A Transformation System for Unique Minimal Normal Forms of Conditional Knowledge Bases

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10369)


Conditional knowledge bases consisting of sets of conditionals are used in inductive nonmonotonic reasoning and can represent the defeasible background knowledge of a reasoning agent. For the comparison of the knowledge of different agents, as well as of different approaches to nonmonotonic reasoning, it is beneficial if these knowledge bases are as compact and straightforward as possible. To enable the replacement of a knowledge base \(\mathcal R\) by a simpler, but equivalent knowledge base \(\mathcal R'\), we propose to use the notions of elementwise equivalence or model equivalence for conditional knowledge bases. For elementwise equivalence, we present a terminating and confluent transformation system on conditional knowledge bases yielding a unique normal form for every \(\mathcal R\). We show that an extended version of this transformation system takes model equivalence into account. For both transformation system, we prove that the obtained normal forms are minimal with respect to subset inclusion and the corresponding notion of equivalence.



This work was supported by DFG-Grant KI1413/5-1 to Gabriele Kern-Isberner as part of the priority program “New Frameworks of Rationality” (SPP 1516). Christian Eichhorn is supported by this Grant. We thank the anonymous reviewers for their valuable hints and comments.


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© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceUniversity of HagenHagenGermany
  2. 2.Department of Computer Science, TU DortmundDortmundGermany

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