activity
20192022
most citedDesign Space of Behaviour Planning for Autonomous Driving

9 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2022★ 1 cited

Learning to Write with Coherence From Negative Examples

Seonil Son, Jaeseo Lim, Youwon Jang +2

Coherence is one of the critical factors that determine the quality of writing. We propose writing relevance (WR) training method for neural encoder-decoder natural language genera…

cs.LG2022★ 2 cited

Recursive Constraints to Prevent Instability in Constrained Reinforcement Learning

Jaeyoung Lee, Sean Sedwards, Krzysztof Czarnecki

We consider the challenge of finding a deterministic policy for a Markov decision process that uniformly (in all states) maximizes one reward subject to a probabilistic constraint…

cs.LG2020

Predictive PER: Balancing Priority and Diversity towards Stable Deep Reinforcement Learning

Sanghwa Lee, Jaeyoung Lee, Ichiro Hasuo

Prioritized experience replay (PER) samples important transitions, rather than uniformly, to improve the performance of a deep reinforcement learning agent. We claim that such prio…

cs.RO2019★ 9 cited

Design Space of Behaviour Planning for Autonomous Driving

Marko Ilievski, Sean Sedwards, Ashish Gaurav +6

We explore the complex design space of behaviour planning for autonomous driving. Design choices that successfully address one aspect of behaviour planning can critically constrain…

cs.LG2019★ 8 cited

WiseMove: A Framework for Safe Deep Reinforcement Learning for Autonomous Driving

Jaeyoung Lee, Aravind Balakrishnan, Ashish Gaurav +2

Machine learning can provide efficient solutions to the complex problems encountered in autonomous driving, but ensuring their safety remains a challenge. A number of authors have…