i am trying to use Reinforcement learning toolbox for a vehicle where i have two inputs /observations for the Reinforcement learning toolbox-DQN Agent and one action to be taken by the DQN Agent. The action has discrete 40 discrete value. Three hiddens layers are to be used with sizes of 20,50 and 100.
- how to define hidden layers size in the script? is it the size of "fullyConnectedLayer(L,'Name','fc1')"
- what should be the size parameter for " imageInputLayer([2 1 1],'Normalization','none','Name','state')" ?
- my simulation gives error of
Error using rl.env.AbstractEnv/sim (line 121)
An error occurred while simulating "RL_hev_control"with the agent "agent".
Error in RL_HEVsimulink (line 79)
experience = sim(env,agent,simOptions);
Error using Simulink.SimulationInput/sim Not enough room in the buffer to store the new experiences. Make sure the bufferSize argument is big enough.
What could be the mistake i am doing ?