Hello,
I implemented deep reinforcement learning in Matlab based on a custom template and saved some agents with high rewards. I was plotting signals in the training phase in each episode and can see the desired performance. I saved all state and control effort (Action) in each episode. My action space is as follows:
numAct = 1;
ActionInfo = rlNumericSpec([numAct 1], 'LowerLimit' ,-0.4189, 'UpperLimit' ,0.4189);
I have a problem with the simulation of the trained agent.
The first figure is one of the results of a training phase and part of the variation of it's action value.
After the simulation, with the below command,
simOptions = rlSimulationOptions('MaxSteps',maxSteps);
experience = sim(env,agent,simOptions);
or for saved agent
experience = sim(env,saved_agent,simOptions);
The result is wrong according to the below figure.
I checked the final agent and some of the high rewards agents. But, the results are similar to the above figure.
After the simulation of the trained agent the action is fixed to lower or upper values of action space acording to above figure for all simulated agents!
Thank you for any help you can offer.
