• Achieving Connectivity between Wide Areas Through Self-Organising Robot Swarms using Embodied Evolution 

      Erik Aaron, Hansen; Nichele, Stefano; Yazidi, Anis; Haugerud, Hårek; Abolpour Mofrad, Asieh; Alcocer, Alex (Chapter; Peer reviewed, 2018)
      Abruptions to the communication infrastructuremight occur occasionally, where manual intervention by dedi-cated personnel is needed to fix the interruptions, restoring com-munication abilities. However, sometimes this can ...
    • Assessment and manipulation of the computational capacity of in vitro neuronal networks through criticality in neuronal avalanches 

      Heiney, Kristine; Huse Ramstad, Ola; Sandvig, Ioanna; Sandvig, Axel; Nichele, Stefano (2019 IEEE Symposium Series on Computational Intelligence (SSCI);, Chapter; Conference object; Peer reviewed, 2020)
      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 the size distribution of network-wide ...
    • Autonomous configuration of network parameters in operating systems using evolutionary algorithms 

      Gembala, Bartosz Gembala; Yazidi, Anis; Haugerud, Hårek; Nichele, Stefano (Proceedings of the 2018 Conference on Research in Adaptive and Convergent Systems;, Chapter; Peer reviewed, 2018)
      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 network stack by increasing the network buffers ...
    • CA-NEAT: Evolved Compositional Pattern Producing Networks for Cellular Automata Morphogenesis and Replication 

      Nichele, Stefano; Ose, Mathias Berild; Risi, Sebastian; Tufte, Gunnar (Journal article; Peer reviewed, 2017)
      Cellular Automata (CA) are a remarkable example of morphogenetic system, where cells grow and self-organise through local interactions. CA have been used as abstractions of biological development and artificial life. Such ...
    • Deep learning with cellular automaton-based reservoir computing 

      Nichele, Stefano; Molund, Andreas (Complex Systems;Volume 26, Issue 4, Journal article; Peer reviewed, 2017)
      Recurrent neural networks (RNNs) have been a prominent concept wiithin artificial intelligence. They are inspired by biological neural net works (BNNs) and provide an intuitive and abstract representation of how BNNs work. ...
    • Ethics of artificial intelligence demarcations 

      Hansen, Anders Braarud; Nichele, Stefano (Communications in Computer and Information Science;1056, Chapter; Peer reviewed, 2019)
      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 distinguishing issues and concerns related to ...
    • Evolved Art with Transparent, Overlapping, and Geometric Shapes 

      Berg, Joachim; Berggren, Nils Gustav Andreas; Borgeteien, Sivert; Jahren, Christian; Sajid, Arqam; Nichele, Stefano (Communications in Computer and Information Science;Volume 1056, Chapter; Conference object; Peer reviewed, 2019-11-22)
      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, lines. Genotypes representing features and ...
    • FeLT- The Futures of Living Technologies 

      Bergaust, Kristin; Nichele, Stefano (Electronic Workshops in Computing (eWiC);Proceedings of POM Beirut 2019, Conference object; Journal article; Peer reviewed, 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; Peer reviewed, 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 ...
    • 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), Chapter; Conference object; Peer reviewed, 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...
    • 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 ...