Simulated annealing is a method that is used to remove any conflicts in data structures. In metallurgy, annealing is a process of slow cooling of metals to make them stronger. In the Artificial Intelligence domain, it refers to a similar process in which the temperature is reduced slowly of a variable that eventually leads to the arrival of greedy descent as the temperature comes closer to zero. Values when using simulated annealing stay assigned to the working variables, which are random by nature. The assignment of the values in the AI system is done based on the improvement in the result of the previous steps in the iteration to ensure that there is a way in which the AI system can be tracked of its ability to learn and implement new things.
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