Systems Realization Laboratory

Workshop: Uncertainty Representation in Robust and

Reliability-Based Design

Jason Aughenbaugh (Univ Texas, Austin)Zissimos Mourelatos (Oakland University)

Chris Paredis (Georgia Tech)

2006 International Design Engineering Technical ConferencesPhiladelphia, PA, September 10, 2006

Systems Realization Laboratory

Workshop Overview

Objective: Promote understanding and discussion of uncertainty representations• Introduction to various uncertainty representations• Comparison and evaluation of uncertainty representations for design

Focus on three different uncertainty representations• Probability theory

Prof. Wei Chen, Northwestern University

• Possibility theory and evidence theory Dr. Scott Ferson, Applied Biomathematics

• Imprecise probability theory Prof. Zissimos Mourelatos, Oakland University

http://www.srl.gatech.edu/Members/cparedis/Workshop

Systems Realization Laboratory

Schedule

1:15 – 1:25: Welcome and introductionsChris Paredis

1:25 – 1:45: Criteria for evaluating uncertainty representationsJason Aughenbaugh

1:45 – 2:15: Probability TheoryWei Chen

2:15 – 2:45: Imprecise Probability TheoryScott Ferson

2:45 – 3:00: Coffee Break 3:00 – 3:30: Possibility and Evidence Theory

Zissimos Mourelatos 3:30 – 4:30: Discussion

Chris Paredis

Systems Realization Laboratory

Topics for Discussion

Representation

Inference / Computation

Decision Making

Other issues: validation, sensitivity analysis, …• If time permits

Final Conclusions

Systems Realization Laboratory

Representation

Expressivity• Is there a need to go beyond probabilities?• Is there a fundamental difference between reducible and irreducible

uncertainty?• What is the relationship between these different representations?

Are they mutually exclusive?

Elicitation• Do all the representations covered today have an unambiguous

definition and elicitation process?• How does one aggregate expert knowledge?

Systems Realization Laboratory

Inference & Computation

Fundamental Issues• How should one evaluate whether a certain inference mechanism

that leads to valid conclusions?• Do the inference mechanisms presented today lead to valid

conclusions?

Computational Issues• To what extent do computational issues play a role in selecting a

formalism• What are the limitations and assumptions that exist in the current

inference algorithms?• What is the maturity level? Can these formalisms be applied to real-

world problems?

Systems Realization Laboratory

Decision Making

Fundamental Issues• How should one compare different decision making methodologies?• Which representation should be used when? Is there one

representation that should always be used?

Decision Making in Engineering Design• Do decisions in engineering design have characteristics that make

some uncertainty representations better suited than others?• How should engineering design decisions be framed within each of

these methodologies? Are there differences?

Systems Realization Laboratory

Final Conclusions

What have we learned today?