Determining DQN architecture for a chess agent

I’m working on training an RL agent to play chess – I’m using the open_spiel library, so it’s more connecting the premade pieces (i.e. the chess env and the RL model are already created). However, I’m wondering how to set the model hyperparameters, particularly regarding the number of hidden layers and number of nodes per hidden layer. How should I approach this problem?

submitted by /u/shadowknife392
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