Robustness During Learning, Interaction and Adaptation for Autonomous Driving
Doktorsavhandling, 2023
Reinforcement Learning
Epistemic Uncertainty
Uncertainty Quantification
Machine Learning
Autonomous Driving
Författare
Hannes Eriksson
Chalmers, Data- och informationsteknik, Data Science och AI
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Many of us have at some point learned how to drive a car. We can all reflect upon what in that process made it challenging for us. What we all remember is that it was a process of trial and error. Perhaps we first started out driving in a parking lot and over time we were able to experience more and more difficult scenarios. At all points in time, our driving instructor was there to make sure we could learn safely. If we were put into a situation we could not handle, then the job of the instructor was to intervene. As we become more and more proficient in driving the instructor could increase their trust in us. We wish to conduct this same feedback loop but for autonomous agents. Instead of a person learning how to drive we have an agent in the same situation. Here, we take the position of the instructor or designer of the agent. How can we replicate this safe learning process for this agent? After all, the agent has no grasp on what it does not know. By designing a more cautious agent we can limit its risk-taking behavior when it has the least amount of experience. Only when we know the agent will not take excessive risks during its learning process will we be able to deploy it in the real world. The agent needs to be wary of other road users and objects in the environment and not cause accidents.
In our work, we provide novel frameworks for the design of robust learning agents.
Styrkeområden
Informations- och kommunikationsteknik
Ämneskategorier
Data- och informationsvetenskap
Datorseende och robotik (autonoma system)
Infrastruktur
C3SE (Chalmers Centre for Computational Science and Engineering)
ISBN
978-91-7905-904-0
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5370
Utgivare
Chalmers
HC3, Hörsalsvägen 16 (Online password 354213)
Opponent: Aviv Tamar, Technion – Israel Institute of Technology, Israel