Exploration Techniques in Reinforcement Learning for Autonomous Vehicles
Autonomous vehicles (AVs) have the potential to revolutionize the transportation system by enhancing road safety, reducing traffic congestion, and freeing drivers from monotonous tasks. Effective exploration is essential for AVs to navigate safely and adapt to dynamic environments. Reinforcement lea...
Saved in:
| Main Authors: | Ammar Khaleel, Áron Ballagi |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-11-01
|
| Series: | Engineering Proceedings |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2673-4591/79/1/24 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Model-based exploration is measurable across tasks but not linked to personality and psychiatric assessments
by: Kristin Witte, et al.
Published: (2025-07-01) -
An Efficient Autonomous Exploration Framework for Autonomous Vehicles in Uneven Off-Road Environments
by: Le Wang, et al.
Published: (2025-07-01) -
Adaptive Noise Exploration for Neural Contextual Multi-Armed Bandits
by: Chi Wang, et al.
Published: (2025-01-01) -
Adaptive sequential sampling for reliability estimation of binary functions
by: Miroslav Vořechovský
Published: (2022-08-01) -
Boredom and curiosity: the hunger and the appetite for information
by: Johannes P.-H. Seiler, et al.
Published: (2024-12-01)