Decision theory with a state of mind represented by an element of a Hilbert space: The Ellsberg paradox

2018 ◽  
Vol 78 ◽  
pp. 131-141 ◽  
Author(s):  
Jürgen Eichberger ◽  
Hans Jürgen Pirner
2015 ◽  
Vol 32 (2) ◽  
pp. 231-248 ◽  
Author(s):  
Richard Bradley

Abstract:What value should we put on our chances of obtaining a good? This paper argues that, contrary to the widely accepted theory of von Neumann and Morgenstern, the value of a chance of some good G may be a non-linear function of the value of G. In particular, chances may have diminishing marginal utility, a property that is termed chance uncertainty aversion. The hypothesis that agents are averse to uncertainy about chances explains a pattern of preferences often observed in the Ellsberg paradox. While these preferences have typically been taken to refute Bayesian decision theory, it is shown that chance risk aversion is perfectly compatible with it.


2018 ◽  
Author(s):  
Ali al-Nowaihi ◽  
Sanjit Dhami ◽  
Mengxing Wei

2020 ◽  
Vol 43 ◽  
Author(s):  
Peter Dayan

Abstract Bayesian decision theory provides a simple formal elucidation of some of the ways that representation and representational abstraction are involved with, and exploit, both prediction and its rather distant cousin, predictive coding. Both model-free and model-based methods are involved.


Author(s):  
J. R. Retherford
Keyword(s):  

PsycCRITIQUES ◽  
2005 ◽  
Vol 50 (23) ◽  
Author(s):  
Michael Fass
Keyword(s):  

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