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A Sudoku starts with some cells containing numbers (clues), and the goal is to solve the remaining cells. Proper Sudokus have one solution. [1] Players and investigators use a wide range of computer algorithms to solve Sudokus, study their properties, and make new puzzles, including Sudokus with interesting symmetries and other properties.
The question is whether knowing the warden's answer changes the prisoner's chances of being pardoned. This problem is equivalent to the Monty Hall problem; the prisoner asking the question still has a 1 / 3 chance of being pardoned but his unnamed colleague has a 2 / 3 chance.
Constraint satisfaction problems (CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables, which is solved by constraint satisfaction methods.
The Wonderlic Contemporary Cognitive Ability Test (formerly the Wonderlic Personnel Test) is an assessment used to measure the cognitive ability and problem-solving aptitude of prospective employees for a range of occupations. The test was created in 1939 by Eldon F. Wonderlic.
The two solutions with the vertical axis denoting time, s the start, f the finish and T the torch The bridge and torch problem (also known as The Midnight Train [1] and Dangerous crossing [2]) is a logic puzzle that deals with four people, a bridge and a torch.
The nearest neighbour algorithm was one of the first algorithms used to solve the travelling salesman problem approximately. In that problem, the salesman starts at a random city and repeatedly visits the nearest city until all have been visited. The algorithm quickly yields a short tour, but usually not the optimal one.
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For many algorithms that solve these tasks, the data in raw representation have to be explicitly transformed into feature vector representations via a user-specified feature map: in contrast, kernel methods require only a user-specified kernel, i.e., a similarity function over all pairs of data points computed using inner products.