Turing machine Presentation... Turing machine assignment

1. Presentation ON:
Turing Machine

2. AUTOMATA CSE-301
presented to:
 Shamsun Nahar Pony
 Honourable Co-
Ordinator
 Faculty Of Engineering
 UODA
presented BY:
 1.Zaheer Raihan (011151053)

3. Turing Machine
 What is a Turing machine?
 A Turing machine is a hypothetical machine thought
of by the mathematician Alan Turing in 1936.
Despite its simplicity, the machine can simulate ANY
computer algorithm, no matter how complicated it
is!

4. Variations of Turing Machines

5. Example:

6. Part of the example:

7. Advantage:
1. CHECK DECIDABILITY IF TM CANNOT SOLVE A PROBLEM IN
COUNTABLE TIME THEN THERE COULD NOT BE ANY
ALGORITHM WHICH COULD SOLVE THAT PROBLEM (THAT IS
THE PROBLEM IS UNDECIDABLE).
FOR A DECISION PROBLEM IF ITS TM HALT IN COUNTABLE TIME
FOR ALL FINITE LENGTH INPUTS THEN WE CAN SAY THAT THE
PROBLEM COULD BE SOLVED BY AN ALGORITHM IN
COUNTABLE TIME.

8.  2. Classify Problem TM helps to classify decidable problems into
classes of Polynomial Hierarchy.
 Suppose we found that the problem is decidable. Then out target
become how efficiently we can solve it. The efficiency been
calculated in number of steps, extra space used , length of the
code/size of the FSM.
 3. Design and Implement Algorithm for Practical Machines TM helps
to propagate idea of algorithm in other practical machines. After
the successful check of 1,2 criteria we can use our practical
devices/computers to design and implement algorithm

9. Limitations:
 Limitations of Turing Machine
 1. Computational complexity theory
 a. A limitation of Turing machines is that they do not model the strengths of a particular arrangement
well.
 b. For instance, modern stored-program computers are actually instances of a more specific form of
abstract machine known as the random access stored program.
 c. An experimental prototype to machine or RASP machine model. Like the Universal Turing machine
the RASP stores its "program" in "memory" external to its finite-state achieve Turing machine machine's
"instructions".
 2. Concurrency a. Another limitation of Turing machines is that they do not model concurrency well.
 b. For example, there is a bound on the size of integer that can be computed by an always halting
nondeterministic Turing machine starting on a blank tape.
 c. By contrast, there are always-halting concurrent systems with no inputs that can compute an integer
of unbounded size.

10. Uses:

11. THE
END

12. Any Questions???