Skip to main content
SpringerLink
Log in

Human Brain Computer/Machine Interface System Feasibility Study for Independent Core Observer Model Based Artificial General Intelligence Collective Intelligence Systems

  • Conference paper
  • First Online:
Biologically Inspired Cognitive Architectures 2019 (BICA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 948))

Included in the following conference series:

Abstract

This paper is primarily designed to help address the feasibility of building optimized mediation clients for the Independent Core Observer Model (ICOM) cognitive architecture for Artificial General Intelligence (AGI) mediated Artificial Super Intelligence (mASI) research program where this client is focused on collecting contextual information and the feasibility of various hardware methods for building that client on, including Brain Computer Interface (BCI), Augmented Reality (AR), Mobile and related technologies. The key criteria looked at is designing for the most optimized process for mediation services in the client as a key factor in overall mASI system performance with human mediation services is the flow of contextual information via various interfaces.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 139.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 179.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Jaffen D Optimizing brain performance, Center for Brain Health, Brain Performance Institute, University of Texas

    Google Scholar 

  2. Kelley D (2018/2019) Architectural overview of a ‘mediated’ artificial super intelligence systems based on the independent core observer model cognitive architecture. Informatica (Summitted and pending)

    Google Scholar 

  3. Kelley D, Twymen M (2019) Independent core observer model (ICOM) theory of consciousness as implemented in the ICOM cognitive architecture and associated consciousness measures. In: AAAI spring symposia 2019, Stanford University. (under review)

    Google Scholar 

  4. Kelley D, Waser M (2018) Human-like emotional responses in a simplified independent core observer model system. Procedia Comput Sci 123:221–227

    Article  Google Scholar 

  5. Kelley D (2016) Part V - artificial general intelligence. (3 Chapters in book titled: Google-It). Springer Scientific 2016, New York. ISBN: 978-1-4939-6413-0

    Google Scholar 

  6. Li G, Zhang D (2016) Brain-computer interface controlled cyborg: establishing a functional information transfer pathway from human brain to cockroach brain. https://doi.org/10.1371/journal.pone.0150667

    Article  Google Scholar 

  7. Tovée M (1994) Neuronal processing: how fast is the speed of thought? https://doi.org/10.1016/s0960-9822(00)00253-0

    Article  Google Scholar 

  8. Wang X, Yu K, Wu S, Gu J, Liu Y, Dong C, Loy C, Quio Y, Tang X (2018) ESRGAN: enhanced super-resolution generative adversarial networks, Cornell University, arXiv:1809.00219v2

  9. Wikipedia Foundation (2019) Emotiv. https://en.wikipedia.org/wiki/Emotiv

  10. Wikipedia Foundation (2019) OpenBCI. https://en.wikipedia.org/wiki/OpenBCI

  11. Wikipedia Foundation (2019) Google Glass. https://en.wikipedia.org/wiki/Google_Glass

  12. Wikipedia Foundation (2019) Microsoft HoloLens. https://en.wikipedia.org/wiki/Microsoft_HoloLens

  13. Wikipedia Foundation (2019) Magic Leap. https://en.wikipedia.org/wiki/Magic_Leap

  14. Wikipedia Foundation (2019) Android (operating system). https://en.wikipedia.org/wiki/Android_(operating_system)

  15. Wikipedia Foundation (2019) iOS. https://en.wikipedia.org/wiki/IOS

  16. Wikipedia Foundation (2019) Windows 10. https://en.wikipedia.org/wiki/Windows_10

  17. Wikipedia Foundation (2019) Kernel (neurotechnology company). https://en.wikipedia.org/wiki/Kernel_(neurotechnology_company)

  18. Wikipedia Foundation (2019) Neuralink. https://en.wikipedia.org/wiki/Neuralink

  19. Wikipedia Foundation (2019) Mary Lou Jepsen. https://en.wikipedia.org/wiki/Mary_Lou_Jepsen

  20. Zhou B, Wu X, Lv Z, Guo X (2016) A fully automated trail selection method for optimization of motor imagery based brain-computer interface. PLoS ONE. https://dol.org/10.1371/journal.pone.0162657

Download references

Author information

Authors and Affiliations

  1. AGI Laboratory, Provo, UT, USA

    David J. Kelley

  2. Seattle, WA, USA

    Kyrtin Atreides

Authors
  1. David J. Kelley
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kyrtin Atreides
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to David J. Kelley .

Editor information

Editors and Affiliations

  1. Moscow Engineering Physics Institute (MEPhI), Department of Cybernetics, National Research Nuclear University (NRNU), Moscow, Russia

    Alexei V. Samsonovich

Rights and permissions

Reprints and permissions

Copyright information

© 2020 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kelley, D.J., Atreides, K. (2020). Human Brain Computer/Machine Interface System Feasibility Study for Independent Core Observer Model Based Artificial General Intelligence Collective Intelligence Systems. In: Samsonovich, A. (eds) Biologically Inspired Cognitive Architectures 2019. BICA 2019. Advances in Intelligent Systems and Computing, vol 948. Springer, Cham. https://doi.org/10.1007/978-3-030-25719-4_25

Download citation

Publish with us

Policies and ethics

Search

Navigation