Using time as a negative reward in RL toolbox

I want to use RL toolbox to train a DQN agent. Right now, i'm using the related step_function to implement the reward function. The problem is I don't know how to punish the agent for taking too long to do the objective. How should I add time to my reward function in this toolbox? Your help is appreciated.

function [NextObs,Reward,IsDone,LoggedSignals] = WW6_StepFunction_genloss(Action,LoggedSignals)

a = Action;
obj=4;
d=[1 2];
state = LoggedSignals.State;

[next_state, ~, genloss]=attack_eff_WW6(state, a, d);

LoggedSignals.State = next_state;
NextObs = LoggedSignals.State;
Down=nnz(~next_state);

IsDone = Down==11;

Reward=genloss;

end

Answer 1

[Kartik Saxena]

Hi,

I understand that you want to add time penalty in the reward function to punish it for taking too long.

The example given below in the MathWorks documentation would be useful for this purpose:

https://www.mathworks.com/help/reinforcement-learning/ug/create-matlab-environments-using-custom-functions.html

You can refer to it and introduce penalty in your reward function by deducting from the reward as per your requirements, instead of adding '1'.

I hope this resolves your issue.