Galapagos, Octopus

Dear All,

I want to know what is the control technique that Galapagos or octopuses using for its optimization?

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Imaging you have multiple attributes working together to reach a goal, and you want to know the values of these attributes.

First you need know your goal, e.g. minimum volume or maximum energy receive. Then somehow translate the goal as math expression, e.g. goal = a + b. The express will be the “landscape function” which means optimization will take it as an “exam”. Galapagos can and only take one function at a time, while Octopuses can take more than one.

Next, you feed related attributes as variables to the optimization component. It will compute different combination of the variables in the “landscape function”. Sometimes the optimization results a certain set of variables, which is the root of the function. But other times it can’t get the answer due to the function is unsolvable. In these cases, the optimization provides some answers that “feels” right.

Dear Zhau,
Thank you so much for your reply.
My goal in compares the control techniques. I am controlling the adaptive facade with RL to achieve my goal which is minimizing energy.
And I need to have another result with another controller technique.

I need to know what controller (the name)octopus or Galapagos using,not algorithm

Hi -

I don’t know where you draw the line between “controller” and “algorithm” and it doesn’t really matter. If you don’t find what you are looking for in the following article on Galapagos, you’ll likely have to make things up all by yourself…

Evolutionary Principles applied to Problem Solving - Grasshopper (