Proximal Policy Optimization and its Dynamic Version for Sequence Generation
Table 2: The BLEU-2 Results of different algorithms on OpenSubtitles.
['Algorithms', 'BLEU']
5.2.1 Results Moreover, we find out that the training progress of both PPO and PPO-dynamic are more stable than policy gradient, and the training progress of PPO-dynamic is much faster than the others. This shows that PPO based methods can improve the high variance problem of using REINFORCE, and the dynamic constraint can help the learning converge quickly.