Evaluating Domain Randomization Techniques in DRL Agents: A Comparative Study of Normal, Randomized, and Non-Randomized Resets
Year: 2025
Type: article
Abstract: Domain randomization is a widely adopted technique in deep reinforcement learning (DRL) to improve agent generalization by exposing policies to diverse environmental conditions. This paper investigates the impact of different... | Find, read and cite all the research you need on Tech Science Press
Author: Abubakar Elsafi
Institution: University of Jeddah
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
Funder: Ministry of Education, India
OpenAlex ID: W4412844226