Towards self-organized control: Using neural cellular automata to robustly control a cart-pole agent A Variengien, S Nichele, T Glover, S Pontes-Filho arXiv preprint arXiv:2106.15240, 2021 | 37 | 2021 |
A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality S Pontes-Filho, P Lind, A Yazidi, J Zhang, H Hammer, GBM Mello, ... Cognitive Neurodynamics 14 (5), 657-674, 2020 | 22 | 2020 |
Bidirectional learning for robust neural networks S Pontes-Filho, M Liwicki 2019 International Joint Conference on Neural Networks (IJCNN), 1-8, 2019 | 15 | 2019 |
Collective control of modular soft robots via embodied Spiking Neural Cellular Automata G Nadizar, E Medvet, S Nichele, S Pontes-Filho arXiv preprint arXiv:2204.02099, 2022 | 13 | 2022 |
A unified substrate for body-brain co-evolution S Pontes-Filho, K Walker, E Najarro, S Nichele, S Risi arXiv preprint arXiv:2203.12066, 2022 | 13* | 2022 |
A conceptual bio-inspired framework for the evolution of artificial general intelligence S Pontes-Filho, S Nichele arXiv preprint arXiv:1903.10410, 2019 | 11 | 2019 |
An experimental comparison of evolved neural network models for controlling simulated modular soft robots G Nadizar, E Medvet, S Nichele, S Pontes-Filho Applied Soft Computing 145, 110610, 2023 | 6 | 2023 |
A deep learning-based tool for automatic brain extraction from functional magnetic resonance images of rodents S Pontes-Filho, AG Dahl, S Nichele, GBM Mello Intelligent Systems and Applications: Proceedings of the 2021 Intelligent …, 2022 | 6 | 2022 |
Towards self-organized control: using neural cellular automata to robustly control a cart-pole agent. Innov Mach Intell (IMI) 1: 1–14 A Variengien, S Pontes-Filho, T Glover, S Nichele | 6 | 2021 |
Towards the Neuroevolution of Low-level artificial general intelligence S Pontes-Filho, K Olsen, A Yazidi, MA Riegler, P Halvorsen, S Nichele Frontiers in Robotics and AI 9, 1007547, 2022 | 5 | 2022 |
EvoDynamic: a framework for the evolution of generally represented dynamical systems and its application to criticality S Pontes-Filho, P Lind, A Yazidi, J Zhang, H Hammer, GBM Mello, ... Applications of Evolutionary Computation: 23rd European Conference …, 2020 | 5* | 2020 |
Assessing the robustness of critical behavior in stochastic cellular automata S Pontes-Filho, PG Lind, S Nichele Physica D: Nonlinear Phenomena 441, 133507, 2022 | 4 | 2022 |
A general representation of dynamical systems for reservoir computing S Pontes-Filho, A Yazidi, J Zhang, H Hammer, G Mello, I Sandvig, G Tufte, ... arXiv preprint arXiv:1907.01856, 2019 | 2 | 2019 |
Bridging the computational gap: From biological to artificial substrates K Heiney, OH Ramstad, S Pontes-Filho, T Glover, T Lindell, JJ Farner, ... Second International Workshop on Theoretical and Experimental Material …, 2021 | 1 | 2021 |
Method to obtain neuromorphic reservoir networks from images of in vitro cortical networks GBM e Mello, S Pontes-Filho, I Sandvig, VD Valderhaug, E Zouganeli, ... 2019 IEEE Symposium Series on Computational Intelligence (SSCI), 2360-2366, 2019 | 1 | 2019 |
Towards spiking neural systems synthesis AC Kammara, S Pontes-Filho, A König Control, Robotics and Sensors, Institution of Engineering & Technology https …, 2018 | 1 | 2018 |
Optimization of dynamical systems towards criticality and intelligent behavior S Pontes-Filho NTNU, 2023 | | 2023 |
DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks VD Valderhaug, S Pontes-Filho, E Zouganeli, I Sandvig, S Nichele arXiv preprint arXiv:1907.01062, 2019 | | 2019 |
DeepTEGINN: Deep Learning Based Tools to Extract Graphs from Images of Neural Networks GBM e Mello, S Pontes-Filho, I Sandvig, VD Valderhaug, E Zouganeli, ... CoRR, 2019 | | 2019 |
The distributed neocortex: How neuroscience can inspire distributed AI systems MK Kvalsund, KO Ellefsen, K Glette, S Pontes-Filho, ME Lepperød | | |