Aritra Samanta
Papers
2
Total Citations
12
H-Index
2
About
Aritra Samanta is a leading researcher at the intersection of autonomous robotics and multi-agent systems, with a primary focus on enabling intelligent, adaptive behavior in real-world robotic deployments. His work is fundamentally motivated by the critical need for efficient on-device learning, a challenge he addresses in his highly cited 2023 paper, “R³: On-Device Real-Time Deep Reinforcement Learning for Autonomous Robotics” (7 citations). This research pioneers frameworks that allow autonomous systems—from vehicles to search-and-rescue robots—to continuously adapt their Deep Reinforcement Learning (DRL) models in dynamic environments without relying on cloud connectivity. Samanta also makes significant contributions to understanding social dynamics in multi-robot teams. In his other notable work, “PIMbot: Policy and Incentive Manipulation for Multi-Robot Reinforcement Learning in Social Dilemmas” (5 citations), he explores how robots navigate the tension between individual self-interest and collective benefit, analyzing the impact of environmental factors like miscommunication. By tackling both the computational constraints of edge deployment and the strategic complexities of cooperation, Samanta’s research provides foundational insights for building more robust, autonomous, and socially-aware robotic systems.
Research Focus
Key Achievements
Top Papers
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