Query network based limited guidance for RL agents

Advisor: Prof. Katia Sycara, School of Computer Science, Carnegie Mellon University

System Overview:

• Designed a neural network based observer policy capable of identifying states for which an RL agent is confused and facilitate efficient communication with an expert
• Resulting network cuts down on episode lengths and improves episode return while minimizing expert queries

The project report can be downloaded from here.