On-line Active Reward Learning for Policy Optimisationin Spoken Dialogue Systems
Table 2: Statistical evaluation of the prediction of the on-line GP systems with respect to Subj rating.
['[ITALIC]  [BOLD] Subj', '[BOLD] Prec.', '[BOLD] Recall', '[BOLD] F-measure', '[BOLD] Number']
The above results verify the effectiveness of the proposed reward model for policy learning. Here we investigate further the accuracy of the model in predicting the subjective success rate.