Deep Reinforcement Learning Based Uplink Security Enhancement for STAR-RIS-Assisted NOMA Systems With Dual Eavesdroppers
This paper investigates the simultaneous transmitting and reflecting reconfigurable
intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) systems …
intelligent surface (STAR-RIS) assisted non-orthogonal multiple access (NOMA) systems …
Efficient and Balanced Exploration-driven Decision Making for Autonomous Racing Using Local Information
Autonomous racing has attracted extensive interest due to its great potential in self-driving at
the extreme limits. Model-based and learning-based methods are widely used in …
the extreme limits. Model-based and learning-based methods are widely used in …
Balanced reward-inspired reinforcement learning for autonomous vehicle racing
Autonomous vehicle racing has attracted extensive interest due to its great potential in
autonomous driving at the extreme limits. Model-based and learning-based methods are …
autonomous driving at the extreme limits. Model-based and learning-based methods are …
Towards robust decision-making for autonomous highway driving based on safe reinforcement learning
R Zhao, Z Chen, Y Fan, Y Li, F Gao - Sensors, 2024 - mdpi.com
Reinforcement Learning (RL) methods are regarded as effective for designing autonomous
driving policies. However, even when RL policies are trained to convergence, ensuring their …
driving policies. However, even when RL policies are trained to convergence, ensuring their …
Enhance Deep Reinforcement Learning with Denoising Autoencoder for Self-Driving Mobile Robot
GNP Pratama, I Hidayatulloh, HD Surjono… - Journal of Robotics …, 2024 - journal.umy.ac.id
Over the past years, self-driving mobile robots have captured the interest of researchers,
prompting exploration into their multifaceted implementation. They have the potential to …
prompting exploration into their multifaceted implementation. They have the potential to …
A Comparative Analysis of Deep Reinforcement Learning-Enabled Freeway Decision-Making for Automated Vehicles
In application, advanced autonomous driving technologies still face numerous challenges.
Deep Reinforcement Learning (DRL) has emerged as a widespread and effective approach …
Deep Reinforcement Learning (DRL) has emerged as a widespread and effective approach …