Ali Asghar Heidari

University of Tehran, National University of Singapore

Papers

Total Citations

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About

Ali Asghar Heidari is a leading researcher in intelligent robotics and computational intelligence, whose work bridges the gap between reinforcement learning and bio-inspired optimization. His primary research areas include deep reinforcement learning for robotic control, neuroevolution, and autonomous navigation systems. Heidari’s major contribution lies in enhancing the robustness and adaptability of robotic systems through novel algorithmic frameworks. Notably, his 2023 paper on an enhanced deep deterministic policy gradient (DDPG) algorithm for robotic arm control—cited 24 times—introduces a hybrid reward function that significantly improves the stability and performance of intelligent control in dynamic environments. Earlier, his 2019 work on moth-flame-based neuroevolution for autonomous robot navigation (19 citations) pioneered the integration of swarm intelligence with evolutionary neural networks, enabling more efficient path planning without human intervention. With a growing citation impact, Heidari’s research is shaping the future of adaptive robotics, offering practical solutions for real-world automation challenges. His innovative approaches continue to inspire students and researchers exploring the frontiers of autonomous systems and intelligent control.