Liangbing Feng
Papers
8
Total Citations
39
H-Index
4
About
Liangbing Feng is a researcher in intelligent robotics and autonomous systems, focusing on the intersection of machine learning, cognitive modeling, and swarm intelligence. His work centers on developing adaptive control systems that enable robots to learn from human interaction and their environment. Feng's major contributions include the creation of a voice command learning system using Parameter-less Growing Self-Organizing Maps (PL-G-SOM) for partner robots, and a hybrid intelligent control model combining high-level time Petri nets with Reinforcement Learning to optimize system states. He has also explored emotion and curiosity-driven behaviors in swarm robots, as well as neuro-fuzzy reinforcement learning systems for adaptive swarm behavior acquisition. His most cited paper (9 citations) introduces a human-machine interaction system that enhances robot communication abilities, while his work on autonomic swarm behaviors (6 citations) advances the field of collective robotics. Feng's research demonstrates a commitment to building more intelligent, autonomous agents capable of complex learning and decision-making, with potential applications in human-robot collaboration and multi-robot systems.
Research Focus
Key Achievements
Top Papers
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- 4Autonomic Behaviors of Swarm Robots Driven by Emotion and Curiosity6 citations · 2010
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