David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
International Journal of Approximate Reasoning 5 (2):149-181 (1991)
The main ingredients of Spohn's theory of epistemic beliefs are (1) a functional representation of an epistemic state called a disbelief function and (2) a rule for revising this function in light of new information. The main contribution of this paper is as follows. First, we provide a new axiomatic definition of an epistemic state and study some of its properties. Second, we study some properties of an alternative functional representation of an epistemic state called a Spohnian belief function. Third, we state a rule for combining disbelief functions that is mathematically equivalent to Spohn's belief revision rule. Whereas Spohn's rule is defined in terms of the initial epistemic state and some features of the final epistemic state, the rule of combination is defined in terms of the initial epistemic state and the incremental epistemic state representing the information gained. Fourth, we state a rule of subtraction that allows one to recover the addendum epistemic state from the initial and final epistemic states. Fifth, we study some properties of our rule of combination. One distinct advantage of our rule of combination is that besides belief revision, it can be used to describe an initial epistemic state for many variables when this information is given as several independent epistemic states each involving few variables. Another advantage of our reformulation is that we can show that Spohn's theory of epistemic beliefs shares the essential abstract features of probability theory and the Dempster-Shafer theory of belief functions. One implication of this is that we have a ready-made algorithm for propagating disbelief functions using only local computation.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
Franz Huber (2007). The Consistency Argument for Ranking Functions. Studia Logica 86 (2):299-329.
Franz Huber (2014). New Foundations for Counterfactuals. Synthese 191 (10):2167-2193.
Franz Huber (2013). Belief Revision II: Ranking Theory. Philosophy Compass 8 (7):613-621.
Similar books and articles
Peter Gärdenfors (1990). An Epistemic Analysis of Explanations and Causal Beliefs. Topoi 9 (2):109-124.
Giacomo Bonanno (2011). AGM Belief Revision in Dynamic Games. In Krzysztof Apt (ed.), Proceedings of the 13th Conference on Theoretical Aspects of Rationality and Knowledge (TARK XIII).
Nir Friedman & Joseph Y. Halpern (1999). Belief Revision: A Critique. [REVIEW] Journal of Logic, Language and Information 8 (4):401-420.
Glenn Shafer (1981). Jeffrey's Rule of Conditioning. Philosophy of Science 48 (3):337-362.
Abhaya C. Nayak (1994). Iterated Belief Change Based on Epistemic Entrenchment. Erkenntnis 41 (3):353-390.
Kevin T. Kelly (1999). Iterated Belief Revision, Reliability, and Inductive Amnesia. Erkenntnis 50 (1):11-58.
Hans P. Van Ditmarsch (2005). Prolegomena to Dynamic Logic for Belief Revision. Synthese 147 (2):229 - 275.
Hans P. Van Ditmarsch (2005). Prolegomena to Dynamic Logic for Belief Revision. Synthese 147 (2):229-275.
Prakash P. Shenoy (1991). On Spohn's Theory of Epistemic Beliefs. In B. Bouchon-Meunier, R. R. Yager & L. A. Zadeh (eds.), Uncertainty in Knowledge Bases. Springer 1--13.
Added to index2009-07-26
Total downloads4 ( #424,619 of 1,726,249 )
Recent downloads (6 months)0
How can I increase my downloads?