Domain Adaptive Imitation Learning for Self Driving Environments

Authors

Eman Hisham Zaki Al Suradi, Mohamed bin Zayed University of Artificial IntelligenceFollow

Document Type

Dissertation

Abstract

To overcome this challenge, we propose a recursive adaptive prediction but due to time limitations, we will defer its implementation to future work. This approach necessitates the model to predict the next position recursively based on the forecasted location in the previous time step, optimizing the model over the entire trajectory. By doing so, the model will be forced to consider all the input information, leading to improved performance and a better understanding of the driving policy.

Publication Date

6-2023

Comments

Thesis submitted to the Deanship of Graduate and Postdoctoral Studies

In partial fulfillment of the requirements for the M.Sc degree in Machine Learning

Advisors: Dr. Kun Zhang, Dr. Hisham Cholakkal

with 2 year embargo period

Recommended Citation

E.H.Z. Al Suradi, "Domain Adaptive Imitation Learning for Self Driving Environments", M.S. Thesis, Machine Learning, Abu Dhabi, UAE, 2023.