Guided reinforcement learning and imitation learning (GRILL)

This project explores ways of speeding up RL and making it more suitable for neuromorphic hardware by giving it guidance in various ways. There are a variety of techniques to explore, and different groups involved in the project can look at different learning rules and different sorts of guidance. We will focus on tasks using the OpenAI Gym framework, with particular attention to the Atari game Montezuma’s Revenge and sequential tasks using the minigrid world framework. There has also been significant interest in looking at GPT-3 as a method for providing few-shot guidance in RL tasks.