a2rl.utils.action_reward#

a2rl.utils.action_reward(df, lag, mask=False)[source]#

Test for the effect of the action on the reward in the data H(reward|prev_action).

Parameters:
  • df (WiDataFrame) – a discretized dataframe.

  • lag (int) – int for the lag.

Return type:

float

Returns:

Returns the conditional entropy of future reward given various lags. It is masked if the information gain is better than random