Propagating degrees of truth on an argumentation framework: an abstract account of fuzzy argumentation

This paper proposes a computational framework to reason with conflicting and gradual evidence. The framework is a synthesis of Dung's seminal work in argumentation semantics with multi-valued logic. Abstract grounded semantics is used to identify the conditions under which a conclusion can be accepted, while multi-valued logic operators are used to quantify the degree of truth of such conditions. We propose a truth-compositional recursive computation based on the notion of irrelevant arguments, and we discuss examples using the major multi-valued logics: Godel's, Zadeh's and Łukasiewicz's logic.

[1]  Luca Longo,et al.  A defeasible reasoning framework for human mental workload representation and assessment , 2015, Behav. Inf. Technol..

[2]  Martine De Cock,et al.  Fuzzy Argumentation Frameworks , 2008 .

[3]  Pierpaolo Dondio Multi-Valued and Probabilistic Argumentation Frameworks , 2014, COMMA.

[4]  Henri Prade,et al.  What are fuzzy rules and how to use them , 1996, Fuzzy Sets Syst..

[5]  Luca Longo,et al.  Trust-Based Techniques for Collective Intelligence in Social Search Systems , 2011, Next Generation Data Technologies for Collective Computational Intelligence.

[6]  Pierpaolo Dondio TOWARD A COMPUTATIONAL ANALYSIS OF PROBABILISTIC ARGUMENTATION FRAMEWORKS , 2014, Cybern. Syst..

[7]  Umberto Straccia,et al.  Managing uncertainty and vagueness in description logics for the Semantic Web , 2008, J. Web Semant..

[8]  Nir Oren,et al.  Probabilistic Argumentation Frameworks , 2011, TAFA.

[9]  Luca Longo,et al.  Defeasible Reasoning and Argument-Based Systems in Medical Fields: An Informal Overview , 2014, 2014 IEEE 27th International Symposium on Computer-Based Medical Systems.

[10]  Luca Longo,et al.  Modeling Mental Workload Via Rule-Based Expert System: A Comparison with NASA-TLX and Workload Profile , 2016, AIAI.

[11]  Pierpaolo Dondio Multi-valued Argumentation Frameworks , 2014, RuleML.

[12]  John L. Pollock,et al.  Defeasible reasoning with variable degrees of justification , 2001, Artif. Intell..

[13]  Cayrol Claudette,et al.  Acceptability semantics accounting for strength of attacks in argumentation , 2010, ECAI 2010.

[14]  Phan Minh Dung,et al.  Towards (Probabilistic) Argumentation for Jury-based Dispute Resolution , 2010, COMMA.

[15]  Guillermo Ricardo Simari,et al.  An Abstract Argumentation Framework with Varied-Strength Attacks , 2008, KR.

[16]  Claudette Cayrol,et al.  Dialectical Proofs Accounting for Strength of Attacks in Argumentation Systems , 2010, 2010 22nd IEEE International Conference on Tools with Artificial Intelligence.

[17]  Claudette Cayrol,et al.  Acceptability semantics accounting for strength of attacks in argumentation , 2010, ECAI.

[18]  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..

[19]  Phan Minh Dung,et al.  Assumption-Based Argumentation , 2009, Argumentation in Artificial Intelligence.

[20]  Stephen Barrett,et al.  Presumptive selection of trust evidence , 2007, AAMAS '07.

[21]  Luca Longo,et al.  Computing Trust as a Form of Presumptive Reasoning , 2014, 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT).

[22]  Pierpaolo Dondio Trust as a form of defeasible reasoning , 2008 .

[23]  Michael Wooldridge,et al.  Inconsistency tolerance in weighted argument systems , 2009, AAMAS.

[24]  Matthias Thimm,et al.  A Probabilistic Semantics for abstract Argumentation , 2012, ECAI.

[25]  D. M. Gabbaya Equational approach to argumentation networks , 2012 .

[26]  Didier Dubois,et al.  Gradual properties vs . uncertainty : Fuzzy logic vs . possibilistic logic , 2022 .

[27]  Anthony Hunter,et al.  A probabilistic approach to modelling uncertain logical arguments , 2013, Int. J. Approx. Reason..

[28]  Dov M. Gabbay,et al.  A Logical Account of Formal Argumentation , 2009, Stud Logica.