Change learning rate of RL DDPG networks after 1st training

I trained my DDPG networks using a particular learning rate. Now I want to improve the network by using a lower learning rate.

How do I change the learning rate without losing my perviously trained results?

[Jonathan Zea]

I think you can train with your initial learning rate for a while, save the agent using the saveAgent option, loading after, and then change the learning rate and restart training.

% telling matlab to save the agent from 10 episode in folder "myfolder".

opts = rlTrainingOptions(...

'SaveAgentDirectory', myfolder, 'SaveAgentValue', 10);

% training agent in environment

trainingInfo = train(agent, env, opts);

After training for a while...

agent = load(...) % load the trained agent

actor = agent.getActor;

actor.Options.LearnRate = 0.001; % your new learning rate

agent = agent.setActor(actor);

% retrain agent in environment

trainingInfo = train(agent, env, opts);