Implementing Deep Reinforcement Learning (DRL)-based Driving Styles for Non-Player Vehicles
We propose a new, hierarchical architecture for behavioral planning of vehicle models usable as realistic non-player vehicles in serious games related to traffic and driving. These agents, trained with deep reinforcement learning (DRL), decide their motion by taking high-level decisions, such as &qu...
Saved in:
Main Authors: | Luca Forneris (Author), Alessandro Pighetti (Author), Luca Lazzaroni (Author), Francesco Bellotti (Author), Alessio Capello (Author), Marianna Cossu (Author), Riccardo Berta (Author) |
---|---|
Format: | Book |
Published: |
Serious Games Society,
2023-11-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
PrescDRL: deep reinforcement learning for herbal prescription planning in treatment of chronic diseases
by: Kuo Yang, et al.
Published: (2024) -
Serious Games for education and training
by: Alessandro De Gloria, et al.
Published: (2014) -
Self-Driving Vehicles and Enabling Technologies
Published: (2021) -
They do not just drive when they are driving: Distracted driving practices among professional vehicle drivers in South India
by: Rizwan Suliankatchi Abdulkader, et al.
Published: (2019) -
Abandoned vehicle - What next for the drive of your life?
by: Sidharth S Mishra, et al.
Published: (2023)