Revision of Defeasible Logic Preferences

There are several contexts of non-monotonic reasoning where a priority between rules is established whose purpose is preventing conflicts. One formalism that has been widely employed for non-monotonic reasoning is the sceptical one known as Defeasible Logic. In Defeasible Logic the tool used for conflict resolution is a preference relation between rules, that establishes the priority among them. In this paper we investigate how to modify such a preference relation in a defeasible logic theory in order to change the conclusions of the theory itself. We argue that the approach we adopt is applicable to legal reasoning where users, in general, cannot change facts or rules, but can propose their preferences about the relative strength of the rules. We provide a comprehensive study of the possible combinatorial cases and we identify and analyse the cases where the revision process is successful. After this analysis, we identify three revision/update operators and study them against the AGM postulates for belief revision operators, to discover that only a part of these postulates are satisfied by the three operators.

[1]  Guido Governatori,et al.  Changing legal systems: legal abrogations and annulments in Defeasible Logic , 2010, Log. J. IGPL.

[2]  Michael J. Maher Under consideration for publication in Theory and Practice of Logic Programming 1 Propositional Defeasible Logic has Linear Complexity , 2004 .

[3]  James P. Delgrande A program-level approach to revising logic programs under the answer set semantics , 2010, Theory Pract. Log. Program..

[4]  Guido Governatori,et al.  Rules and Norms: Requirements for Rule Interchange Languages in the Legal Domain , 2009, RuleML.

[5]  Michael J. Maher,et al.  Argumentation Semantics for Defeasible Logic , 2004, J. Log. Comput..

[6]  Guido Governatori,et al.  A defeasible logic for modelling policy-based intentions and motivational attitudes , 2009, Log. J. IGPL.

[7]  Michael J. Maher,et al.  Embedding defeasible logic into logic programming , 2006, Theory Pract. Log. Program..

[8]  Dirk Vermeir,et al.  Defeasible logics , 1998 .

[9]  Donald Nute,et al.  Defeasible Logic , 1994, INAP.

[10]  Krzysztof R. Apt,et al.  Logic Programming , 1990, Handbook of Theoretical Computer Science, Volume B: Formal Models and Sematics.

[11]  Guido Boella,et al.  A Logical Understanding of Legal Interpretation , 2010, KR.

[12]  Guido Governatori On the relationship between Carneades and Defeasible Logic , 2011, ICAIL.

[13]  Guido Governatori,et al.  Superiority Based Revision of Defeasible Theories , 2010, RuleML.

[14]  Michael J. Maher,et al.  Defeasible Logic versus Logic Programming without Negation as Failure , 2000, J. Log. Program..

[15]  Ivo Düntsch A Microcomputer Based System for Small Relation Algebras , 1994, J. Symb. Comput..

[16]  Theo Tryfonas,et al.  Frontiers in Artificial Intelligence and Applications , 2009 .

[17]  Grigoris Antoniou Defeasible logic with dynamic priorities , 2002, NMR.

[18]  P G rdenfors,et al.  Knowledge in flux: modeling the dynamics of epistemic states , 1988 .

[19]  Michael J. Maher,et al.  Representation results for defeasible logic , 2000, TOCL.

[20]  Guido Boella,et al.  Lex Minus Dixit Quam Voluit, Lex Magis Dixit Quam Voluit: A Formal Study on Legal Compliance and Interpretation , 2009, AICOL Workshops.

[21]  Catherine Legg Ontologies on the Semantic Web , 2007 .

[22]  Phan Minh Dung,et al.  On the Acceptability of Arguments and its Fundamental Role in Nonmonotonic Reasoning, Logic Programming and n-Person Games , 1995, Artif. Intell..

[23]  Guillermo Ricardo Simari,et al.  Argument Theory Change Applied to Defeasible Logic Programming , 2008, AAAI.

[24]  Hirofumi Katsuno,et al.  Propositional Knowledge Base Revision and Minimal Change , 1991, Artif. Intell..

[25]  Ioannis P. Vlahavas,et al.  A Defeasible Logic Reasoner for the Semantic Web , 2004, Int. J. Semantic Web Inf. Syst..

[26]  Michael J. Maher,et al.  A Family of Defeasible Reasoning Logics and its Implementation , 2000, ECAI.

[27]  N. Given,et al.  Hierarchical Argumentation , 2022 .

[28]  Phan Minh Dung,et al.  An Argumentation Semantics for Logic Programming with Explicit Negation , 1993, ICLP.

[29]  I. Levi Subjunctives, dispositions and chances , 1977, Synthese.

[30]  Peter Gärdenfors,et al.  Knowledge in Flux: Modeling the Dynamics of Epistemic States , 2008 .

[31]  A Jurisprudential Model,et al.  Legal Reasoning , 2008 .

[32]  Matteo Cristani,et al.  Many-Sorted Preference Relations , 2002, International Conference on Principles of Knowledge Representation and Reasoning.

[33]  Peter Gärdenfors,et al.  On the logic of theory change: Partial meet contraction and revision functions , 1985, Journal of Symbolic Logic.

[34]  Stefan Woltran,et al.  AGM-Style Belief Revision of Logic Programs under Answer Set Semantics , 2008, LPNMR.

[35]  Grigoris Antoniou,et al.  DR-Prolog: A System for Defeasible Reasoning with Rules and Ontologies on the Semantic Web , 2007, IEEE Transactions on Knowledge and Data Engineering.

[36]  Guido Governatori,et al.  The Making of SPINdle , 2009, RuleML.

[37]  Gerhard Brewka Well-Founded Semantics for Extended Logic Programs with Dynamic Preferences , 1996, J. Artif. Intell. Res..

[38]  Chiaki Sakama,et al.  Abducing Priorities to Derive Intended Conclusions , 1999, IJCAI.

[39]  Matteo Cristani,et al.  The complexity of constraint satisfaction problems for small relation algebras , 2004, Artif. Intell..

[40]  Henry Prakken,et al.  Argument-Based Extended Logic Programming with Defeasible Priorities , 1997, J. Appl. Non Class. Logics.