Kristian Hartikainen

Exploration in Approximate Hyper-State Space for Meta Reinforcement\n Learning

2020 · arXiv (Cornell University)

To rapidly learn a new task, it is often essential for agents to explore\nefficiently -- especially when performance matters from the first timestep. One\nway to learn such behaviour is via meta-learning. Many existing methods however\nrely …