AI Seminar Series 2023: Gautham Vasan, Learning Sparse-Reward Tasks on Real Robots From Scratch
The AI Seminar is a weekly meeting at the University of Alberta where researchers interested in artificial intelligence (AI) can share their research. Presenters include both local speakers from the University of Alberta and visitors from other institutions. Topics can be related in any way to artificial intelligence, from foundational theoretical work to innovative applications of AI techniques to new fields and problems.
Abstract:
Learning from experience and continual adaptation to changing environments is crucial for intelligent robots to solve an open-ended sequence of increasingly complex tasks. In this talk, I’ll outline some oft-ignored, practical challenges of continual learning on real-world robots and address two such issues: (i) How to specify reinforcement learning tasks?, and (ii) How to set up a real-time learning agent? Our findings helped us produce the first demonstration of pixel-based control by real-time model-free learning on four different kinds of real robots from scratch in just a few hours.
Presenter Bio:
Gautham Vasan is a PhD student at the University of Alberta, advised by Dr. Rupam Mahmood. He is interested in building machines with human-like intelligence. His research focuses on policy gradient methods, real-time learning architectures and temporal abstraction in reinforcement learning. At Kindred Systems Inc, he worked on developing deep reinforcement learning techniques for an automated put wall robot, known as SORT, which efficiently identifies apparel items, picks them, places them, and sorts them into complete end-customer orders. His website:
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