Skip to main content
SpringerLink
Log in
Book cover

Encyclopedia of Operations Research and Management Science pp 756–764Cite as

Influence Diagrams

  • Reference work entry
  • First Online:

  • 247 Accesses

Introduction

Before influence diagrams were developed, describing and solving decision problems under uncertainty was quite difficult. The first difficulty was determining the probabilistic relationship among uncertain variables, because it is easy to model many variables as jointly related, but extremely difficult to assess their probabilistic relationship. An experienced decision analyst can reasonably assess the uncertainty in a single variable (Spetzler and Staël von Holstein 1975), but more than two variables make the task almost impossible. A better way was needed to understand the relationship among uncertain variables. The second difficulty was understanding and describing the relationship between decisions and uncertainties, particularly indicating which uncertainties would be revealed before which decisions and then transforming the probabilistic descriptions to condition the probabilities in the proper order of information revelation, using Bayes’ Rule. The usual, but very...

This is a preview of subscription content, 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   799.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD   899.99
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

Learn about institutional subscriptions

References

  • Howard, R. (1965). Bayesian models for systems engineering. IEEE Transactions on SystemsScience and Cybernetics, Vol. SSC-1 No. 1, 36–40.

    Google Scholar 

  • Howard, R. A. (1989). Knowledge maps. Management Science, 35(8), 903–922.

    Article  Google Scholar 

  • Howard, R. A. (1990). From influence to relevance to knowledge. In R. M. Oliver, & J. Q. Smith (Eds.), Influence diagrams, belief netsand decision analysis, Proceedings, May 1988 conference (pp. 3–23). New York: John Wiley & Sons.

    Google Scholar 

  • Howard, R., & Matheson, J. (1983). Influence diagrams. In R. A. Howard & J. E. Matheson (Eds.), Readings on the principles and applications of decision analysis (pp. 719–763). Menlo Park, CA: Strategic Decisions Group.

    Google Scholar 

  • Howard, R., & Matheson, J. (2005a). Influence diagrams. Reprinted in the special issue on graphical methods. Decision Analysis, 2 (3), 127–143.

    Google Scholar 

  • Howard, R. A., & Matheson, J. E. (2005b). Influence diagrams retrospective. Special issue on graphical methods. Decision Analysis, 2 (3), 144–147.

    Google Scholar 

  • Howard, R. A., Matheson, J. E., Merkhofer, M. W. (lee), Miller, A. C., & Warner North, D. (2006). Comment on influence diagram retrospective. Decision Analysis, 3 (2), 117–119.

    Google Scholar 

  • Howard, R., Matheson, J., Merkhofer, M., Miller III, A., and Rice, T. (1976). Development of automated aidsfor decision analysis. DARPA Contract MDA 903-74-C-0240. Menlo Park, CA: SRI International.

    Google Scholar 

  • Matheson, J. (1983). Managing the corporate business portfolio. In R. A. Howard & J. E. Matheson (Eds.), Readings on the principles and applications of decision analysis (pp. 311–326). Menlo Park, CA: Strategic Decisions Group.

    Google Scholar 

  • Matheson, J. (1990). Using influence diagrams to value information and control. In R. M. Oliver, & J. Q. Smith (Eds.), Influence diagrams, belief netsand decision analysis. Proceedings, May 1988 conference (pp. 25–63). New York: John Wiley & Sons.

    Google Scholar 

  • Matheson, D., & Matheson, J. (2005). Describing and valuing interventions that observe or control decision situations. In the special issue on graphical methods. Decision Analysis 2 (3), 165–181.

    Google Scholar 

  • Matheson, D., & Matheson, J. (1998). The smart organization, creating value through strategic R&D. Cambridge, MA: Harvard Business School Press.

    Google Scholar 

  • Neapolitan, R. (2004). Learning Bayesian networks. Englewood Cliffs, NJ: Prentice Hall.

    Google Scholar 

  • Olmsted, S. (1983). On representing and solvingdecision problems. Ph.D. thesis, EES Department, Stanford University, Stanford, CA.

    Google Scholar 

  • Pearl, J. (1986). Fusion, propagation, and structuring in belief networks. Artificial Intelligence, 29, 24l–288l.

    Article  Google Scholar 

  • Pearl, J. (2005). Influence diagrams – historical and personal perspectives. Decision Analysis, 2(4), 232–234.

    Article  Google Scholar 

  • Shachter, R. (1986). Evaluating influence diagrams. Operations Research, 34(6), 871–882.

    Article  Google Scholar 

  • Shachter, R. (1988). Probabilistic inference and influence diagrams. Operations Research, 36(4), 589–604.

    Article  Google Scholar 

  • SmartOrg. (2005). Dynamic depression drug: Tutorial. Menlo Park, CA: SmartOrg, Inc.

    Google Scholar 

  • Spetzler, C., & Staël von Holstein, C. (1975). Probability encoding in decision analysis. Management Science, 22, 340–358.

    Article  Google Scholar 

  • World Economic Forum. (2011). Global risks 2011: SixthEdition, an initiative ofthe risk response network. January, Cologny, Geneva.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. SmartOrg, Inc., 855 Oak Grove Aven, Menlo Park, CA, 94025, USA

    James E. Matheson

Authors
  1. James E. Matheson
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to James E. Matheson .

Editor information

Editors and Affiliations

  1. Robert H. Smith School of Business, University of Maryland, College Park, MD, USA

    Saul I. Gass

  2. Robert H. Smith School of Business and Institute for Systems Research, University of Maryland, College Park, MD, USA

    Michael C. Fu

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer Science+Business Media New York

About this entry

Cite this entry

Matheson, J.E. (2013). Influence Diagrams. In: Gass, S.I., Fu, M.C. (eds) Encyclopedia of Operations Research and Management Science. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-1153-7_1160

Download citation

  • DOI: https://doi.org/10.1007/978-1-4419-1153-7_1160

  • Published:

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4419-1137-7

  • Online ISBN: 978-1-4419-1153-7

  • eBook Packages: Business and Economics

Publish with us

Policies and ethics

Search

Navigation