Information

Scope

We are in the reality of natural and computational systems of argumentation provided by reasoning, with natural and artificial languages. Intelligent systems of argumentation target advanced methods for exchanging, saving, reasoning, accessing, and updating information in memory. The special session on Natural Language and Argumentation (NLA) covers theories and applications. Formal models of argumentation like the Dung framework assume that natural language arguments have properly been mapped to logical formulas or partial proofs. Argument mining, when mainly working with existing machine learning methods, encounters difficulties to properly analyse arguments and relations between arguments, over general data, and especially when natural language expressions involve logical constructions. On the other side, traditional methods map sentences to logical formulas, which can be available after having been handled by a theorem prover. E.g., categorial analyses yield discourse representation structures, by using a parser (like Boxer, or Grail), and theorem provers (e.g., Coq) handle corresponding logical representations. The first two approaches (the Dung framework, and typical argument mining) suffer from the lack of development of the relations between natural language texts and dialogues, and do not handle the logical structure of meanings, while the third one (the predominant, traditional logical approach) is limited by the lack of sophisticated semantic lexicon for encompassing the logical structure carried by some words, and interconnections with other methods.


Topics

We welcome submissions on the following topics, without limiting to them, across approaches, methods, theories, implementations, and applications, in support of argumentation:

  • Formal models of argumentations (e.g., Dung's framework)
  • Logic of preferences
  • Argument mining
  • Theorem provers and assistants
  • Model checkers
  • Theory of computation
  • Theory of information
  • Natural language inference
  • Beliefs, attitudes, persuasions - theories and applications
  • Formal languages in support of reasoning and argumentation
  • Algorithms related to natural language and argumentation - theories, implementations, applications
  • Mapping NL expressions into logical representations
  • Syntactic and semantic analyses of natural language
  • Computational methods to natural language - approaches, theories
  • Computational syntax, semantics, and/or interfaces between them
  • NLP argument mining
  • Ambiguity and underspecification in syntax and semantics
  • Discourse and context dependency
  • Reasoning with ambiguity and underspecification
  • Interactive computation, reasoning, argumentation
  • Computation with heterogeneous information
  • Reasoning with heterogeneous and/or inconsistent information
  • Dialog, interactions
  • Interdisciplinary approaches to language, computation, reasoning, memory, relevant for argumentation
  • Argumentation in AI applications: e.g., to business, economy, justice, health, medical sciences

Committee

Organizing Committee

  • Stergios Chatzikyriakidis - University of Gothenburg (Sweden)
  • Emiliano Lorini - CNRS, IRIT (France)
  • Roussanka Loukanova - Stockholm University (Sweden) - Institute of Mathematics and Informatics, Bulgarian Academy of Sciences (Bulgaria)
  • Richard Moot - LIRMM-CNRS, Montpellier (France)
  • Christian Retoré - Université de Montpellier and LIRMM-CNRS, Montpellier (France)

Contact

Stergios Chatzikyriakidis
stergios.chatzikyriakidis@gu.se

Emiliano Lorini
lorini@irit.fr

Roussanka Loukanova
rloukanova the special symbol gmaildotcom

Richard Moot
richard.moot@lirmm.fr

Christian Retoré
christian.retore@lirmm.fr