Weekly Twitter Selection

Our weekly short collection of relevant scholarly information, publications and news found on Twitter.

What we are reading

There are numerous publications as well as initiatives that inform or inspire our work with the NRP, and we will add items to the list below while our work progresses. Feel free to send us a quick note at neurorobotics@ebrains.eu, if you wish to suggest us something to include.

Neurorobotics


  • Arbib M.A., Metta G., van der Smagt P. (2008). Neurorobotics: From Vision to Action, In: Siciliano B., Khatib O. (eds) Springer Handbook of Robotics. Springer, Berlin, Heidelberg. [link]

  • Baillie, J.C. (2017). Why AI Needs a Body, Medium. [link]

  • Baillie, J.C. (2020). Developmental AI: How Virtual Worlds Could Contribute, Medium.[link]

  • Bassett, D. S. et al. (2020). Reflections on the past two decades of neuroscience, Nature Reviews. [link]

  • Bitar, M. and Barry, G. (2020). Building a Human Brain for Research, Frontiers in Molecular Neuroscience.[link]

  • Cave, S., Dihal, K., Dillon, S. (2020). AI Narratives, Oxford University Press.

  • Chemero, A. (2011). Radical Embodied Cognitive Science, MIT Press.

  • Crook, S.M. et al. (2020). Reproducibility and Rigour in Computational Neuroscience, Frontiers in Neuroinformatics.[link]

  • Evans, E. (2003). Domain-Driven Design (Tackling Complexity in the Heart of Software). Addison-Wesley Professional ed.

  • Furber, S. (ed.), Bogdan, P. (ed.) (2020). SpiNNaker: A Spiking Neural Network Architecture, Boston-Delft: now publishers, [link]

  • Huang, W. et al. (2020). Dynamic simulation of articulated soft robots, Nature Communications. [link]

  • Janner, M. (2019). Model-Based Reinforcement Learning: Theory and Practice, Berkeley Artificial Intelligence Research. [link]

  • Key Papers in Deep RL, OpenAI. [link]

  • Marcus, G (2020). The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence, Cornell University. [link]

  • Santucci, V. G., Oudeyer, P.-Y., Barto, A., Baldassarre, G., eds. (2020). Intrinsically Motivated Open-Ended Learning in Autonomous Robots, Frontiers in Neurorobotics and Frontiers in Robotics and AI.[link]

  • Scalable agent architecture for distributed training, DeepMind, 2018. [link]

  • Seymour, B., and Lee, S. W. (2019). Decision-making in brains and robots - the case for an interdisciplinary approach, Current Opinion in Behavioral Sciences. [link]

  • Sejnowski, T. J. (2018). The Deep Learning Revolution, The MIT Press.

  • Stone, J.V. (2020). A brief guide to Artificial Intelligence, Sebtel Press.[link]

  • Summerfield, C. (2018). How to build a brain from scratch, Oxford Neuroscience.[link]

  • Ullman, S. (2019). Using neuroscience to develop artificial intelligence, Science. [link]

  • Weng, L. (2018). Policy Gradient Algorithms, [link]


Responsible Innovation


  • AI4SDGs Cooperation Network Advancing UN Sustainable Development Goals and Digital Cooperation through AI Innovation and Partner Networks

  • Doteveryone (2019). Consequence Scanning: An Agile event for Responsible Innovators. [link]

  • europa.eu (last checked 09/06/2020). Data protection under GDPR [link]

  • Floridi, L. (2020). AI and Its New Winter: from Myths to Realities, Philosophy and Technology.[link]

  • Ryan, M. and Carsten Stahl, B. (2020). Artificial intelligence ethics guidelines for developers and users: clarifying their content and normative implications [link]

  • SIENNA project [link]

  • The global AI agenda: Promise, reality, and a future of data sharing, MIT Technology Review. [link]

  • The OECD Forum Network (2019). New Frontiers of the Mind: Enabling responsible innovation in neurotechnology [link]

  • The Open Dialogue on AI Ethics | Contribution to the UNESCO Recommendation on the Ethics of Artificial Intelligence [link]

  • Ulnicane, I. (2020). The governance of dual-use research in the EU The case of neuroscience, in Emerging Security Technologies and EU Governance, Routledge. [link]



Interesting initiatives


  • AI2-THOR, Open source interactive environments for embodied AI.

  • KnowledgeSpace- a community-based, data-driven encyclopedia for neuroscience, a joint development between the Human Brain Project (HBP), the International Neuroinformatics Coordinating Facility (INCF), and the Neuroscience Information Framework (NIF).

  • NeuroStars- A question and answer forum for neuroscience researchers, infrastructure providers and software developers.

  • NFDI NEUROSCIENCE, National Research Data Infrastructure for Neuroscience

  • NINAI- Neuroscience-Inspired Networks for Artificial Intelligence