How do I define a continuous reward function for RL environment?
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Prashanth Chivkula
on 5 Oct 2020
Commented: Emmanouil Tzorakoleftherakis
on 12 Oct 2020
I am trying to follow the double integrator example for giving a continuous reward function. When I used the custom template, and defined the reward using the QR cost function, I get an error stating that the reward should be a scalar value. Where can I find the property of reward and change it to accept vector values?
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Priysha LNU
on 8 Oct 2020
Here is an excerpt from the documentation :
To guide the learning process, reinforcement learning uses a scalar reward signal generated from the environment.
For detailed information on defining reward signals, discrete and continous rewards, please refer to this documentation link.
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