Trying out a simple example using TuneSearchCV with LGBMClassifier and it fails on start.

Environment:

Python 3.8.3
tune-sklearn 0.3.0
ray 1.3.0
macos mojave 10.14.6

Code:

from ray.tune.sklearn import TuneSearchCV

from lightgbm import LGBMClassifier

lgmb_param_dists = dict(

                boosting_type=['gbdt','dart','rf'],
                num_leaves=(10,500),
 

Currently we use a very ad-hoc procedure for scaling the quadratic component of NAF when used for exploration:
https://github.com/angelolovatto/raylab/blob/9820275b17ee085e1955a6d845c0bdf61333f8da/raylab/algorithms/naf/naf_policy.py#L150-L155

A possibly better alternative would be to scale it based on the desired average action stddev. Something like:

scale_tril * (1.0 / average_st

Implement parameterized linear and non-linear dynamics model with bimodal Gaussian noise.