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  2. Nondeterministic algorithm - Wikipedia

    en.wikipedia.org/wiki/Nondeterministic_algorithm

    For these models, a nondeterministic algorithm is considered to perform correctly when, for each input, there exists a run that produces the desired result, even when other runs produce incorrect results. This existential power makes nondeterministic algorithms of this sort more efficient than known deterministic algorithms for many problems.

  3. Nondeterministic Turing machine - Wikipedia

    en.wikipedia.org/wiki/Nondeterministic_Turing...

    Comparison of deterministic and nondeterministic computation. In contrast to a deterministic Turing machine, in a nondeterministic Turing machine (NTM) the set of rules may prescribe more than one action to be performed for any given situation. For example, an X on the tape in state 3 might allow the NTM to:

  4. Nondeterministic programming - Wikipedia

    en.wikipedia.org/wiki/Nondeterministic_programming

    A nondeterministic programming language is a language which can specify, at certain points in the program (called "choice points"), various alternatives for program flow. ...

  5. Comparison of parser generators - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_parser...

    Deterministic context-free languages [ edit ] Context-free languages are a category of languages (sometimes termed Chomsky Type 2 ) which can be matched by a sequence of replacement rules, each of which essentially maps each non-terminal element to a sequence of terminal elements and/or other nonterminal elements.

  6. NL (complexity) - Wikipedia

    en.wikipedia.org/wiki/NL_(complexity)

    There is a simple algorithm that establishes that C = NL. Clearly C is contained in NL, since: If the string is not in the language, both reject along all computation paths. If the string is in the language, an NL algorithm accepts along at least one computation path and a C algorithm accepts along at least two-thirds of its computation paths.

  7. UP (complexity) - Wikipedia

    en.wikipedia.org/wiki/UP_(complexity)

    In complexity theory, UP (unambiguous non-deterministic polynomial-time) is the complexity class of decision problems solvable in polynomial time on an unambiguous Turing machine with at most one accepting path for each input. UP contains P and is contained in NP.

  8. Computational complexity - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity

    Simulating an NP-algorithm on a deterministic computer usually takes "exponential time". A problem is in the complexity class NP, if it may be solved in polynomial time on a non-deterministic machine. A problem is NP-complete if, roughly speaking, it is in NP and is not easier than any other NP problem.

  9. Deterministic algorithm - Wikipedia

    en.wikipedia.org/wiki/Deterministic_algorithm

    Deterministic algorithms are by far the most studied and familiar kind of algorithm, as well as one of the most practical, since they can be run on real machines efficiently. Formally, a deterministic algorithm computes a mathematical function ; a function has a unique value for any input in its domain , and the algorithm is a process that ...