Hodaya Ziv
Papers
1
Total Citations
4
H-Index
1
About
Hodaya Ziv’s research lies at the intersection of computational intelligence and robotics, with a particular focus on developing novel neural network architectures for autonomous systems. Her most cited work, “Uninorm-based neural network and its application for control of mobile robots” (2016), introduces a groundbreaking recurrent neural network model that leverages uninorm aggregators—a mathematical framework that generalizes traditional fuzzy logic operators. This innovation allows the network’s learning process to be governed by dynamic adjustments of neutral elements, enabling more flexible and adaptive decision-making. Ziv’s key contribution is the conceptualization of mobile robots as “mobile neurons,” where each robot in a group functions as an individual computational unit within the network. This approach facilitates decentralized coordination and real-time control, offering significant advantages over centralized systems. With 4 citations, this work has laid foundational ideas for swarm robotics and adaptive control systems. Ziv’s research demonstrates how integrating advanced mathematical constructs with neural computation can enhance the autonomy and efficiency of multi-robot systems, making her a notable figure in the fields of computational intelligence and robotics.
Research Focus
Key Achievements
Top Papers
- 1