Deep reinforcement learning–based safe path planning for leader–follower robots
This work proposes a modified Multi-Agent Twin-Delayed Deep Deterministic Policy Gradient (M-MATD3) algorithm, specifically designed to mitigate common issues such as overestimation bias and high variance observed in standard MATD3.