25 citations · 67 across the 13 of their papers we have counts for
14 papers
The Affordance is the Message: Creative Media as Complex Systems
Ane Espeseth, Elias Najarro
The affordances of a creative medium strongly condition the creative artefacts the medium will produce. In this work, we present a formalisation of computational creativity (CC) me…
Conversable Complexity: Agentic LLM Collectives as Interpretable Substrates
Elias Najarro, Ane Espeseth, Eleni Nisioti +2
Complexity and interpretability rarely coincide: systems rich enough for complex behaviours to emerge are usually too opaque to question, while transparent ones are too simple for…
Learning Developmental Scaffoldings to Guide Self-Organisation
Milton L. Montero, Elias Najarro, Jakob Schauser +1
From subcellular structures to entire organisms, many natural systems generate complex organisation through self-organisation: local interactions that collectively give rise to glo…
Solving Stochastic Inverse Problems in Embedding Space
Elias Najarro, Nicolas Bessone, Sebastian Risi
Solving an inverse problem consists in finding the unknown parameters of a system from observations. This task is particularly challenging when observations have a strong stochasti…
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…
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…
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
Shyam Sudhakaran, Miguel González-Duque, Claire Glanois +3
Procedural Content Generation (PCG) is a technique to generate complex and diverse environments in an automated way. However, while generating content with PCG methods is often str…
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…
A Unified Substrate for Body-Brain Co-evolution
Sidney Pontes-Filho, Kathryn Walker, Elias Najarro +2
The discovery of complex multicellular organism development took millions of years of evolution. The genome of such a multicellular organism guides the development of its body from…
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Shyam Sudhakaran, Djordje Grbic, Siyan Li +4
Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Re…
EvoCraft: A New Challenge for Open-Endedness
Djordje Grbic, Rasmus Berg Palm, Elias Najarro +2
This paper introduces EvoCraft, a framework for Minecraft designed to study open-ended algorithms. We introduce an API that provides an open-source Python interface for communicati…
Testing the Genomic Bottleneck Hypothesis in Hebbian Meta-Learning
Rasmus Berg Palm, Elias Najarro, Sebastian Risi
Hebbian meta-learning has recently shown promise to solve hard reinforcement learning problems, allowing agents to adapt to some degree to changes in the environment. However, beca…
Meta-Learning through Hebbian Plasticity in Random Networks
Elias Najarro, Sebastian Risi
Lifelong learning and adaptability are two defining aspects of biological agents. Modern reinforcement learning (RL) approaches have shown significant progress in solving complex t…