Skip to main content

The Importance of Grain Size in Communication Within Cyber-Physical Systems

  • Conference paper
  • First Online:
Applied Cyber-Physical Systems
  • 2681 Accesses

Abstract

This chapter will look at various applications of natural language communication to cyber-physical systems. One of the assumptions that it makes is that such communication is not only necessary for the future systems, but also should be done on a level acceptable and natural to humans, rather than training them to accommodate machine capabilities with exact and precise commands. We will address a grain size of commands or descriptions that could be given to a system—at the same time the physical capabilities of a system will be sketched only as needed for purposes of examples. The range of commands that we are talking about is a typical algorithmic description of a task at the low level and a natural one for a human task description on the high level. A low, more detailed, fine-grain-sized level is assumed to exist already. The higher, coarser-grain-sized level is what we are striving for, in the sense of being able to switch to it automatically when convenient, i.e., to pay with some vagueness, as people and language do, for the ease of not having to resolve an ambiguity.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover 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

Notes

  1. 1.

    Let us assume here that animals do know things and can be valid agents of the concept know just like people are valid agents of it.

  2. 2.

    The author is grateful to Victor Raskin for pointing out that this is not that different from considerations underlying Weinreich’s [19] objections to what he referred to as Katz and Fodor’s [20] “infinite polysemy” in their semantic theory. Why, Weinreich asked, does the theory have to differentiate between two senses of ingest (eat solids/drink liquids) but not between two senses of eat (with a fork/with a spoon)? Reversing it to fit our discussion, we can say that English masks the latter distinction with the word eat but reveals the former distinction with two different words, both, incidentally, in much more common usage than the masking ingest.

References

  1. J. M Taylor, V. Raskin, C. F. Hempelmann, & S. Attardo, An Unintentional Inference and Ontological Property Defaults. Proc. IEEE SMC 2010, Istanbul, Turkey, 2010.

    Google Scholar 

  2. V. Raskin, J. M. Taylor, & C. F. Hempelmann, “Ontological Semantic Technology for Detecting Insider Threat and Social Engineering.” Proc NSPW-2010, Concorde, MA, 2010.

    Google Scholar 

  3. V. Raskin, S. Nirenburg, I. Nirenburg, C. F. Hempelmann, & K. E. Triezenberg, “The Genesis of a Script for Bankruptcy in Ontological Semantics, in G. Hirst and S. Nirenburg, Eds., Proceedings of the Text Meaning Workshop, HLT/NAACL 2003: Human Language Technology and North American Chapter of the Association of Computational Linguistics Conference. ACL: Edmonton, Alberta, Canada, May 31, 2003.

    Google Scholar 

  4. J. A. Crowder, J. M. Taylor, & V. Raskin, “Autonomous Creation and Detection of Procedural Memory Scripts.” International Conference on Artificial Intelligence, Las Vegas, NE, July 2012.

    Google Scholar 

  5. R. C. Schank, Computer Models of Thought and Language. San Francisco: Freeman, 1973.

    Google Scholar 

  6. R. C. Schank, & R. Abelson, Scripts, Plans, Goals, and Understanding. New York: Wiley, 1977.

    Google Scholar 

  7. V. Raskin, C. F. Hempelmann, & J. M. Taylor, “Guessing vs. Knowing: The Two Approaches to Semantics in Natural Language Processing,” in A. E. Kibrik, Ed., Proceedings of Annual International Conference Dialogue, Moscow, Russia: AABBY/Yandex.

    Google Scholar 

  8. J. M. Taylor, V. Raskin, & C. F. Hempelmann, “On an Automatic Acquisition Toolbox for Ontologies and Lexicons in Ontological Semantics.” Proc. ICAI-2010: International Conference on Artificial Intelligence, Las Vegas, NE, 2010.

    Google Scholar 

  9. C. F. Hempelmann, J. M. Taylor, & V. Raskin, “Application-Guided Ontological Engineering.” Proc. ICAI-2010: International Conference on Artificial Intelligence, Las Vegas, NE, 2010.

    Google Scholar 

  10. J. M. Taylor, V. Raskin, & C. F. Hempelmann, “From Disambiguation Failures to Common-Sense Knowledge Acquisition: A day in the Life of an Ontological Semantic System.” Proc. Web Intelligence Conference, Lyon, France, August, 2011.

    Google Scholar 

  11. J. M. Taylor, V. Raskin, & C. F. Hempelmann, “Post-Logical Verification of Ontology and Lexicons: The Ontological Semantic Technology Approach.” International Conference on Artificial Intelligence, Las Vegas, NE, July, 2011.

    Google Scholar 

  12. J. M. Taylor, & V. Raskin, “Graph Decomposition and Its Use for Ontology Verification and Semantic Representation, Intelligent Linguistic Technologies Workshop at International Conference on Artificial Intelligence, Las Vegas, NE, July, 2011.

    Google Scholar 

  13. J. M. Taylor, & V. Raskin, “Understanding the unknown: Unattested input processing in natural language,” FUZZ-IEEE Conference, Taipei, Taiwan, June, 2011.

    Google Scholar 

  14. S. Nirenburg, & V. Raskin, Ontological Semantics. Cambridge, MA: MIT Press, 2004.

    Google Scholar 

  15. J. McCarthy, “Programs With Common Sense.” Proceedings of the Teddington Conference on the Mechanization of Thought Processes, 75–91. London: Her Majesty’s Stationary Office, 1959.

    Google Scholar 

  16. D. B. Lenat, “CYC: Toward Programs With Common Sense.” Communications of the ACM 33:8, 30–49, 1990.

    Google Scholar 

  17. J. M. Gordon, & L. K. Schubert, “Quantificational Sharpening of Commonsense Knowledge”, in: Havasi 2010, 27–32.

    Google Scholar 

  18. C. Havasi, D. B. Lenat, & B. Van Durme, Eds., Commonsense Knowledge: Papers from the AAAI Fall Symposium. Menlo Park, CA: AAAI Press, 2010.

    Google Scholar 

  19. H. Liu, & P. Singh, “ConceptNet—a Practical Commonsense Reasoning Tool-Kit, BT Technology Journal, 22:4. 211–226, 2004.

    Google Scholar 

  20. U. Weinreich, “Explorations in Semantic Theory.” In: T. A. Sebeok, Ed., Current Trends in Linguistics, Vol. 3, 395–477, The Hague: Mouton, 1966.

    Google Scholar 

  21. J. J. Katz, & J. A. Fodor, “The Structure of a Semantic Theory,” Language 39:1, 170–210, 1963.

    Google Scholar 

  22. J. M. Taylor, V. Raskin, & L. M. Stuart, “Matching Human Understanding: Syntax and Semantics Revisited.” Proc. IEEE SMC 2012, Seoul, Korea, 2012.

    Google Scholar 

  23. E. Matson, J. Taylor, V. Raskin, B.-C. Min, & E. Wilson, “A Natural Language Model for Enabling Human, Agent, Robot and Machine Interaction.” The 5th IEEE International Conference on Automation, Robotics and Applications, Wellington, New Zealand, December 2011.

    Google Scholar 

  24. D. Erickson, M. DeWees J. Lewis, & E. T. Matson, “Communication for Task Completion with Heterogeneous Robots.” 1st International Conference on Robot Intelligence Technology and Applications, Gwangju, South Korea, 2012.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Julia M. Taylor .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer Science+Business Media New York

About this paper

Cite this paper

Taylor, J.M. (2014). The Importance of Grain Size in Communication Within Cyber-Physical Systems. In: Suh, S., Tanik, U., Carbone, J., Eroglu, A. (eds) Applied Cyber-Physical Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7336-7_9

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7336-7_9

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7335-0

  • Online ISBN: 978-1-4614-7336-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics