Daria Ramon
Papers
2
Total Citations
8
H-Index
2
About
Daria Ramon is a researcher at the forefront of computational logic and multi-agent systems, with a particular focus on how groups of autonomous agents can make collective decisions under conditions of perception bias. Her most cited work introduces a groundbreaking application of non-commutative logic to decision-making, where the order of information processing fundamentally alters outcomes. Ramon’s key contribution lies in extending traditional uninorm and absorbing norm aggregators with a novel asymmetry parameter that quantifies the “level of non-commutativity” in group reasoning. This framework allows for more realistic modeling of how individual biases and sequential information influence collective choices. While her citation counts are still building—with her flagship 2023 paper garnering 5 and 3 citations respectively—the work represents a significant theoretical advance in merging non-classical logic with practical multi-agent coordination. Ramon’s research sits at the intersection of artificial intelligence, logic, and social choice theory, offering new tools for designing more robust and context-aware autonomous systems. Her innovative approach to formalizing perception bias is particularly relevant for applications in robotics, distributed AI, and computational social science.
Research Focus
Key Achievements
Top Papers
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- 2