activity
20242026
collaborators
Showing cs.NEShow all

5 papers · 1 filter

cs.NE2025

Hypernetworks That Evolve Themselves

Joachim Winther Pedersen, Erwan Plantec, Eleni Nisioti +4

How can neural networks evolve themselves without relying on external optimizers? We propose Self-Referential Graph HyperNetworks, systems where the very machinery of variation and…

cs.NE2024

Meta-Learning an Evolvable Developmental Encoding

Milton L. Montero, Erwan Plantec, Eleni Nisioti +2

Representations for black-box optimisation methods (such as evolutionary algorithms) are traditionally constructed using a delicate manual process. This is in contrast to the repre…

cs.NE2024

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…

cs.NE2024

Structurally Flexible Neural Networks: Evolving the Building Blocks for General Agents

Joachim Winther Pedersen, Erwan Plantec, Eleni Nisioti +2

Artificial neural networks used for reinforcement learning are structurally rigid, meaning that each optimized parameter of the network is tied to its specific placement in the net…

cs.NE2024

Growing Artificial Neural Networks for Control: the Role of Neuronal Diversity

Eleni Nisioti, Erwan Plantec, Milton Montero +2

In biological evolution complex neural structures grow from a handful of cellular ingredients. As genomes in nature are bounded in size, this complexity is achieved by a growth pro…