Question

The following figure shows a genetic algorithm. Briefly describe why the genetic algorithm should have the function 'REPRODUCE (x, y). (5pts) function GENETIC-ALGORITHM(population, FITNESS-FN) returns an individual inputs: population, a set of individuals FITNESS-FN, a function that measures the fitness of an individual repeat new-population ? empty set for i = 1 to SIZE(population) do x ? RANDOM-SELECTION(population, FITNESS-FN) y ? RANDOM-SELECTION(population, FITNESS-FN) child ? REPRODUCE(x, y) if (small random probability) then child ? MUTATE(child) add child to new_population population ? new_population until some individual is fit enough, or enough time has elapsed return the best individual in population, according to FITNESS-FN function REPRODUCE(x, y) returns an individual inputs: x, y, parent individuals n ? LENGTH(x); c ? random number from 1 to n return APPEND(SUBSTRING(x, 1, c), SUBSTRING(y, c + 1, n))

          The following figure shows a genetic algorithm. Briefly describe why the genetic algorithm should have
the function 'REPRODUCE (x, y). (5pts)
function GENETIC-ALGORITHM(population, FITNESS-FN) returns an individual
inputs: population, a set of individuals
FITNESS-FN, a function that measures the fitness of an individual
repeat
new-population ? empty set
for i = 1 to SIZE(population) do
x ? RANDOM-SELECTION(population, FITNESS-FN)
y ? RANDOM-SELECTION(population, FITNESS-FN)
child ? REPRODUCE(x, y)
if (small random probability) then child ? MUTATE(child)
add child to new_population
population ? new_population
until some individual is fit enough, or enough time has elapsed
return the best individual in population, according to FITNESS-FN
function REPRODUCE(x, y) returns an individual
inputs: x, y, parent individuals
n ? LENGTH(x); c ? random number from 1 to n
return APPEND(SUBSTRING(x, 1, c), SUBSTRING(y, c + 1, n))

The following figure shows a genetic algorithm. Briefly describe why the genetic algorithm should have
the function 'REPRODUCE (x, y). (5pts)
function GENETIC-ALGORITHM(population, FITNESS-FN) returns an individual
inputs: population, a set of individuals
FITNESS-FN, a function that measures the fitness of an individual
repeat
new-population ? empty set
for i = 1 to SIZE(population) do
x ? RANDOM-SELECTION(population, FITNESS-FN)
y ? RANDOM-SELECTION(population, FITNESS-FN)
child ? REPRODUCE(x, y)
if (small random probability) then child ? MUTATE(child)
add child to newpopulation
population ? newpopulation
until some individual is fit enough, or enough time has elapsed
return the best individual in population, according to FITNESS-FN
function REPRODUCE(x, y) returns an individual
inputs: x, y, parent individuals
n ? LENGTH(x); c ? random number from 1 to n
return APPEND(SUBSTRING(x, 1, c), SUBSTRING(y, c + 1, n))

Added by Makayla R.

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