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Nazim Kemal Ure

2 accepted papers

2023

Self-Improving Safety Performance of Reinforcement Learning Based Driving with Black-Box Verification Algorithms

ICRA 2023poster

In this work, we propose a self-improving artificial intelligence system to enhance the safety performance of reinforcement learning (RL)-based autonomous driving (AD) agents using black-box verification methods. RL algorithms have become popular in AD applications in recent years. However, the perf…

Cited by 5SourcecodeScholar
2019

Sample Efficient Interactive End-to-End Deep Learning for Self-Driving Cars with Selective Multi-Class Safe Dataset Aggregation

IROS 2019poster

The objective of this paper is to develop a sample efficient end-to-end deep learning method for self-driving cars, where we attempt to increase the value of the information extracted from samples, through careful analysis obtained from each call to expert driver's policy. End-to-end imitation learn…

Cited by 17SourceScholar