Iterated belief revision requires information about the current beliefs. This information is represented by mathematical structures called doxastic states. Most literature concentrates on how to revise a doxastic state and neglects that it may exponentially grow. This problem is studied for the most common ways of storing a doxastic state. All four of them are able to store every doxastic state, but some do it in less space than others. In particular, the explicit representation (an enumeration of the current beliefs) is the more wasteful on space. The level representation (a sequence of propositional formulae) and the natural representation (a history of natural revisions) are more succinct than it. The lexicographic representation (a history of lexicographic revision) is even more succinct than them.

Representing states in iterated belief revision / Liberatore, Paolo. - In: ARTIFICIAL INTELLIGENCE. - ISSN 0004-3702. - 336:November 2024(2024). [10.1016/j.artint.2024.104200]

Representing states in iterated belief revision

Liberatore, Paolo
2024

Abstract

Iterated belief revision requires information about the current beliefs. This information is represented by mathematical structures called doxastic states. Most literature concentrates on how to revise a doxastic state and neglects that it may exponentially grow. This problem is studied for the most common ways of storing a doxastic state. All four of them are able to store every doxastic state, but some do it in less space than others. In particular, the explicit representation (an enumeration of the current beliefs) is the more wasteful on space. The level representation (a sequence of propositional formulae) and the natural representation (a history of natural revisions) are more succinct than it. The lexicographic representation (a history of lexicographic revision) is even more succinct than them.
2024
artificial intelligence; knowledge representation; belief revision
01 Pubblicazione su rivista::01a Articolo in rivista
Representing states in iterated belief revision / Liberatore, Paolo. - In: ARTIFICIAL INTELLIGENCE. - ISSN 0004-3702. - 336:November 2024(2024). [10.1016/j.artint.2024.104200]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1718116
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