Skip to main content

Decision Making in the Presence of Noise

  • Chapter
Informatik

Part of the book series: TEUBNER-TEXTE zur Informatik ((TTZI,volume 1))

Abstract

We consider problems of decision making based on imperfect information. We derive Bayesian optimal decision procedures for some simple one-person games on trees in which the player is given redundant but noisy information about the true configuration of the game. Our procedures are computationally efficient, and the decision rules which they implement are describable by simple formulas. Not surprisingly, the presence of noise greatly affects the decision procedure, and decisions procedures that are optimal for the corresponding noiseless games may be far from optimal in the presence of noise. In many cases, the optimal decision depends not only on the given noisy data but also on knowledge of the expected amount of noise present in the data. For arbitrary mN, we present examples in which the optimal decision changes m times as the probability of error in an individual datum increases from 0 to 1/2. Thus, no decision procedure that is insensitive to (or does not know) the amount of uncertainty in the data can perform as well as one that is aware of the unreliability of its data.

This research was supported in part by National Science Foundation grant IRI-9015570.

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 49.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 49.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. John Geanakoplos and Larry Gray, June 1991. Personal communication.

    Google Scholar 

  2. John Geanakoplos and Larry Gray. When seeing further is not seeing better. Manuscript, July 1991.

    Google Scholar 

  3. Judea Pearl. On the nature of pathology in game searching. Artificial Intelligence, 20:427–453, 1983.

    Article  MATH  Google Scholar 

  4. Sheldon Ross. A first course in Probability. Macmillan, New York, NY, 1976.

    MATH  Google Scholar 

  5. Martin Shubik. Game Theory in the social sciences. MIT Press, Cambridge, MA, 1982.

    MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1992 B. G. Teubner Verlagsgesellschaft, Leipzig

About this chapter

Cite this chapter

Fischer, M.J., Paleologou, S.A. (1992). Decision Making in the Presence of Noise. In: Buchmann, J., Ganzinger, H., Paul, W.J. (eds) Informatik. TEUBNER-TEXTE zur Informatik, vol 1. Vieweg+Teubner Verlag, Wiesbaden. https://doi.org/10.1007/978-3-322-95233-2_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-322-95233-2_9

  • Publisher Name: Vieweg+Teubner Verlag, Wiesbaden

  • Print ISBN: 978-3-8154-2033-1

  • Online ISBN: 978-3-322-95233-2

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics