Population while new population is not full merge new

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Unformatted text preview: ganism will live another cycle (generation) Basis for the natural selection simulation Organisms are selected to mate with probabilities proportional to their fitness Probabilistically better solutions have a better chance of conferring their building blocks to the next generation (cycle) A Simple GA Generate initial population do Calculate the fitness of each member // simulate another generation do Select parents from current population Perform crossover add offspring to the new population while new population is not full Merge new population into the current population Mutate current population while not converged How do GAs work The structure of a GA is relatively simple to comprehend, but the dynamic behavior is complex Holland has done significant work on the theoretical foundations of Gas “GAs work by discovering, emphasizing, and recombining good ‘building blocks’ of solutions in a highly parallel fashion.” Melanie Mitchell, paraphrasing John Holland Using formalism Notion of a building block is formalized as a schema Schemas are propagated or destroyed according to the laws of probability Schema A template, much like a regular expression, describing a set of strings The set of strings represented by a given schema characterizes a set of candidate solutions sharing a property This property is the encoded equivalent of a building block Example 0 or 1 represents a fixed bit Asterisk represents a “don’t care...
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