RESEARCH
ML APPLICATIONS
IR-VIC: Unsupervised Discovery of Sub-goals for Transfer in RL
January 5, 2021
Abstract
We propose a novel framework to identify subgoals useful for exploration in sequential decision making tasks under partial observability. We utilize the variational intrinsic control framework (Gregor et.al., 2016) which maximizes empowerment – the ability to reliably reach a diverse set of states and show how to identify sub-goals as states with high necessary option information through an information theoretic regularizer. Despite being discovered without explicit goal supervision, our subgoals provide better exploration and sample complexity on challenging grid-world navigation tasks compared to supervised counterparts in prior work.
AUTHORS
Written by
Nirbhay Modhe
Prithvijit Chattopadhyay
Mohit Sharma
Abhishek Das
Publisher
International Joint Conference on Artificial Intelligence (IJCAI)
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