Generalisation of Samet's (2010) agreement theorem
AbstractWe develop a framework that allows us to reproduce the generalised agreement theorem of Samet (2010), and extend it to models with a non-partitional information structure, while highlighting the features that distinguish the result from the classic theorems found in the literature. Furthermore, we produce results that are similar to Samet’s with some modified assumptions.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 29067.
Date of creation: 23 Feb 2011
Date of revision:
Agreeing to disagree; knowledge; common knowledge; belief; information; epistemic logic;
Find related papers by JEL classification:
- D89 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Other
- D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search, Learning, and Information
- D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
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- Tarbush, Bassel, 2011. "Agreeing to disagree with generalised decision functions," MPRA Paper 29066, University Library of Munich, Germany.
- Dov Samet, 2006.
"Agreeing to disagree: The non-probabilistic case,"
321307000000000536, UCLA Department of Economics.
- Robert J Aumann, 1999. "Agreeing to Disagree," Levine's Working Paper Archive 512, David K. Levine.
- Giacomo Bonanno & Klaus Nehring, .
"Assessing The Truth Axiom Under Incomplete Information,"
Department of Economics
97-03, California Davis - Department of Economics.
- Bonanno, Giacomo & Nehring, Klaus, 1998. "Assessing the truth axiom under incomplete information," Mathematical Social Sciences, Elsevier, vol. 36(1), pages 3-29, July.
- Klaus Nehring & Giacomo Bonanno, 2003. "Assessing The Truth Axiom Under Incomplete Information," Working Papers 973, University of California, Davis, Department of Economics.
- Bacharach, Michael, 1985. "Some extensions of a claim of Aumann in an axiomatic model of knowledge," Journal of Economic Theory, Elsevier, vol. 37(1), pages 167-190, October.
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