February 10 – 15 , 2019, Dagstuhl Perspectives Workshop 19072

The Role of Non-monotonic Reasoning in Future Development of Artificial Intelligence


Anthony Hunter (University College London, GB)
Gabriele Kern-Isberner (TU Dortmund, DE)
Thomas Meyer (University of Cape Town, ZA)
Renata Wassermann (University of Sao Paulo, BR)

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Nonmonotonic reasoning (NMR) addresses a fundamental problem that classical-logical methods in computer science encounter when modelling real-world problems: New information may not only extend previously held knowledge (this would correspond to a monotonic extension) but can drastically change knowledge in that conclusions turn out to be wrong and need to be replaced by alternative conclusions. Nonmonotonic phenomena are present in all areas of our everyday lives mostly due to uncertain and incomplete information, but also due to humans reasoning with restricted resources only; on the other hand, humans do very well in determining relevant contexts of reasoning, so reasoning from only incomplete information may well be on purpose and for sake of efficiency. Nowadays, with computer systems being part of nearly all areas of our lives, the need for computational intelligence to be able to also reason in a nonmonotonic way becomes more and more urgent.

The international Nonmononotonic Reasoning (NMR) workshops have provided a premier specialized forum for researchers in non-monotonic reasoning and related areas since 1984. Over the years, NMR topics and results have been disseminated broadly in many different areas such as answer set programming, computational models of argument, and description logics for ontologies. However, research on core topics of NMR has been scattered across different subcommunities that no longer collaborate in depth on a regular base. As a consequence, much time and effort for solving specific, but in principle similar problems is wasted, general relevance of proposed solutions is overlooked, and general methodological competence is no longer developed on the same level of quality as ten years ago.

This Perspectives Workshop will bring together researchers both from core topics and peripheral areas of NMR, but also attract researchers from other scientific domains in which recent developments have shown an increased relevance of NMR topics, encompassing researchers from various communities within computer science and engineering (e.g., artificial intelligence, classical and non-classical logics, machine learning, agent and multiagent systems), as well as from other disciplines like philosophy and psychology. The workshop will be relevant for artificial intelligence in general: For AI to progress from pattern recognition and machine learning to broader cognitive reasoning, it needs to have common sense reasoning, and this in turn calls for a deeper understanding of NMR. So this workshop is about identifying how NMR can be useful for future AI, and how NMR can be developed for those requirements. The goal of this workshop is to reshape NMR as a core methodology for artificial intelligence being able to meet present and future challenges. For this, we will identify research questions which are central to different areas, clarify their connections to NMR, and develop new perspectives for NMR research. Moreover, the workshop will foster collaborations between researchers from different subcommunities to concentrate efforts for solving basic NMR problems, and to disseminate NMR solutions to other areas.

  Creative Commons BY 3.0 DE
  Anthony Hunter, Gabriele Kern-Isberner, Thomas Meyer, and Renata Wassermann


  • Artificial Intelligence / Robotics
  • Semantics / Formal Methods
  • Verification / Logic


  • Nonmonotonic and defeasible reasoning
  • Commonsense reasoning
  • Default and plausible reasoning
  • Conditional reasoning
  • Probabilistic and uncertain reasoning


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