Automata Theory - Accepted & Decided Language

Automata Theory - Multi-tape Turing Machine

Automata Theory - Multi-Track Turing Machine

Automata Theory - Non-Deterministic Turing Machine

Automata Theory - Semi-Infinite Tape Turing Machine

Automata Theory - Linear Bounded Automata

Automata Theory - Decidability

Automata Theory - Language Decidability

Automata Theory - Undecidable Language

Automata Theory - Turing Machine Halting Problem

Automata Theory - Rice Theorem

Automata Theory - Post Correspondence Problem

Automata Theory - Exams and Certification

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