Optimisation for Artificial Intelligence, a 4-day course

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**Evolutionary methods** become of interest when exact methods reach their limits because of combinatorial of the problem running out of control; functions to optimise behaving as black boxes, with noisy output; or functions with complex shapes and difficulty to run out of local minima.

The premise of evolutionary computation is simple: the simulation of natural selection used to solve a problem, where candidate solutions compete as individuals in order to inﬂuence future generations. From this simple premise, a multitude of algorithms have been developed, and evolutionary computation can be found in a number of domains.

Topics | |
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8.0 | A bestiary of functions for optimisation |

8.1 | Simulated annealing |

8.2 | Genetic algorithms |

8.3 | CMA-ES |

At this point of the course, as many of such methods are more of