Code for the Joint Learning paper #2
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Added the new parameter p to shift the h0 reference in the release family of functions from the old measurement point to the new one. Added the integration function to take this param as input too. Added the integration function implementing the release constraint.
in the model added: - the new objectives function - load exogenous signals for inputs 4 onwards - activate or deactivate the release constraint
New model of Lake Como featuring the joint learning approach. This model load additional matrices of variables (time x additional dimension). These are used after the 3 BOP inputs and the exogenous signals input. Which matrices and which column of it to use is coded into the decision variable string in the end after the parameters for the policy.
Just more readable.
lik in model_lakecomo moved from pointer to reference to make the code more readable.
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A new version of the Lake Como model, where after the basic information (day and level) and exogenous signals (forecast or observation), it is possible to add multiple variables and have the MOEA choose which one to use and which column (property of the variable or pre-processed information) to use.