Belief revision and uncertain reasoning
Thinking and Reasoning 7 (3):217 – 234 (2001)
| Abstract | When a new piece of information contradicts a currently held belief, one has to modify the set of beliefs in order to restore its consistency. In the case where it is necessary to give up a belief, some of them are less likely to be abandoned than others. The concept of epistemic entrenchment is used by some AI approaches to explain this fact based on formal properties of the belief set (e.g., transitivity). Two experiments were designed to test the hypothesis that contrary to such views, (i) belief is naturally represented by degrees rather than in an all-or-nothing manner, (ii) entrenchment is primarily a matter of content and not only a matter of form, and (iii) consequently prior degree of belief is a powerful factor of change. The two experiments used Elio and Pelletier's (1997) paradigm in which participants were presented with full simple deductive arguments whose conclusion was denied, following which they were asked to decide which premise to revise. | |||||||||
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Mark Jago (2006). Resource-Bounded Belief Revision and Contraction. In P. Torroni, U. Endriss, M. Baldoni & A. Omicini (eds.), Declarative Agent Languages and Technologies III. Springer.
John L. Pollock & Anthony S. Gillies (2000). Belief Revision and Epistemology. Synthese 122 (1-2):69-92.
Adnan Darwiche & Judea Pearl (1997). On the Logic of Iterated Belief Revision. Artificial Intelligence 89:1-29.
Abhaya C. Nayak (1994). Iterated Belief Change Based on Epistemic Entrenchment. Erkenntnis 41 (3):353-390.
Hans Rott (2003). Basic Entrenchment. Studia Logica 73 (2):257 - 280.
Abhaya C. Nayak, Paul Nelson & Hanan Polansky (1996). Belief Change as Change in Epistemic Entrenchment. Synthese 109 (2):143 - 174.
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