25 citations · 55 across the 15 of their papers we have counts for
8 papers · 1 filter
Smart Cellular Bricks for Decentralized Shape Classification and Damage Recovery
Rodrigo Moreno, Andres Faina, Shyam Sudhakaran +2
Biological systems possess remarkable capabilities for self-recognition and morphological regeneration, often relying solely on local interactions. Inspired by these decentralized…
From Text to Life: On the Reciprocal Relationship between Artificial Life and Large Language Models
Eleni Nisioti, Claire Glanois, Elias Najarro +7
Large Language Models (LLMs) have taken the field of AI by storm, but their adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work we…
Generative Design through Quality-Diversity Data Synthesis and Language Models
Adam Gaier, James Stoddart, Lorenzo Villaggi +1
Two fundamental challenges face generative models in engineering applications: the acquisition of high-performing, diverse datasets, and the adherence to precise constraints in gen…
Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
Elias Najarro, Shyam Sudhakaran, Sebastian Risi
Biological nervous systems are created in a fundamentally different way than current artificial neural networks. Despite its impressive results in a variety of different domains, d…
Severe Damage Recovery in Evolving Soft Robots through Differentiable Programming
Kazuya Horibe, Kathryn Walker, Rasmus Berg Palm +2
Biological systems are very robust to morphological damage, but artificial systems (robots) are currently not. In this paper we present a system based on neural cellular automata,…
Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems
Shyam Sudhakaran, Elias Najarro, Sebastian Risi
Inspired by cellular growth and self-organization, Neural Cellular Automata (NCAs) have been capable of "growing" artificial cells into images, 3D structures, and even functional m…
HyperNCA: Growing Developmental Networks with Neural Cellular Automata
Elias Najarro, Shyam Sudhakaran, Claire Glanois +1
In contrast to deep reinforcement learning agents, biological neural networks are grown through a self-organized developmental process. Here we propose a new hypernetwork approach…
Variational Neural Cellular Automata
Rasmus Berg Palm, Miguel González-Duque, Shyam Sudhakaran +1
In nature, the process of cellular growth and differentiation has lead to an amazing diversity of organisms -- algae, starfish, giant sequoia, tardigrades, and orcas are all create…