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8/9/2019 Hence the Name Genetic Algorithm - The Programming Model is Based on DNA
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introduces an element of randomness that allows variation in the solution sets, which
otherwise would stagnate and have no advantage over a hand-crafted solution. Mutations
may diminish the strength of some solutions, but in general it will increase the overallvalue of the solution set; by including a very small mutation rate, you introduce new traits
that might never have otherwise existed within the pool. This allows you to explore a
larger group of possibilities and avoid stagnation. In fact, many other AI techniques forgothe idea of breeding solutions and work simply by making small "mutations" or changes
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to a potential solution to a problem.
Genetic algorithms can do some amazing things and solve very complex problems.
Nevertheless, this techniques will require having way of evaluating possible solutions --
this is one of the most difficult problems with genetic algorithms. The second challenge
8/9/2019 Hence the Name Genetic Algorithm - The Programming Model is Based on DNA
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is finding a good way to represent solutions to the problem as strings. Once these are
sorted out, a genetic algorithm may be a good approach to your problem.
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