Compilation of static and evolving conditional knowledge bases for computing induced nonmonotonic inference relations

2019 ◽  
Vol 87 (1-2) ◽  
pp. 5-41 ◽  
Author(s):  
Christoph Beierle ◽  
Steven Kutsch ◽  
Kai Sauerwald
Keyword(s):  
Knowledge Bases ◽  
Conditional Knowledge ◽  
Nonmonotonic Inference

scholarly journals A Complete Map of Conditional Knowledge Bases in Different Normal Forms and Their Induced System P Inference Relations Over Small Signatures

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Christoph Beierle ◽  
Jonas Haldimann ◽  
Steven Kutsch
Keyword(s):  
Normal Form ◽  
Normal Forms ◽  
Knowledge Bases ◽  
Predominant Role ◽  
New Normal ◽  
Conditional Knowledge ◽  
System P

Conditional knowledge bases consisting of qualitativeconditionals play a predominant role in knowledge representationand reasoning. In this paper, we develop a full map of allconsistent conditional knowledge bases over a small signature indifferent normal forms. We introduce two new normal formsthat take the induced system P inference relation into account,the system P normal form (SPNF) and the renaming SPNF(ρSPNF) considering additionally renamings of theunderlying signature. For a two-element signature, we systematicallygenerate and compare all consistent knowledge bases in ANF,RANF, SPNF, and their renaming counterparts, as well as allcomplete system P inference relations induced by conditionalknowledge bases.

scholarly journals InfOCF-Web: An Online Tool for Nonmonotonic Reasoning with Conditionals and Ranking Functions

2021 ◽  
Author(s):  
Steven Kutsch ◽  
Christoph Beierle
Keyword(s):  
Nonmonotonic Reasoning ◽  
Minimal Models ◽  
Ranking Functions ◽  
Online Tool ◽  
Ranking Models ◽  
Conditional Knowledge ◽  
System P ◽  
Nonmonotonic Inference

InfOCF-Web provides implementations of system P and system Z inference, and of inference relations based on c-representation with respect to various inference modes and different classes of minimal models. It has an easy-to-use online interface for computing ranking models of a conditional knowledge R, and for answering queries and comparing inference results of nonmonotonic inference relations induced by R.

Syntax Splitting = Relevance + Independence: New Postulates for Nonmonotonic Reasoning From Conditional Belief Bases

2020 ◽  
Author(s):  
Gabriele Kern-Isberner ◽  
Christoph Beierle ◽  
Gerhard Brewka
Keyword(s):  
Knowledge Base ◽  
Belief Revision ◽  
Inductive Inference ◽  
Nonmonotonic Reasoning ◽  
Irrelevant Information ◽  
Knowledge Bases ◽  
P System ◽  
Conditional Belief ◽  
Conditional Knowledge ◽  
System P

Syntax splitting, first introduced by Parikh in 1999, is a natural and desirable property of KR systems. Syntax splitting combines two aspects: it requires that the outcome of a certain epistemic operation should only depend on relevant parts of the underlying knowledge base, where relevance is given a syntactic interpretation (relevance). It also requires that strengthening antecedents by irrelevant information should have no influence on the obtained conclusions (independence). In the context of belief revision the study of syntax splitting already proved useful and led to numerous new insights. In this paper we analyse syntax splitting in a different setting, namely nonmonotonic reasoning based on conditional knowledge bases. More precisely, we analyse inductive inference operators which, like system P, system Z, or the more recent c-inference, generate an inference relation from a conditional knowledge base. We axiomatize the two aforementioned aspects of syntax splitting, relevance and independence, as properties of such inductive inference operators. Our main results show that system P and system Z, whilst satisfying relevance, fail to satisfy independence. C-inference, in contrast, turns out to satisfy both relevance and independence and thus fully complies with syntax splitting.

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