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  2. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    From a dynamic programming point of view, Dijkstra's algorithm for the shortest path problem is a successive approximation scheme that solves the dynamic programming functional equation for the shortest path problem by the Reaching method. [8] [9] [10] In fact, Dijkstra's explanation of the logic behind the algorithm, [11] namely Problem 2.

  3. Adaptive Huffman coding - Wikipedia

    en.wikipedia.org/wiki/Adaptive_Huffman_coding

    Adaptive Huffman coding (also called Dynamic Huffman coding) is an adaptive coding technique based on Huffman coding. It permits building the code as the symbols are being transmitted, having no initial knowledge of source distribution, that allows one-pass encoding and adaptation to changing conditions in data.

  4. Adaptation (computer science) - Wikipedia

    en.wikipedia.org/wiki/Adaptation_(computer_science)

    Adaptive algorithm – Algorithm that changes its behavior at the time it is run; Personalization – Using technology to accommodate the differences between individuals; Adaptive hypermedia – Hypermedia which varies output provided according to a model of the user; Content adaptation – Design approach for distribution to mixed environments

  5. Adaptive mesh refinement - Wikipedia

    en.wikipedia.org/wiki/Adaptive_mesh_refinement

    Adaptive mesh refinement provides such a dynamic programming environment for adapting the precision of the numerical computation based on the requirements of a computation problem in specific areas of multi-dimensional graphs which need precision while leaving the other regions of the multi-dimensional graphs at lower levels of precision and ...

  6. Markov decision process - Wikipedia

    en.wikipedia.org/wiki/Markov_decision_process

    For example, the dynamic programming algorithms described in the next section require an explicit model, and Monte Carlo tree search requires a generative model (or an episodic simulator that can be copied at any state), whereas most reinforcement learning algorithms require only an episodic simulator.

  7. List of dynamical systems and differential equations topics

    en.wikipedia.org/wiki/List_of_dynamical_systems...

    Adaptive control; Hierarchical control; Intelligent control; Optimal control; Dynamic programming; Robust control; Stochastic control; System dynamics, system analysis; Takens' theorem; Exponential dichotomy; Liénard's theorem; Krylov–Bogolyubov theorem; Krylov-Bogoliubov averaging method

  8. Adaptive software development - Wikipedia

    en.wikipedia.org/wiki/Adaptive_Software_Development

    Adaptive software development (ASD) is a software development process that grew out of the work by Jim Highsmith and Sam Bayer on rapid application development (RAD). It embodies the principle that continuous adaptation of the process to the work at hand is the normal state of affairs.

  9. Adaptive algorithm - Wikipedia

    en.wikipedia.org/wiki/Adaptive_algorithm

    An example of an adaptive algorithm in radar systems is the constant false alarm rate (CFAR) detector. In machine learning and optimization , many algorithms are adaptive or have adaptive variants, which usually means that the algorithm parameters such as learning rate are automatically adjusted according to statistics about the optimisation ...