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A Comprehensive Review of Propagation Models in Complex Networks: From Deterministic to Deep Learning Approaches

Autor: Wu, Bin, Luo, Sifu, Suh, C. Steve

Understanding propagation mechanisms in complex networks is essential for fields like epidemiology and multi-robot networks. This paper reviews various propagation models, from traditional deterministic frameworks to advanced data-driven and deep lea

Externí odkaz: http://arxiv.org/abs/2410.02118

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Deep Reinforcement Learning for Decentralized Multi-Robot Control: A DQN Approach to Robustness and Information Integration

Autor: Wu, Bin, Suh, C Steve

The superiority of Multi-Robot Systems (MRS) in various complex environments is unquestionable. However, in complex situations such as search and rescue, environmental monitoring, and automated production, robots are often required to work collaborat

Externí odkaz: http://arxiv.org/abs/2408.11339

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State-of-the-art in Robot Learning for Multi-Robot Collaboration: A Comprehensive Survey

Autor: Wu, Bin, Suh, C Steve

With the continuous breakthroughs in core technology, the dawn of large-scale integration of robotic systems into daily human life is on the horizon. Multi-robot systems (MRS) built on this foundation are undergoing drastic evolution. The fusion of a

Externí odkaz: http://arxiv.org/abs/2408.11822

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