Olivia Breysse
Papers
1
Total Citations
19
H-Index
1
About
Olivia Breysse is a researcher working at the intersection of developmental robotics and artificial intelligence, with a particular focus on how autonomous agents develop perceptual and cognitive capabilities from the ground up. Her most notable work, the 2012 paper "A non-linear approach to space dimension perception by a naive agent," challenges longstanding assumptions in AI design by questioning the notion that perception is an inherent, pre-programmed capacity of intelligent systems. Rather than relying on designer-imposed models, Breysse advances a framework in which perception emerges organically through the agent's own developmental experience — a paradigm shift that aligns with broader movements toward more biologically inspired and self-organizing AI architectures. This contribution, which has garnered 19 citations, is particularly significant for researchers exploring embodied cognition and autonomous learning systems, as it opens new pathways for building agents that develop spatial awareness without explicit human-engineered perceptual scaffolding. Breysse's work invites both AI practitioners and cognitive scientists to reconsider foundational assumptions about machine perception, making her research a valuable touchstone for anyone studying developmental approaches to artificial intelligence.
Research Focus
Key Achievements
Top Papers
- 1A non-linear approach to space dimension perception by a naive agent19 citations · 2012