Timezone: »

 
Invited Talk - "Walking the Boundary of Learning and Interaction"
Dorsa Sadigh · Erdem Biyik

Fri Dec 11 07:45 AM -- 08:30 AM (PST) @
in 3rd Robot Learning Workshop »

There have been significant advances in the field of robot learning in the past decade. However, many challenges still remain when considering how robot learning can advance interactive agents such as robots that collaborate with humans. This includes autonomous vehicles that interact with human-driven vehicles or pedestrians, service robots collaborating with their users at homes over short or long periods of time, or assistive robots helping patients with disabilities. This introduces an opportunity for developing new robot learning algorithms that can help advance interactive autonomy.

In this talk, we will discuss a formalism for human-robot interaction built upon ideas from representation learning. Specifically, we will first discuss the notion of latent strategies — low dimensional representations sufficient for capturing non-stationary interactions. We will then talk about the challenges of learning such representations when interacting with humans, and how we can develop data-efficient techniques that enable actively learning computational models of human behavior from demonstrations and preferences.

Author Information

Dorsa Sadigh (Stanford)
Erdem Biyik (Stanford University)

Erdem Biyik is a PhD candidate in Electrical Engineering at Stanford University. He is working on AI for Robotics in Intelligent and Interactive Autonomous Systems Group (ILIAD), and advised by Prof. Dorsa Sadigh. His research interests are: machine learning, artificial intelligence (AI), and their applications for human-robot interaction and multi-agent systems. He also works on AI and optimization for autonomous driving and traffic management. Before coming to Stanford, Erdem was an undergraduate student in the Department of Electrical and Electronics Engineering at Bilkent University, where he worked in Imaging and Computational Neuroscience Laboratory (ICON Lab) in National Magnetic Resonance Research Center under the supervision of Prof. Tolga Çukur with a focus on compressed sensing reconstructions, coil compression, and bSSFP banding suppression in MRI. He also worked on generalized approximate message passing algorithms as an intern in Prof. Rudiger Urbanke's Communication Theory Laboratory (LTHC) in EPFL, under the supervision of Dr. Jean Barbier, for a summer.

More from the Same Authors