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3.2: Undecidability

  • Page ID
    121612
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    • 3.2.1: Introduction
      It is one thing to not be able to imagine how one would compute complicated functions, and quite another to actually prove that they are uncomputable.
    • 3.2.2: Enumerating Turing Machines
      We can show that the set of all Turing machines is countable. This follows from the fact that each Turing machine can be finitely described.
    • 3.2.3: The Halting Problem
      The halting problem is one example of a larger class of problems of the form “can \(X\) be accomplished using Turing machines.” (The answer is no: the halting problem is unsolvable.)
    • 3.2.4: The Decision Problem
      We say that first-order logic is decidable iff there is an effective method for determining whether or not a given sentence is valid. As it turns out, there is no such method: the problem of deciding validity of first-order sentences is unsolvable.
    • 3.2.5: Representing Turing Machines
      In order to represent Turing machines and their behavior by a sentence of first-order logic, we have to define a suitable language. The language consists of two parts: predicate symbols for describing configurations of the machine, and expressions for numbering execution steps (“moments”) and positions on the tape.
    • 3.2.6: Verifying the Representation
      In order to verify that our representation works, we have to prove two things. First, we have to show that if \(M\) halts on input \(w\), then \(T(M, w) \rightarrow E(M, w)\) is valid. Then, we have to show the converse, i.e., that if \(T(M, w) \rightarrow E(M, w)\) is valid, then \(M\) does in fact eventually halt when run on input \(w\).
    • 3.2.7: The Decision Problem is Unsolvable
      If the decision problem were solvable, we could use it to solve the halting problem.
    • 3.2.8: Summary


    This page titled 3.2: Undecidability is shared under a CC BY license and was authored, remixed, and/or curated by Richard Zach et al. (Open Logic Project) .

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