- Define the Environment interface
- Create the Custom Environment
- Create the Q-Table
- Implement the Learning Algorithm
- Create the MATLAB Environment Object
rlNumericSpec and rlFiniteSetSpec multi channell environment + Qtable
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I'm seeking to develop a custom environment for a (partially observable) Q learning problem. In particular I'm interested in been able to use in my environment a DT markov chain and some differential equations ( which estimante the state of the Markov chain). Something like have observations which are rlNumericSpec and rlFiniteSetSpec. In other words I would need my observations to have multiple channels and make use of a Qtable
Is there some best practice/ideas on how to accomplish this?
Cheers
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Aditya
2024년 1월 16일
Developing a custom environment for a partially observable Q-learning problem with a discrete-time (DT) Markov chain and differential equations is a complex task. However, MATLAB provides the tools necessary to create such an environment. Here are some best practices and ideas to help you accomplish this:
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