DIKU Bits: Efficient Robot Learning under Uncertainty
Speaker
Hang Yin, Assistant Professor - Tenure Track in the Image Analysis, Computational Modelling, and Geometry section (IMAGE)
Title
Efficient Robot Learning under Uncertainty
Abstract
Imagine a robot opening your dishwasher, taking out cleaned cutlery and placing them back into a cabinet. Such a task is seemingly less intelligence demanding than creating legible texts and image arts. Then why haven’t we got such AI systems? In this talk, I will present my opinions on the difficulties in learning embodied agents that live in a physical world. I will review some recent research efforts on acquiring robot skills through data-driven methods. Sharing with you my own research, I will discuss how our knowledge in modelling and controlling other cyber-physical systems may help in building efficient learning algorithms.
Which courses do you teach?
Vision and Image Processing (VIP)
Simulation-based Reinforcement Learning (SiRL)
Which technology/research/projects/startup are you excited to see the evolution of?
New design, computing methods, and applications involving robots and broader AI systems.