Turing Machines: Classifying for Decidable Problems

In summary, the conversation discusses the concept of a machine that can decide on all Turing decidable problems and whether it would belong to a specific class or not. The speaker also clarifies the definition of a decidable problem and raises the possibility of a Universal Turing Machine.
  • #1
Gear300
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It's been a while since I've done this, but the question spurred on. Is there any sort of named class that a machine that can decide on all Turing decidable problems would belong to?

Edit: Actually, I guess it would be Turing if you could program it to decide on a particular problem.
 
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  • #2
Can you rephrase your question a bit?

Are you looking for actual code in Java or C++ or some generic algorithm?
 
  • #3
Gear300 said:
It's been a while since I've done this, but the question spurred on. Is there any sort of named class that a machine that can decide on all Turing decidable problems would belong to?

Edit: Actually, I guess it would be Turing if you could program it to decide on a particular problem.

You must put your question in a more clear way as jedishrfu points out. A problem is decidable if there is an algorithm to answer it. As you may know an algorithm - formally speaking, is a TM that halts on all inputs whether accepted or not. So, effectively a decidable problem is equivalent to a recursive language. Now, just by guesswork, is your question about a UTM (Universal Turing Machine)? Because in this case the language ##L_{u}## of UTM is not recursive but recursively enumerable.
 
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1. What is a Turing Machine?

A Turing Machine is a mathematical model that represents a hypothetical computing machine. It consists of a tape, a read/write head, and a set of rules that determine how the machine manipulates the symbols on the tape.

2. How does a Turing Machine classify problems as decidable?

A Turing Machine classifies problems as decidable if it can determine whether a given statement is true or false within a finite number of steps. This means that the machine will eventually reach a halting state and provide an answer, rather than looping infinitely.

3. Can a Turing Machine solve all problems?

No, a Turing Machine is limited by its finite set of rules and its finite tape. This means that there are problems that cannot be solved by a Turing Machine, such as the Halting Problem.

4. How are Turing Machines used in computer science?

Turing Machines are used as a theoretical framework for understanding the limits of computation. They also serve as a basis for the design and analysis of algorithms and programming languages.

5. Are there real-world applications for Turing Machines?

While Turing Machines are primarily used as a theoretical tool, they have also been applied in practical fields such as artificial intelligence, computer security, and natural language processing. However, most real-world problems are too complex to be solved by a Turing Machine alone, and require additional tools and techniques.

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