[go: up one dir, main page]
More Web Proxy on the site http://driver.im/
Skip to main content

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12766))

Included in the following conference series:

  • 708 Accesses

Abstract

This paper proposes a new field of knowledge that aims to integrate explicit knowledge and tacit knowledge, with quantitative treatment. The aim of wisdom science is to formulate a theory of knowledge based on brain activities, and on more detailed level, on neuron functions. Tacit and explicit knowledge are treated as two facets that represent knowledge of a person, differing from conventional interpretation of two independent entities. The hypernetwork model is used to describe both tacit and explicit knowledge, which is capable of representing structures that cannot be described by conventional system models. The concept of system science serves as the basic framework for the modeling and analysis.

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

Access this chapter

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 35.99
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 44.99
Price includes VAT (United Kingdom)
  • 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

Similar content being viewed by others

References

  1. Polanyi, M.: Genius in science. Encounter 38, 43–50 (1972)

    Google Scholar 

  2. Nonaka, I.: A dynamic theory of organizational knowledge creation. Organ. Sci. 5, 14–37 (1994)

    Article  Google Scholar 

  3. Klein, G.: Sources of Power: How People Make Decisions. MIT Press, Cambridge (2017)

    Book  Google Scholar 

  4. Klein, G.: A recognition primed decision (RPD) model of rapid decision making. In: Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E. (eds.) Decision Making in Action, pp. 138–147. Ablex (1993)

    Google Scholar 

  5. Klein, G.A., Orasanu, J., Calderwood, R., Zsambok, C.E.: Decision Making in Action. Ablex (1993)

    Google Scholar 

  6. Kahneman, D.: Thinking, Fast and Slow. Farrar, Straus and Giroux (2011)

    Google Scholar 

  7. Doya, K.: Complementary roles of basal ganglia and cerebellum in learning and motor control. Curr. Opin. Neurobiol. 10, 732–739 (2000)

    Article  Google Scholar 

  8. Doya, K., Shadlen, M.N.: Decision making, editorial overview. Curr. Opin. Neurobiol. 22, 911–913 (2002)

    Article  Google Scholar 

  9. Damasio, A.: Descartes’ Error: Emotion. Reason and the Human Brain. Grosset/Putnam (1994)

    Google Scholar 

  10. Quiroga, R.Q., Reddy, L., Kreiman, G., Koch, C., Fried, I.: Invariant visual representation by single neurons in the human brain. Nature 435, 1102–1107 (2005)

    Article  Google Scholar 

  11. Maeshiro, T.: Framework based on relationship to describe non-hierarchical, boundaryless and multi-perspective phenomena. SICE Journal of Control, Measurement, and System Integration 11, 381–389 (2019)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Tetsuya Maeshiro .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Maeshiro, T. (2021). Proposal of Wisdom Science. In: Yamamoto, S., Mori, H. (eds) Human Interface and the Management of Information. Information-Rich and Intelligent Environments. HCII 2021. Lecture Notes in Computer Science(), vol 12766. Springer, Cham. https://doi.org/10.1007/978-3-030-78361-7_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-78361-7_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-78360-0

  • Online ISBN: 978-3-030-78361-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics