Pierre Delarboulas

Université Paris-Saclay, Centre National de la Recherche Scientifique

Papers

Total Citations

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About

Pierre Delarboulas is a researcher at the intersection of evolutionary robotics and bio-inspired navigation systems. His work is distinguished by a pioneering application of information theory to open-ended evolution in robotics, a contribution that has shaped how autonomous agents can develop complex behaviors without predefined goals. His most cited paper, "Open-Ended Evolutionary Robotics: An Information Theoretic Approach" (2010, 11 citations), introduces a framework that uses mutual information as a driver for novelty and adaptation, offering a powerful alternative to traditional fitness-based evolution. Delarboulas also made notable strides in neural-based spatial cognition with "Robustness Study of a Multimodal Compass Inspired from HD-Cells and Dynamic Neural Fields" (2014, 8 citations), where he demonstrated how dynamic neural fields can mimic biological head-direction cells to create resilient, multimodal orientation systems for robots. This work bridges computational neuroscience and practical robotics, providing insights into robust sensor fusion. Though his citation counts reflect a focused, emerging impact, Delarboulas’s contributions are foundational for researchers exploring self-organization, neural field theory, and the principles of lifelong learning in artificial agents.