Rethinking Action Spaces for Reinforcement Learning in End-to-end Dialog Agents with Latent Variable Models
Table 2: Results on DealOrNoDeal. Diversity is measured by the number of unique responses the model used in all scenarios from the test data.
['[EMPTY]', 'PPL', 'Reward', 'Agree%', 'Diversity']
rewards with a much smaller performance drop in language quality (PPL), whereas the word-level model can only increase its task rewards by deviating significantly from natural language.