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Konferenzbeitrag

Measure Selection: Notions of Rationality and Representation Independence

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44689

Jaeger,  Manfred
Programming Logics, MPI for Informatics, Max Planck Society;

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Zitation

Jaeger, M. (1998). Measure Selection: Notions of Rationality and Representation Independence. In G. S. Cooper, & S. Moral (Eds.), Proceedings of the 14th Conference on Uncertainty in Artificial Intelligence (UAI-98) (pp. 274-281). San Francisco, USA: Morgan Kaufmann.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-3854-9
Zusammenfassung
We take another look at the general problem of selecting a preferred probability measure among those that comply with some given constraints. The dominant role that entropy maximization has obtained in this context is questioned by arguing that the minimum information principle on which it is based could be supplanted by an at least as plausible ``likelihood of evidence'' principle. We then review a method for turning given selection functions into representation independent variants, and discuss the tradeoffs involved in this transformation.