Hi,
I understand that you want to initialize the 'rlTable' with the values of the predefined matrix.
Assuming you have 243 states and 5 actions, this can be done as follows.
obsInfo = rlFiniteSetSpec([1:243]);
actInfo = rlFiniteSetSpec([1:5]);
qTable = rlTable(obsInfo,actInfo); %This step initializes the Q-table to all 0s.
%Here, I am generating a random matrix for testing.
% Instead, you can use your matrix directly in the next line of code
mean_QTables = rand(243,5);
% This will assign the scalar values
% present in 'mean_QTables' matrix to the rlTable variable 'qTable'
qTable.Table = mean_QTables;
For more information, please refer to these resources.
- Q-Value function approximator object for reinforcement learning agents - MATLAB: https://www.mathworks.com/help/reinforcement-learning/ref/rl.function.rlqvaluefunction.html#mw_d745cee1-79f5-43b5-9ca0-274a06be0272
- Value table or Q table - MATLAB: https://www.mathworks.com/help/reinforcement-learning/ref/rltable.html
- Create specifications object for a finite-set action or observation channel - MATLAB: https://www.mathworks.com/help/reinforcement-learning/ref/rl.util.rlfinitesetspec.html
Hope this helps in resolving your query!
