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  2. List of games using procedural generation - Wikipedia

    en.wikipedia.org/wiki/List_of_games_using...

    Procedural generation is a common technique in computer programming to automate the creation of certain data according to guidelines set by the programmer. Many games generate aspects of the environment or non-player characters procedurally during the development process in order to save time on asset creation.

  3. Random number table - Wikipedia

    en.wikipedia.org/wiki/Random_number_table

    In the 1950s, a hardware random number generator named ERNIE was used to draw British premium bond numbers. The first "testing" of random numbers for statistical randomness was developed by M.G. Kendall and B. Babington Smith in the late 1930s, and was based upon looking for certain types of probabilistic expectations in a given sequence. The ...

  4. List of children's games - Wikipedia

    en.wikipedia.org/wiki/List_of_children's_games

    A child playing tag.. This is a list of games that are played by children.Traditional children's games do not include commercial products such as board games but do include games which require props such as hopscotch or marbles (toys go in List of toys unless the toys are used in multiple games or the single game played is named after the toy; thus "jump rope" is a game, while "Jacob's ladder ...

  5. Randomization - Wikipedia

    en.wikipedia.org/wiki/Randomization

    Randomization is a statistical process in which a random mechanism is employed to select a sample from a population or assign subjects to different groups. [1] [2] [3] The process is crucial in ensuring the random allocation of experimental units or treatment protocols, thereby minimizing selection bias and enhancing the statistical validity. [4]

  6. Training, validation, and test data sets - Wikipedia

    en.wikipedia.org/wiki/Training,_validation,_and...

    A training data set is a data set of examples used during the learning process and is used to fit the parameters (e.g., weights) of, for example, a classifier. [9] [10]For classification tasks, a supervised learning algorithm looks at the training data set to determine, or learn, the optimal combinations of variables that will generate a good predictive model. [11]

  7. Randomized algorithm - Wikipedia

    en.wikipedia.org/wiki/Randomized_algorithm

    A randomized algorithm is an algorithm that employs a degree of randomness as part of its logic or procedure. The algorithm typically uses uniformly random bits as an auxiliary input to guide its behavior, in the hope of achieving good performance in the "average case" over all possible choices of random determined by the random bits; thus either the running time, or the output (or both) are ...

  8. Monte Carlo method - Wikipedia

    en.wikipedia.org/wiki/Monte_Carlo_method

    Possible moves are organized in a search tree and many random simulations are used to estimate the long-term potential of each move. A black box simulator represents the opponent's moves. [80] The Monte Carlo tree search (MCTS) method has four steps: [81] Starting at root node of the tree, select optimal child nodes until a leaf node is reached.

  9. Random optimization - Wikipedia

    en.wikipedia.org/wiki/Random_optimization

    Random optimization (RO) is a family of numerical optimization methods that do not require the gradient of the optimization problem and RO can hence be used on functions that are not continuous or differentiable. Such optimization methods are also known as direct-search, derivative-free, or black-box methods.