Merging Possibilistic Belief Bases by Argumentation

2017 ◽  
pp. 24-34 ◽  
Author(s):  
Thi Hong Khanh Nguyen ◽  
Trong Hieu Tran ◽  
Tran Van Nguyen ◽  
Thi Thanh Luu Le
Keyword(s):  
Belief Bases

Consistency-based Revision of Structured Belief Bases

2015 ◽  
Vol 136 (4) ◽  
pp. 381-404 ◽  
Author(s):  
Michał Korpusik ◽  
Witold Łukaszewicz ◽  
Ewa Madalińska-Bugaj
Keyword(s):  
Belief Bases

Argumentation Framework for Merging Stratified Belief Bases

2016 ◽  
pp. 43-53 ◽  
Author(s):  
Trong Hieu Tran ◽  
Thi Hong Khanh Nguyen ◽  
Quang Thuy Ha ◽  
Ngoc Trinh Vu
Keyword(s):  
Argumentation Framework ◽  
Belief Bases

On Structured Belief Bases

2001 ◽  
pp. 349-367 ◽  
Author(s):  
Renata Wassermann
Keyword(s):  
Belief Bases

Multi-source multiple change on belief bases

2019 ◽  
Vol 110 ◽  
pp. 145-163 ◽  
Author(s):  
Luciano H. Tamargo ◽  
Cristhian A.D. Deagustini ◽  
Alejandro J. García ◽  
Marcelo A. Falappa ◽  
Guillermo R. Simari
Keyword(s):  
Belief Bases

scholarly journals System Z for Conditional Belief Bases with Positive and Negative Information

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Meliha Sezgin ◽  
Gabriele Kern-Isberner
Keyword(s):  
Negative Information ◽  
Trivial Extension ◽  
Positive Information ◽  
Conditional Belief ◽  
Belief Base ◽  
Belief Bases

In non-monotonic reasoning, conditional belief bases mostly contain positive information in the form of standard conditionals. However, in practice we are often confronted with negative information, stating that a conditional does \emph{not} hold, i.e. we need a suitable approach for reasoning over belief bases $\Delta$ with positive and negative information. In this paper, we investigate the interaction of positive and negative information in a conditional belief base and establish a property for partitions of $\Delta$ that is equivalent to consistency. Based on this property, we develop a non-trivial extension of system Z for mixed conditional belief bases and provide an algorithm to compute this partition.

scholarly journals Selection Strategies for Inductive Reasoning From Conditional Belief Bases and for Belief Change Respecting the Principle of Conditional Preservation

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Christoph Beierle ◽  
Gabriele Kern-Isberner
Keyword(s):  
Belief Change ◽  
Inductive Reasoning ◽  
Conditional Belief ◽  
Belief Base ◽  
Belief Bases ◽  
Selection Strategies ◽  
Ranking Model

Given a belief base ∆ consisting of a set of conditionals,there are many different ways an agent may inductivelycomplete the knowledge represented by ∆ to a completeepistemic state; two well-known approaches are given by systemP and system Z, and also each ranking model of ∆ induces afull inference relation. C-representations are special rankingmodels that obey the principle of conditional indifference.Inductive reasoning using c-representations can be done withrespect to all c-representations, with respect to a subclass of,e.g., minimal c-representations, or with respect to singlec-representations. In this paper, we present and investigateselection strategies for determining single c-representations tobe used for inductive reasoning from belief bases. We developaxioms for specifying characteristics of selection strategies.We illustrate which desirable properties, like syntaxsplitting, are ensured by the axioms, and develop constructionsfor obtaining selection strategies satisfying the axioms.Furthermore, we also present and study the extension of selectionstrategies to c-revisions that follow the principle ofconditional preservation and that have been employed successfullyin various belief change settings.

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