Hi,
When creating a custom environment in MATLAB for use with the Reinforcement Learning Toolbox, you can define a 'step' function that advances the environment's state based on the agent's action. To simulate the environment at a faster rate than the agent operates, modify the 'step' function to perform multiple updates (10 updates of 1ms each) for each call to the 'step' function.
Refer to the following code snippet:
for i = 1:10
% Update the environment state based on the action
% Assume updateEnvironment is a function that updates the environment state
% for a 1ms timestep given the current state and action
loggedSignals = updateEnvironment(loggedSignals, action);
end
Hope it helps!
