Learning to imitate: using GAIL to imitate PPO

Usually, in reinforcement learning, the agent is provided with a reward according to the action it executes to interact with the environment and its goal is to optimize its total cumulative reward over multiple steps. Actions are selected according to some observations the agent has to learn to interpret. In this post, we are going to explore a new field called imitation learning: the agent … Continue reading Learning to imitate: using GAIL to imitate PPO

SeqGAN: text generation with generative models

In this post we propose to review recent history of research in the Natural Language Generation (NLG) tasks of the Natural Language Processing domain. Realistic human-like language generation has been a challenge for researches that has recently come into greater focus with the release of large neural models for NLP like the GPT and BERT models. In this post we propose to focus ourselves on … Continue reading SeqGAN: text generation with generative models