第一天 其中在开篇的的时候谈到了遗传算法
Genetic Algorithm
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Anatomy of an evolutionary robotics experiment:

  1. Create a task environment.

  2. Create the robot.

  3. Create the robot’s brain, or Artificial Neural Network (ANN).

  4. Use an evolutionary algorithm to optimize the ANN so that the robot performs the

desired task in its environment.
Week plan
Week 1 to Week 10
Complete the weekly work of the question
Weeks 11 to 14: Use the system to conduct an evolutionary robotics experiment.

  1. Given the same optimizer, neural network and eight hours of behavior

optimization on the same computer, does a quadrupedal robot evolve to walk

further or not as far as a hexapedal robot, or is there no significant difference?

  1. Create five fitness functions that not only select for locomotion on the quadrupedal

robot, but each also selects for a particular gait: walking, trotting, canter, galloping

and pronking.

  1. Create a fitness function that rewards NNs for locomotion, but penalizes them for

requiring a lot of energy to realize the gait. This is difficult, as there are two

solutions that are not desirable: evolution finds fast but inefficient gaits, or ‘gaits’ in

which the robot does not move, and therefore does not consume energy.

  1. Equip the robot with a simulated laser range finder, which tells the robot about

objects in its environment. Evolve a robot that walks toward round objects, but
walks away from rectangular objects.
Assign 1
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