Please fill in the blanks with prepositions only.
The program starts
with a population of 20 digital chromosomes,
each consisting of an initially random binary digit that corresponds to a muscle wire - where a 1 represents its activation and a 0 its deactivation. Each of these chromosomes forms the basis of a series of movements in the robot.
"You end
a cyclic pattern of muscle activation," says Bentley. Some may result
the robot moving and some will not. The GA tries them all
and awards them a fitness rating, depending
how far it makes the snake move.
The two best chromosomes are then saved, the remainder are mixed
or randomly mutated and the process is repeated. After a number of generations, the amount of improvement finally tends to taper
, says Mahdavi, indicating that the GA has reached a performance plateau.
Once the robot was mobile, the team disabled some of its segments to see if it could adapt to injury. Initially it was immobilised, says Bentley, but as the GA continued to try to improve the locomotion, it gradually worked
how to move again, albeit more awkwardly and with an ungainly, dragging gait - but it was still good enough to get the robot to its destination.