Extending DDPG with Physics-Informed Constraints for Energy-Efficient Robotic Control
Energy efficiency stands as an essential factor when implementing deep reinforcement learning (DRL) policies for robotic control systems. Standard algorithms, including Deep Deterministic Policy Gradient (DDPG), primarily opt... | Find, read and cite all the research you need on Tech Science Press
Authors
- Ashraf Osman Ibrahim (ORCID: https://orcid.org/0000-0001-5526-3623)
- Abubakar Elsafi
- Lubna A. Gabralla (ORCID: https://orcid.org/0000-0002-6910-6861)
- Ali Ahmed
- Arafat Abdulgader Mohammed Elhag
Publication Details
- Journal
- Computer Modeling in Engineering & Sciences
- Published
- 2025-01-01
- DOI
- https://doi.org/10.32604/cmes.2025.072726
- Primary Topic
- Reinforcement Learning in Robotics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Princess Nourah Bint Abdulrahman University