XInternational Federation for Information Processing

XKnowledge Representation and Reasoning

Knowledge representation and reasoning deal with the theory and applications of languages, tools and methods to describe, in a computer program, specific domains of interest and draw conclusions about them.





In knowledge representation both explicit (classical, modal, fuzzy, and description logics, rules, frames, semantic nets, etc.) and implicit representations (e.g., artificial neural networks, vectorial representations, dynamical systems as representations) as well as hybrid systems are taken into account.

Reasoning methods are a basic underlying component in many areas and systems including expert systems, natural language understanding and robotics. Reasoning includes deduction, abduction and induction and can be based, for instance, on logical inference systems, probabilistic and statistical methods, statistical machine learning, dynamic system models and hybrid systems.

IFIP WG 12.1 also covers the relationship between the development of AI theories and applications and the related disciplines including cognitive science, psychology, sociology, biology, and physics.

WG 12.1 is a part of IFIP TC12.