11 citations · 52 across the 22 of their papers we have counts for
24 papers
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…
Information encoding and decoding in in-vitro neural networks on micro electrode arrays through stimulation timing
Trym A. E. Lindell, Ola H. Ramstad, Ionna Sandvig +2
A primary challenge in utilizing in-vitro biological neural networks for computations is finding good encoding and decoding schemes for inputting and decoding data to and from the…
Optimization of a Hydrodynamic Computational Reservoir through Evolution
Alessandro Pierro, Kristine Heiney, Shamit Shrivastava +2
As demand for computational resources reaches unprecedented levels, research is expanding into the use of complex material substrates for computing. In this study, we interface wit…
Local learning through propagation delays in spiking neural networks
Jørgen Jensen Farner, Ola Huse Ramstad, Stefano Nichele +1
We propose a novel local learning rule for spiking neural networks in which spike propagation times undergo activity-dependent plasticity. Our plasticity rule aligns pre-synaptic s…
Assessing the robustness of critical behavior in stochastic cellular automata
Sidney Pontes-Filho, Pedro Lind, Stefano Nichele
There is evidence that biological systems, such as the brain, work at a critical regime robust to noise, and are therefore able to remain in it under perturbations. In this work, w…
Towards the Neuroevolution of Low-level Artificial General Intelligence
Sidney Pontes-Filho, Kristoffer Olsen, Anis Yazidi +3
In this work, we argue that the search for Artificial General Intelligence (AGI) should start from a much lower level than human-level intelligence. The circumstances of intelligen…
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…
Collective control of modular soft robots via embodied Spiking Neural Cellular Automata
Giorgia Nadizar, Eric Medvet, Stefano Nichele +1
Voxel-based Soft Robots (VSRs) are a form of modular soft robots, composed of several deformable cubes, i.e., voxels. Each VSR is thus an ensemble of simple agents, namely the voxe…
AI-based artistic representation of emotions from EEG signals: a discussion on fairness, inclusion, and aesthetics
Piera Riccio, Kristin Bergaust, Boel Christensen-Scheel +3
While Artificial Intelligence (AI) technologies are being progressively developed, artists and researchers are investigating their role in artistic practices. In this work, we pres…
Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity
Jørgen Jensen Farner, Håkon Weydahl, Ruben Jahren +3
Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulate…
Towards self-organized control: Using neural cellular automata to robustly control a cart-pole agent
Alexandre Variengien, Stefano Nichele, Tom Glover +1
Neural cellular automata (Neural CA) are a recent framework used to model biological phenomena emerging from multicellular organisms. In these systems, artificial neural networks a…
On Artificial Life and Emergent Computation in Physical Substrates
Kristine Heiney, Gunnar Tufte, Stefano Nichele
In living systems, we often see the emergence of the ingredients necessary for computation -- the capacity for information transmission, storage, and modification -- begging the qu…
A deep learning based tool for automatic brain extraction from functional magnetic resonance images in rodents
Sidney Pontes-Filho, Annelene Gulden Dahl, Stefano Nichele +1
Removing skull artifacts from functional magnetic images (fMRI) is a well understood and frequently encountered problem. Because the fMRI field has grown mostly due to human studie…
Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches
Kristine Heiney, Ola Huse Ramstad, Ioanna Sandvig +2
In this work, we report the preliminary analysis of the electrophysiological behavior of in vitro neuronal networks to identify when the networks are in a critical state based on t…
Evaluation of the criticality of in vitro neuronal networks: Toward an assessment of computational capacity
Kristine Heiney, Vibeke Devold Valderhaug, Ioanna Sandvig +4
Novel computing hardwares are necessary to keep up with today's increasing demand for data storage and processing power. In this research project, we turn to the brain for inspirat…
A general representation of dynamical systems for reservoir computing
Sidney Pontes-Filho, Anis Yazidi, Jianhua Zhang +5
Dynamical systems are capable of performing computation in a reservoir computing paradigm. This paper presents a general representation of these systems as an artificial neural net…
DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks
Gustavo Borges Moreno e Mello, Vibeke Devold Valderhaug, Sidney Pontes-Filho +3
In the brain, the structure of a network of neurons defines how these neurons implement the computations that underlie the mind and the behavior of animals and humans. Provided tha…
Ethics of Artificial Intelligence Demarcations
Anders Braarud Hanssen, Stefano Nichele
In this paper we present a set of key demarcations, particularly important when discussing ethical and societal issues of current AI research and applications. Properly distinguish…
Evolved Art with Transparent, Overlapping, and Geometric Shapes
Joachim Berg, Nils Gustav Andreas Berggren, Sivert Allergodt Borgeteien +3
In this work, an evolutionary art project is presented where images are approximated by transparent, overlapping and geometric shapes of different types, e.g., polygons, circles, l…
A Conceptual Bio-Inspired Framework for the Evolution of Artificial General Intelligence
Sidney Pontes-Filho, Stefano Nichele
In this work, a conceptual bio-inspired parallel and distributed learning framework for the emergence of general intelligence is proposed, where agents evolve through environmental…
Autonomous Configuration of Network Parameters in Operating Systems using Evolutionary Algorithms
Bartosz Gembala, Anis Yazidi, Hårek Haugerud +1
By default, the Linux network stack is not configured for highspeed large file transfer. The reason behind this is to save memory resources. It is possible to tune the Linux networ…
Achieving Connectivity Between Wide Areas Through Self-Organising Robot Swarm Using Embodied Evolution
Erik Aaron Hansen, Stefano Nichele, Anis Yazidi +3
Abruptions to the communication infrastructure happens occasionally, where manual dedicated personnel will go out to fix the interruptions, restoring communication abilities. Howev…
Deep Reservoir Computing Using Cellular Automata
Stefano Nichele, Andreas Molund
Recurrent Neural Networks (RNNs) have been a prominent concept within artificial intelligence. They are inspired by Biological Neural Networks (BNNs) and provide an intuitive and a…
Reservoir Computing Using Non-Uniform Binary Cellular Automata
Stefano Nichele, Magnus S. Gundersen
The Reservoir Computing (RC) paradigm utilizes a dynamical system, i.e., a reservoir, and a linear classifier, i.e., a read-out layer, to process data from sequential classificatio…