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  2. Proof by exhaustion - Wikipedia

    en.wikipedia.org/wiki/Proof_by_exhaustion

    Proof by exhaustion, also known as proof by cases, proof by case analysis, complete induction or the brute force method, is a method of mathematical proof in which the statement to be proved is split into a finite number of cases or sets of equivalent cases, and where each type of case is checked to see if the proposition in question holds. [1]

  3. Reinforcement learning - Wikipedia

    en.wikipedia.org/wiki/Reinforcement_learning

    The brute force approach entails two steps: For each possible policy, sample returns while following it; Choose the policy with the largest expected discounted return; One problem with this is that the number of policies can be large, or even infinite.

  4. Trial and error - Wikipedia

    en.wikipedia.org/wiki/Trial_and_error

    In the field of computer science, the method is called generate and test (brute force). In elementary algebra, when solving equations, it is called guess and check. [citation needed] This approach can be seen as one of the two basic approaches to problem-solving, contrasted with an approach using insight and theory.

  5. Brute-force search - Wikipedia

    en.wikipedia.org/wiki/Brute-force_search

    Brute force attacks can be made less effective by obfuscating the data to be encoded, something that makes it more difficult for an attacker to recognise when he has cracked the code. One of the measures of the strength of an encryption system is how long it would theoretically take an attacker to mount a successful brute force attack against it.

  6. Algorithm - Wikipedia

    en.wikipedia.org/wiki/Algorithm

    Brute-force or exhaustive search Brute force is a problem-solving method of systematically trying every possible option until the optimal solution is found. This approach can be very time-consuming, testing every possible combination of variables. It is often used when other methods are unavailable or too complex.

  7. Dynamic programming - Wikipedia

    en.wikipedia.org/wiki/Dynamic_programming

    While more sophisticated than brute force, this approach will visit every solution once, making it impractical for n larger than six, since the number of solutions is already 116,963,796,250 for n = 8, as we shall see. Dynamic programming makes it possible to count the number of solutions without visiting them all.

  8. Search algorithm - Wikipedia

    en.wikipedia.org/wiki/Search_algorithm

    Specific applications of search algorithms include: Problems in combinatorial optimization, such as: . The vehicle routing problem, a form of shortest path problem; The knapsack problem: Given a set of items, each with a weight and a value, determine the number of each item to include in a collection so that the total weight is less than or equal to a given limit and the total value is as ...

  9. Lateral computing - Wikipedia

    en.wikipedia.org/wiki/Lateral_computing

    The traditional or conventional approach to solving computing problems is to either build mathematical models or have an IF- THEN -ELSE structure. For example, a brute-force search is used in many chess engines, [2] but this approach is computationally expensive and sometimes may arrive at poor solutions. It is for problems like this that ...