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  2. How to Solve It - Wikipedia

    en.wikipedia.org/wiki/How_to_Solve_It

    Genre. Mathematics, problem solving. Publication date. 1945. ISBN. 9780691164076. How to Solve It (1945) is a small volume by mathematician George Pólya, describing methods of problem solving. [1] This book has remained in print continually since 1945.

  3. Problem solving - Wikipedia

    en.wikipedia.org/wiki/Problem_solving

    Problem solving is the process of achieving a goal by overcoming obstacles, a frequent part of most activities. Problems in need of solutions range from simple personal tasks (e.g. how to turn on an appliance) to complex issues in business and technical fields. The former is an example of simple problem solving (SPS) addressing one issue ...

  4. Divide-and-conquer algorithm - Wikipedia

    en.wikipedia.org/wiki/Divide-and-conquer_algorithm

    A divide-and-conquer algorithm recursively breaks down a problem into two or more sub-problems of the same or related type, until these become simple enough to be solved directly. The solutions to the sub-problems are then combined to give a solution to the original problem. The divide-and-conquer technique is the basis of efficient algorithms ...

  5. Three-part lesson - Wikipedia

    en.wikipedia.org/wiki/Three-part_lesson

    Students engage in solving math problems individually, in pairs, or in small groups, and "record the mathematical thinking they used to develop solutions". Students then plan the strategies, methods, and concrete materials they will use to solve the problem.

  6. Greedy algorithm - Wikipedia

    en.wikipedia.org/wiki/Greedy_algorithm

    A greedy algorithm is any algorithm that follows the problem-solving heuristic of making the locally optimal choice at each stage. [1] In many problems, a greedy strategy does not produce an optimal solution, but a greedy heuristic can yield locally optimal solutions that approximate a globally optimal solution in a reasonable amount of time.

  7. Mathematical optimization - Wikipedia

    en.wikipedia.org/wiki/Mathematical_optimization

    Mathematical optimization (alternatively spelled optimisation) or mathematical programming is the selection of a best element, with regard to some criterion, from some set of available alternatives. [1] [2] It is generally divided into two subfields: discrete optimization and continuous optimization.

  8. Brute-force search - Wikipedia

    en.wikipedia.org/wiki/Brute-force_search

    Brute-force search. In computer science, brute-force search or exhaustive search, also known as generate and test, is a very general problem-solving technique and algorithmic paradigm that consists of systematically checking all possible candidates for whether or not each candidate satisfies the problem's statement.

  9. 100 prisoners problem - Wikipedia

    en.wikipedia.org/wiki/100_prisoners_problem

    100 prisoners problem. Each prisoner has to find their own number in one of 100 drawers, but may open only 50 of the drawers. The 100 prisoners problem is a mathematical problem in probability theory and combinatorics. In this problem, 100 numbered prisoners must find their own numbers in one of 100 drawers in order to survive.

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