activity
20202026
most citedMultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach

54 citations · 55 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

BraiNCA: brain-inspired neural cellular automata and applications to morphogenesis and motor control

Léo Pio-Lopez, Benedikt Hartl, Michael Levin

Most of the Neural Cellular Automata (NCAs) defined in the literature have a common theme: they are based on regular grids with a Moore neighborhood (one-hop neighbour). They do no…

cs.NE2026

Evolving Symbiosis, from Barricelli's Legacy to Collective Intelligence: a simulated and conceptual approach

James Ashford, Marko Cvjetko, Richard Löffler +6

This report documents the work of our group (named SymBa) at the ALICE 2026 workshop in Copenhagen. Inspired by the pioneering work by Nils Aall Barricelli on symbiogenesis of nume…

cs.AI2026★ 1 cited

Remapping and navigation of an embedding space via error minimization: a fundamental organizational principle of cognition in natural and artificial systems

Benedikt Hartl, Léo Pio-Lopez, Chris Fields +1

The emerging field of diverse intelligence seeks an integrated view of problem-solving in agents of very different provenance, composition, and substrates. From subcellular chemica…

cs.AI2025

Neural cellular automata: applications to biology and beyond classical AI

Benedikt Hartl, Michael Levin, Léo Pio-Lopez

Neural Cellular Automata (NCA) represent a powerful framework for modeling biological self-organization, extending classical rule-based systems with trainable, differentiable (or e…

q-bio.PE2022

The scaling of goals via homeostasis: an evolutionary simulation, experiment and analysis

Leo Pio-Lopez, Johanna Bischof, Jennifer V. LaPalme +1

All cognitive agents are composite beings. Specifically, complex living agents consist of cells, which are themselves competent sub-agents navigating physiological and metabolic sp…

cs.LG2020★ 54 cited

MultiVERSE: a multiplex and multiplex-heterogeneous network embedding approach

Léo Pio-Lopez, Alberto Valdeolivas, Laurent Tichit +2

Network embedding approaches are gaining momentum to analyse a large variety of networks. Indeed, these approaches have demonstrated their efficiency for tasks such as community de…