Prerequisite – Turing Machine
A problem is said to be Decidable if we can always construct a corresponding algorithm that can answer the problem correctly. We can intuitively understand Decidable problems by considering a simple example. Suppose we are asked to compute all the prime numbers in the range of 1000 to 2000. To find the solution of this problem, we can easily devise an algorithm that can enumerate all the prime numbers in this range.
Now talking about Decidability in terms of a Turing machine, a problem is said to be a Decidable problem if there exist a corresponding Turing machine which halts on every input with an answer- yes or no. It is also important to know that these problems are termed as Turing Decidable since a Turing machine always halts on every input, accepting or rejecting it.
Semi- Decidable Problems –
Semi-Decidable problems are those for which a Turing machine halts on the input accepted by it but it can either halt or loop forever on the input which is rejected by the Turing Machine. Such problems are termed as Turing Recognisable problems.
Examples – We will now consider few important Decidable problems:
- Are two regular languages L and M equivalent?
We can easily check this by using Set Difference operation.
L-M =Null and M-L =Null.
Hence (L-M) U (M-L) = Null, then L,M are equivalent.
- Membership of a CFL?
We can always find whether a string exist in a given CFL by using on algorithm based on dynamic programming.
- Emptiness of a CFL
By checking the production rules of the CFL we can easily state whether the language generates any strings or not.
Undecidable Problems –
The problems for which we can’t construct an algorithm that can answer the problem correctly in a finite time are termed as Undecidable Problems. These problems are not even partially decidable and can lead a Turing machine to loop forever without answering at all.
We can understand Undecidable Problems intuitively by considering Fermat’s Theorem, a popular Undecidable Problem which states that no three positive integers a, b and c for any n>=2 can ever satisfy the equation: a^n + b^n = c^n.
If we feed this problem to a Turing machine to find such a solution which gives a contradiction then a Turing Machine might run forever, to find the suitable values of n, a, b and c. But we are always unsure whether a contradiction exists or not and hence we term this problem as an Undecidable Problem.
Examples – These are few important Undecidable Problems:
- Whether a CFG generates all the strings or not?
As a CFG generates infinite strings ,we can’t ever reach up to the last string and hence it is Undecidable.
- Whether two CFG L and M equal?
Since we cannot determine all the strings of any CFG , we can predict that two CFG are equal or not.
- Ambiguity of CFG?
There exist no algorithm which can check whether for the ambiguity of a CFL. We can only check if any particular string of the CFL generates two different parse trees then the CFL is ambiguous.
- Is it possible to convert a given ambiguous CFG into corresponding non-ambiguous CFL?
It is also an Undecidable Problem as there doesn’t exist any algorithm for the conversion of an ambiguous CFL to non-ambiguous CFL.
- Is a language Learning which is a CFL, regular?
This is an Undecidable Problem as we can not find from the production rules of the CFL whether it is regular or not.
Some more Undecidable Problems related to Turing machine:
- Membership problem of a Turing Machine?
- Finiteness of a Turing Machine?
- Emptiness of a Turing Machine?
- Whether the language accepted by Turing Machine is regular or CFL?
This article is contributed by Aishwarya Agarwal. If you like GeeksforGeeks and would like to contribute, you can also write an article using contribute.geeksforgeeks.org or mail your article to firstname.lastname@example.org. See your article appearing on the GeeksforGeeks main page and help other Geeks.
Please write comments if you find anything incorrect, or you want to share more information about the topic discussed above.
- GATE CS 2018 Mock Tests
- Computer Network | Transport Layer responsibilities
- Regular Expressions, Regular Grammar and Regular Languages
- Recursive and Recursive Enumerable Languages
- Turing Machine
- Computer Network | Simple network management protocol (SNMP)
- Discrete Mathematics | Hasse Diagrams
- S – attributed and L – attributed SDTs in Syntax directed translation
- Mathematics | Walks, Trails, Paths, Cycles and Circuits in Graph
- Operating System | Belady’s Anomaly