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  2. Algorithmic Puzzles - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_Puzzles

    Reviewer Narayanan Narayanan recommends the book to any puzzle aficionado, or to anyone who wants to develop their powers of algorithmic thinking. [4] Reviewer Martin Griffiths suggests another group of readers, schoolteachers and university instructors in search of examples to illustrate the power of algorithmic thinking. [ 3 ]

  3. Computational thinking - Wikipedia

    en.wikipedia.org/wiki/Computational_thinking

    The history of computational thinking as a concept dates back at least to the 1950s but most ideas are much older. [6] [3] Computational thinking involves ideas like abstraction, data representation, and logically organizing data, which are also prevalent in other kinds of thinking, such as scientific thinking, engineering thinking, systems thinking, design thinking, model-based thinking, and ...

  4. Computational creativity - Wikipedia

    en.wikipedia.org/wiki/Computational_creativity

    Edmond de Belamy, an artwork generated by a generative adversarial network. Computational creativity (also known as artificial creativity, mechanical creativity, creative computing or creative computation) is a multidisciplinary endeavour that is located at the intersection of the fields of artificial intelligence, cognitive psychology, philosophy, and the arts (e.g., computational art as part ...

  5. List of algorithms - Wikipedia

    en.wikipedia.org/wiki/List_of_algorithms

    An algorithm is fundamentally a set of rules or defined procedures that is typically designed and used to solve a specific problem or a broad set of problems.. Broadly, algorithms define process(es), sets of rules, or methodologies that are to be followed in calculations, data processing, data mining, pattern recognition, automated reasoning or other problem-solving operations.

  6. Algorithmic technique - Wikipedia

    en.wikipedia.org/wiki/Algorithmic_technique

    There are several broadly recognized algorithmic techniques that offer a proven method or process for designing and constructing algorithms. Different techniques may be used depending on the objective, which may include searching, sorting, mathematical optimization, constraint satisfaction, categorization, analysis, and prediction.

  7. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    Examples of such greedy algorithms are Kruskal's algorithm and Prim's algorithm for finding minimum spanning trees and the algorithm for finding optimum Huffman trees. Greedy algorithms appear in the network routing as well. Using greedy routing, a message is forwarded to the neighbouring node which is "closest" to the destination.

  8. This is why you should give your dog choices when training ...

    www.aol.com/why-dog-choices-training-them...

    Often, our pets don’t get to make their own choices, as we decide when they need to go to the vet and when we feed them, for example. So, giving them choices during training sessions can go a ...

  9. Analysis of algorithms - Wikipedia

    en.wikipedia.org/wiki/Analysis_of_algorithms

    For example, since the run-time of insertion sort grows quadratically as its input size increases, insertion sort can be said to be of order O(n 2). Big O notation is a convenient way to express the worst-case scenario for a given algorithm, although it can also be used to express the average-case — for example, the worst-case scenario for ...