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  2. Nondeterministic algorithm - Wikipedia

    en.wikipedia.org/wiki/Nondeterministic_algorithm

    Nondeterministic algorithm. In computer science and computer programming, a nondeterministic algorithm is an algorithm that, even for the same input, can exhibit different behaviors on different runs, as opposed to a deterministic algorithm. Different models of computation give rise to different reasons that an algorithm may be non ...

  3. NP (complexity) - Wikipedia

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

    NP is the set of decision problems for which the problem instances, where the answer is "yes", have proofs verifiable in polynomial time by a deterministic Turing machine, or alternatively the set of problems that can be solved in polynomial time by a nondeterministic Turing machine. [2][Note 1] NP is the set of decision problems solvable in ...

  4. Nondeterministic Turing machine - Wikipedia

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

    e. In theoretical computer science, a nondeterministic Turing machine (NTM) is a theoretical model of computation whose governing rules specify more than one possible action when in some given situations. That is, an NTM's next state is not completely determined by its action and the current symbol it sees, unlike a deterministic Turing machine.

  5. Computational complexity theory - Wikipedia

    en.wikipedia.org/wiki/Computational_complexity...

    In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and explores the relationships between these classifications. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of ...

  6. Random sample consensus - Wikipedia

    en.wikipedia.org/wiki/Random_sample_consensus

    Random sample consensus (RANSAC) is an iterative method to estimate parameters of a mathematical model from a set of observed data that contains outliers, when outliers are to be accorded no influence on the values of the estimates. Therefore, it also can be interpreted as an outlier detection method. [1] It is a non-deterministic algorithm in ...

  7. k-means clustering - Wikipedia

    en.wikipedia.org/wiki/K-means_clustering

    Example image with only red and green channel (for illustration purposes) Vector quantization of colors present in the image above into Voronoi cells using k-means. Example: In the field of computer graphics, k-means clustering is often employed for color quantization in image compression. By reducing the number of colors used to represent an ...

  8. Shortest path problem - Wikipedia

    en.wikipedia.org/wiki/Shortest_path_problem

    Shortest path (A, C, E, D, F) between vertices A and F in the weighted directed graph. In graph theory, the shortest path problem is the problem of finding a path between two vertices (or nodes) in a graph such that the sum of the weights of its constituent edges is minimized.

  9. Petri net - Wikipedia

    en.wikipedia.org/wiki/Petri_net

    A Petri net is a directed bipartite graph that has two types of elements: places and transitions. Place elements are depicted as white circles and transition elements are depicted as rectangles. A place can contain any number of tokens, depicted as black circles. A transition is enabled if all places connected to it as inputs contain at least ...

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