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Summary
Created a config for PID and BB that I ran locally (and saved the outputs to
results/local_pid/andresults/local_bb/) which gave reasonable CVGA graphs for 1000 timesteps. The PID parameters will have to be tuned to find better parameters, this paper kind of says there isn't an easy way to optimally find the PID parameters (bottom of page 8) so might want to do some paper reviewing.Since the kwargs for the PID and BB controllers are a little ad-hoc I didn't want to make config classes for them, so instead I just added the
kwargsparameter to the model config class.Other changes
experiment_runner.pyout oftraining/and into the basesrcdir