Now showing items 21-40 of 40

    • Evolving spiking neuron cellular automata and networks to emulate in vitro neuronal activity 

      Jensen Farner, Jørgen; Weydahl, Håkon; Jahren, Ruben; Huse Ramstad, Ola; Nichele, Stefano; Heiney, Kristine Anne (IEEE Symposium Series on Computational Intelligence (SSCI);2021 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2021-01-24)
      Neuro-inspired models and systems have great potential for applications in unconventional computing. Often, the mechanisms of biological neurons are modeled or mimicked in simulated or physical systems in an attempt to ...
    • An experimental comparison of evolved neural network models for controlling simulated modular soft robots 

      Nadizar, Giorgia; Medvet, Eric; Nichele, Stefano; Pontes Filho, Sidney (Peer reviewed; Journal article, 2023)
      Voxel-based soft robots (VSRs) are a type of modular robots composed by interconnected soft and deformable blocks, i.e., voxels. Thanks to the softness of their bodies, VSRs may exhibit rich dynamic behaviors. One open ...
    • FeLT- The Futures of Living Technologies 

      Bergaust, Kristin; Nichele, Stefano (Electronic Workshops in Computing (eWiC);Proceedings of POM Beirut 2019, Conference object, 2019-06)
      FeLT- The Futures of Living Technologies is a research project, but also an initiative to build an environment for interdisciplinary research and education of national and international significance with a strong innovative ...
    • Gathering of the Hive: Investigating the clustering behaviour of honeybees through art and swarm robotics 

      Roen, Haakon Haraldsen; Varankian, Vako; Nichele, Stefano; Bergaust, Kristin (ALife 2019: Proceedings of the artificial life conference 2019;No 31, July, Conference object, 2019)
      In the Gathering of the Hive project, the societal and ecological implications, as well as technological possibilities of swarm robotics are explored through artistic methodology applied to Artificial Life. These matters ...
    • Hallmarks of Criticality in Neuronal Networks Depend on Cell Type and the Temporal Resolution of Neuronal Avalanches 

      Heiney, Kristine; Valderhaug, Vibeke Devold; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (International Journal of Unconventional Computing;Volume 16, Number 4 (2021), Peer reviewed; Journal article, 2021)
      The human brain has a remarkable capacity for computation, and it has been theorized that this capacity arises from the brain self-organizing into the critical state, a dynamical state poised between ordered and dis- ordered ...
    • Instantaneous Mental Workload Recognition Using Wavelet-Packet Decomposition and Semi-Supervised Learning 

      Zhang, Jianhua; Li, Jianrong; Nichele, Stefano (IEEE Symposium Series on Computational Intelligence (SSCI);2019 IEEE Symposium Series on Computational Intelligence (SSCI), Conference object, 2020-02-20)
      The real-time monitoring of human operator's mental workload (MWL) is crucial for development of adaptive/intelligent human-machine cooperative systems in various safety/mission-critical application fields. Although ...
    • Interactive evolution of artificial life art 

      Dumo, Glare Eugenio (ACIT;2022, Master thesis, 2022)
      In this thesis, we designed and presented an interface which is used for creating art using tools from artificial intelligence and artificial life. The interface is used for conducting two different experiments, one for ...
    • Introducing IoT Competencies to First-Year University Students With The Tiles Toolkit 

      Mora, Simone; Gianni, Francesco Valerio; Nichele, Stefano; Divitini, Monica (Proceedings of the 7th Computer Science Education Research Conference;, Chapter; Peer reviewed, 2018)
      Advances in the field of Internet of Things (IoT) are introducing innovations in multiple domains including smart cities, healthcare and transportation. An increasing number of jobs today require IoT competences that ...
    • Investigate AI-based learning for cloud services for adaptive autonomous behavior 

      Azab, Eman Moustafa (ACIT;2021, Master thesis, 2021)
      Cloud computing provides more reliable web services due to its flexibility for accessing resources on-demand and self-managed services. However, cloud computing faces new challenges when managing a massive amount of ...
    • Investigating Rules and Parameters of Reservoir Computing with Elementary Cellular Automata, with a Criticism of Rule 90 and the Five-Bit Memory Benchmark 

      Glover, Tom Eivind; Lind, Pedro; Yazidi, Anis; Osipov, Evgeny; Nichele, Stefano (Peer reviewed; Journal article, 2023)
      Reservoir computing with cellular automata (ReCAs) is a promising concept by virtue of its potential for effective hardware implementation. In this paper, we explore elementary cellular automata rules in the context of ...
    • Method to Obtain Neuromorphic Reservoir Networks from Images of in Vitro Cortical Networks 

      Mello, Gustavo; Pontes-Filho, Sidney; Sandvig, Ioanna; Valderhaug, Vibeke Devold; Zouganeli, Evi; Huse Ramstad, Ola; Sandvig, Axel; Nichele, Stefano (IEEE Symposium Series on Computational Intelligence (SSCI);, Chapter; Peer reviewed, 2020-02-20)
      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 that we can describe the network of neurons ...
    • Minimum Equivalence in Random Boolean Networks, Elementary Cellular Automata, and Beyond 

      Glover, Tom Eivind; Jahren, Christian Ruben; Huse Ramstad, Ola; Nichele, Stefano (Peer reviewed; Conference object, 2023)
      Random Boolean networks (RBN) and Cellular Automata (CA) operate in a very similar way. They update their state with simple deterministic functions called Boolean function or Transition Table (TT), both being essentially ...
    • A neuro-inspired general framework for the evolution of stochastic dynamical systems: Cellular automata, random Boolean networks and echo state networks towards criticality 

      Pontes-Filho, Sidney; Lind, Pedro; Yazidi, Anis; Zhang, Jianhua; Hammer, Hugo Lewi; Mello, Gustavo; Sandvig, Ioanna; Tufte, Gunnar; Nichele, Stefano (Cognitive Neurodynamics;, Journal article; Peer reviewed, 2020-06-11)
      Although deep learning has recently increased in popularity, it suffers from various problems including high computational complexity, energy greedy computation, and lack of scalability, to mention a few. In this paper, ...
    • Reservoir Computing Using Nonuniform Binary Cellular Automata 

      Nichele, Stefano; Gundersen, Magnus Skogstrøm (Complex Systems;Volume 26, Issue 3, Journal article; Peer reviewed, 2017)
      The reservoir computing (RC) paradigm utilizes a dynamical system (a reservoir) and a linear classifier (a readout layer) to process data from sequential classification tasks. In this paper, the usage of cellular automata ...
    • A single neural cellular automaton for body-brain co-evolution 

      Pontes Filho, Sidney; Walker, Kathryn; Najarro, Elias; Nichele, Stefano; Risi, Sebastian (Chapter; Peer reviewed; Conference object, 2022)
      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 a single cell, including its control ...
    • Structural and functional alterations associated with the LRRK2 G2019S mutation revealed in structured human neural networks 

      Valderhaug, Vibeke Devold; Huse Ramstad, Ola; van de Wijdeven, Rosanne Francisca; Heiney, Kristine; Nichele, Stefano; Sandvig, Axel; Sandvig, Ioanna (bioRxiv;, Journal article, 2020-05-02)
      Mutations in the LRRK2 gene have been widely linked to Parkinson ́s disease. The G2019S variant has been shown to contribute uniquely to both familial and sporadic forms of the disease. LRRK2-related mutations have been ...
    • Towards a Plant Bio-Machine 

      Nichele, Stefano; Risi, Sebastian; Tufte, Gunnar; Beloff, Laura (Chapter; Peer reviewed, 2017)
      Plants are very efficient computing machines. They are able to sense diverse environmental conditions and quickly react through chemical and electrical signaling. In this paper, we present an interface between plants and ...
    • Towards Making a Cyborg: A Closed-Loop Reservoir-Neuro System 

      Aaser, Peter; Knudsen, Martinius; Huse Ramstad, Ola; van de Wijdeven, Rosanne; Nichele, Stefano; Sandvig, Ioanna; Tufte, Gunnar; Bauer, Ulrich Stefan; Halaas, Øyvind; Hendseth, Sverre; Sandvig, Axel; Valderhaug, Vibeke Devold (Chapter; Peer reviewed, 2017)
      The human brain is a remarkable computing machine, i.e. vastly parallel, self-organizing, robust, and energy efficient. To gain a better understanding into how the brain works, a cyborg (cybernetic organism, a combination ...
    • Translating Emotions from EEG to Visual Arts 

      Riccio, Piera; Galati, Francesco; Zuluaga, Maria; De Martin, Juan Carlos; Nichele, Stefano (Lecture Notes in Computer Science;, Chapter; Peer reviewed; Conference object; Journal article, 2022)
      Exploring the potentialities of artificial intelligence (AI) in the world of arts is fundamental to understand and define how this technology is shaping our creativity. We propose a system that generates emotionally ...
    • Universality of Evolved Cellular Automata in-Materio 

      Nichele, Stefano; Farstad, Sigve Sebastian; Tufte, Gunnar (Journal article; Peer reviewed, 2017)
      Evolution-in-Materio (EIM) is a method of using artificial evolution to exploit physical properties of materials for computation. It has previously been successfully used to evolve a multitude of different computational ...