**Fabio Cozman**

A postscript version of this paper is available.

This work appeared as technical report CMU-RI-TR-96-41,
Robotics Institute, Carnegie Mellon University.

- Introduction
- Motivation
- Background
- Quasi-Bayesian theory
- Finitely generated convex sets of distributions
- Exact algorithms and the basic transformation
- Complexity and generic approximations
- Approximate inferences through parameter estimation
- Approximate inferences through Lavine's bracketing algorithm
- Classes of finitely generated convex sets of distributions
- Expected utility and variance
- Conclusion
- References

© Fabio Cozman[Send Mail?]

Tue Jan 21 15:59:56 EST 1997