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.
Recommendations
Revising Nonmonotonic Theories: The Case of Defeasible Logic
KI '99: Proceedings of the 23rd Annual German Conference on Artificial Intelligence: Advances in Artificial IntelligenceThe revision and transformation of knowledge is widely recognized as a key issue in knowledge representation and reasoning. Reasons for the importance of this topic are the fact that intelligent systems are gradually developed and refined, and that ...
Overview of knowledge reasoning for knowledge graph
AbstractKnowledge graphs are large-scale semantic networks that considerably impact knowledge representation. Mining hidden knowledge from existing data, including triplet knowledge reasoning, is a primary objective of knowledge graphs. With the ...
Revising Defeasible Theories via Instructions
Rules and ReasoningAbstractProgress in AI raises agent alignment problems. In this paper, we look at the problem of instructing an agent, i.e. informing it about a regularity in the world it did not previously know. We study an idealized case: agents reasoning with logical ...
Comments
Please enable JavaScript to view thecomments powered by Disqus.Information & Contributors
Information
Published In
Publisher
Morgan Kaufmann Publishers Inc.
San Francisco, CA, United States
Publication History
Published: 13 March 1994
Qualifiers
- Article
Acceptance Rates
Overall Acceptance Rate 61 of 177 submissions, 34%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 185Total Downloads
- Downloads (Last 12 months)46
- Downloads (Last 6 weeks)22
Reflects downloads up to 17 Nov 2024
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in