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:
Recently we have seen many successful applications of Reinforcement Learning (RL). It is natural to extend the scope of RL to vision-based real-time learning of robotic control tasks. However, a vision-based real-time robotic RL agent faces some practical issues oft-ignored in conventional RL research. The first issue we investigated is that robots deployed in the real world are usually tethered to a resource-limited computer, while vision-based RL algorithms are expensive. The second issue we investigated is how to design an effective reward function that is independent of domain knowledge.
Presenter Bio:
Yan Wang is a Master's student in the Department of Computing Science at the University of Alberta, supervised by Rupam Mahmood. He is interested in applying RL methods to practical questions, especially robotic control tasks. He likes playing video games, board games, and reading stories about UFOs.
