Trial and Error

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Trial and Error is a general problem solving method in contrast of an approach using insight and theory. In science, formulation and testing of hypotheses is based on trial and error, in computer science also called generate and test, and in elementary algebra, when solving certain equations, called guess and check. Learning and optimization methods such as genetic algorithms, simulated annealing and reinforcement learning also apply trial and error methods. In general, trial and error makes no attempt to discover why a solution works, but that it is a solution. A further application related to computer chess is to find factors for the application of Magic Bitboards with spare populated, but otherwise randomly chosen numbers.

=See also=
 * Automated Tuning
 * Backtracking
 * Book Learning
 * Brute-Force
 * Genetic Programming
 * Learning
 * Looking for Magics
 * Monte-Carlo Tree Search
 * Reinforcement Learning
 * Simulated Annealing

=Selected Publications=
 * Donald Michie (1961). Trial and Error. Penguin Science Survey, pdf
 * Herbert A. Simon, Peter A. Simon (1962). Trial and Error Search in Solving Difficult Problems: Evidence from the Game of Chess. Behavioral Science, Vol. 7, No. 4, pp. 425-429

=External Links=
 * Trial and error from Wikipedia
 * Trial and error (disambiguation) from Wikipedia
 * Generate-And-Test Search - Artificial Intelligence
 * Generate and Test from adiwebs.com
 * Problem Solving: Guess and Check - TeacherVision.com
 * NP-complete from Wikipedia
 * Dreams - Try Me, Dreams (1970), YouTube Video
 * Randy Brecker, Michael Brecker, Barry Rogers, Billy Cobham, John Abercrombie, Edward Vernon, Jeff Kent, Doug Lubahn

=References=

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