load multiple trained reinforcement agents into MATLAB workspace

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I have trained a DDPQ reinforcement learning agent and saved all agents with a reward over a set critieria.
These have all been saved into the same file directory autonomously with the name "AgentXXXX" with XXXX being the training iteration (note these are not necassarily sequential).
I am looking to assess them all over 10 randomly initiated tests to identify the top 5% for further testing.
The question I have is how to import all the agents to the matlab workspace with unique names as to test them all in one for loop so I do not have to manually load each agent.
there are around 2000 saved agents.

Accepted Answer

Anh Tran
Anh Tran on 6 Mar 2020
Edited: Anh Tran on 9 Mar 2020
It is not neccessary to load all 2000 agents into MATLAB (consume memory and tricky to assign unique name) to evaluate their performance. Instead, I believe a more reasonable approach would be load an agent, run 10 tests, log results and repeat
% get a list of all mat file in the folder, assuming only agent are saved in the folder as mat file
listing = dir('*.mat');
for ct = 1:numel(listing)
load(listing(ct).name)
% run test on agent
% log result
end
% combine result from each agent
% analyze
  1 Comment
Alex Grimshaw
Alex Grimshaw on 9 Mar 2020
Thanks for the answer.
This is almost exactly what I have ended up implementing and performing iteratively and worked really well.

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R2019b

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