Revising knowledge: a hierarchical approach
Pages 160 - 174
Abstract
A tradition in economics seeks to explain behavior by identifying the underlying preferences which (in a given environment) generate that behavior. This approach was extended in the work of Savage [1954] to decision making under uncertainty. "Belief", and thus "knowledge", are interpreted as properties of individuals' preferences (and thus, in principle, observable choices).
References
[1]
Aumann, R. {1976}. "Agreeing to Disagree," The Annals of Statistics, 4:6, 1236--1239.
[2]
Aumann, R. {1989}. "Notes on Interactive Epistemology", Yale University.
[3]
Binmore, K. and A. Brandenburger {1990}. "Common Knowledge and Game Theory," in Binmore {1990}, Essays on the Foundations of Game Theory. Oxford: Basil Blackwell.
[4]
Blackwell, D. {1951}. "The Comparison of Experiments" in Proceedings, Second Berkeley Symposium on Mathematical Statistics and Probability, 93--102. University of California Press.
[5]
Böge, W. and T. Eisele {1979}. "On Solutions of Bayesian Games," International Journal of Game Theory, 8, 193--215.
[6]
Brandenburger, A. and E. Dekel {1993}. "Hierarchies of Beliefs and Common Knowledge," Journal of Economic Theory, 59:1, 189--198.
[7]
Brandenburger, A., E. Dekel and J. Geanakoplos {1992}. "Correlated Equilibrium with Generalized Information Structures," Games and Economic Behavior, 4, 182--201.
[8]
Fagin, R., J. Halpern and M. Vardi {1991}. "A Model-Theoretic Analysis of Knowledge," Journal of the Association for Computing Machinery, 38:2, 382--428.
[9]
Fagin, R., J. Geanakoplos, J. Halpern and M. Vardi {1992}. "The Expressive Power of the Hierarchical Approach to Modeling Knowledge and Common Knowledge," IBM Almaden Research Center.
[10]
Geanakoplos, J. {1989}. "Game Theory without Partitions, and Applications to Speculation and Consensus," Cowles Foundation Discussion Paper #914, Yale University.
[11]
Geanakoplos, J. {1992}. "Common Knowledge," in 4th Conference on Theoretical Aspects of Reasoning about Knowledge, edited by Y. Moses. San Mateo, California: Morgan Kaufman.
[12]
Gul, F. {1992}. "Savage's Theorem with a Finite Number of States," Journal of Economic Theory, 57:1, 99--110.
[13]
Kripke, S. {1963}. "Semantic analysis of modal logic," Z. Math. Logik Grundlag. der Math., 9, 67--96.
[14]
Machina, M. {1989}. "Dynamic Consistency and Non-Expected Utility Models of Choice Under Uncertainty," Journal of Economic Literature, 27, 1622--1668.
[15]
Mertens, J.-F. and S. Zamir {1985}. "Formulation of Bayesian analysis for Games with Incomplete Information," International Journal of Game Theory, 14:1, 1--29.
[16]
Milgrom, P. and N. Stokey. {1982}. "Information, Trade and Common Knowledge," Journal of Economic Theory, 26:1, 17--27.
[17]
Modica, S. and A. Rustichini {1993}. "Unawareness: a Formal Theory of Unforeseen Contingencies."
[18]
Morris, S. {1991}. "The Role of Beliefs in Economic Theory." Ph.D. dissertation, Yale University.
[19]
Morris, S. {1992a}. "Dynamic Consistency and the Value of Information," CARESS Working Paper #92-17, University of Pennsylvania.
[20]
Morris, S. {1992b}. "Revising Knowledge: A Decision Theoretic Approach," CARESS Working Paper #92-27, University of Pennsylvania.
[21]
Morris, S. and H. Shin {1993}. "Noisy Bayes Updating and the Value of Information," CARESS Working Paper #93-02, University of Pennsylvania.
[22]
Ramsey, F. {1926}. "Truth and Probability," in The Foundations of Mathematics and other Logical Essays. London: Kegan Paul {1930}.
[23]
Rubinstein, A. and A. Wolinsky {1990}. "On the logic of "Agreeing to Disagree" type results," Journal of Economic Theory, 52:1, 190--207.
[24]
Samet, D. {1990}. "Ignoring Ignorance and Agreeing to Disagree," Journal of Economic Theory, 52:1, 190--207.
[25]
Savage, L. {1954}. The Foundations of Statistics. John Wiley and Sons.
[26]
Shin, H. {1992}. "Logical Structure of Common Knowledge," forthcoming in Journal of Economic Theory.
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Published: 13 March 1994
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