Specification-Guided Reinforcement Learning

Reinforcement Learning (RL) is being touted to revolutionize the way we design systems. However, a key challenge to reaching that holy grail comes from the lack of guarantees that the synthesized systems offer. Logic and formal reasoning can address some of these issues ... or can they? In this talk, I will cover recent progress in using logical specifications in RL and discuss the challenges it faces moving forward.

 

Short Bio:
Suguman Bansal is a is an assistant professor in the School of Computer Science at Georgia Institute of Technology. Her research interests lie at the intersection of Artificial Intelligence and Programming Languages. Specifically, she works on developing tools and techniques to improve the quality of automated verification and synthesis of computational systems. Her recent work concerns providing formal guarantees about learning-enabled systems with a focus on Reinforcement Learning.