As of R2020b, the RL Agent block does not support Code Generation (we are working on it) and is currently only used for training a Reinforcement Learning Agent in Simulink.
However, in R2020b, native Simulink blocks such as 'Image Classifier' and 'Predict' were introduced in Deep Learning Toolbox, and the MATLAB function block was enhanced to model Deep Learning networks in Simulink. These blocks allow using pre-trained networks including Reinforcement Learning policies in Simulink to perform inference.
Also, in R2021a, plain C Code generation for Deep Learning networks is supported (so no dependence on 3p libraries like one-dnn), which enables code generation from the native DL blocks and the enhanced MATLAB function block mentioned above.
Using these features, steps you could follow in R2021a are:
1) Use either Predict or the MATLAB function block to replace the existing RL Agent block, and pull in your trained agent into Simulink
2) Leverage the Plain C Code generation feature to generate code for your Reinforcement Learning Agent
To create a function that can be used within the 'MATLAB function' block to evaluate the learned policy (pre-trained agent), or to create ‘agentData’ that can be imported into the 'Predict' block, please refer to the 'generatePolicyFunction' API.