95 citations · 378 across the 58 of their papers we have counts for
7 papers · 1 filter
Incentivizing Routing Choices for Safe and Efficient Transportation in the Face of the COVID-19 Pandemic
Mark Beliaev, Erdem Bıyık, Daniel A. Lazar +3
The COVID-19 pandemic has severely affected many aspects of people's daily lives. While many countries are in a re-opening stage, some effects of the pandemic on people's behaviors…
ROIAL: Region of Interest Active Learning for Characterizing Exoskeleton Gait Preference Landscapes
Kejun Li, Maegan Tucker, Erdem Bıyık +6
Characterizing what types of exoskeleton gaits are comfortable for users, and understanding the science of walking more generally, require recovering a user's utility landscape. Le…
Multi-Agent Safe Planning with Gaussian Processes
Zheqing Zhu, Erdem Bıyık, Dorsa Sadigh
Multi-agent safe systems have become an increasingly important area of study as we can now easily have multiple AI-powered systems operating together. In such settings, we need to…
Reinforcement Learning based Control of Imitative Policies for Near-Accident Driving
Zhangjie Cao, Erdem Bıyık, Woodrow Z. Wang +4
Autonomous driving has achieved significant progress in recent years, but autonomous cars are still unable to tackle high-risk situations where a potential accident is likely. In s…
Active Preference-Based Gaussian Process Regression for Reward Learning
Erdem Bıyık, Nicolas Huynh, Mykel J. Kochenderfer +1
Designing reward functions is a challenging problem in AI and robotics. Humans usually have a difficult time directly specifying all the desirable behaviors that a robot needs to o…
Learning Reward Functions from Diverse Sources of Human Feedback: Optimally Integrating Demonstrations and Preferences
Erdem Bıyık, Dylan P. Losey, Malayandi Palan +3
Reward functions are a common way to specify the objective of a robot. As designing reward functions can be extremely challenging, a more promising approach is to directly learn re…
When Humans Aren't Optimal: Robots that Collaborate with Risk-Aware Humans
Minae Kwon, Erdem Biyik, Aditi Talati +3
In order to collaborate safely and efficiently, robots need to anticipate how their human partners will behave. Some of today's robots model humans as if they were also robots, and…