Introduction to Knowledge Representation: Space, Time, Events

This course gives an introduction to the area of knowledge representation, a sub-discipline of computer science in general and artificial intelligence in particular.

Knowledge representation is involved with identifying means to represent practical problems and according background knowledge as data structures, and to develop reasoning algorithms to solve these problems. 

This course puts a spotlight on symbolic techniques to represent knowledge involving a spatio-temporal component as is typical for most practical real-world problems. In particular, we will consider qualitative representations and according constraint-based reasoning techniques. Symbolic approaches like qualitative representations are particularly interesting as they are well-suited to designing knowledge-based systems, while they also connect to formal methods in computer science, allowing for an rigorous analysis. 

contents:

  • fundamental concepts: knowledge, abstractions, relations, logics
  • syntax and semantics, formalization of knowledge
  • representation and reasoning
  • qualitative algebras
  • constraint-based reasoning
  • qualitative constraint calculi
  • complexity and tractable subclasses

organisation: module SME-STE-M, 6 ECTS, lecture and tutorials

courses: 

  • winter term 2017/2018 (lecture Tue, 12–14 WE5/02.020, tutorials Wed 10–12 WE5/05.017.; please sign in at VC!)
  • winter term 2016/2017 (lecture Tue, 12–14 WE5/04.003, tutorials Wed 10–12 and 12–14 WE5/05.017; please sign in at VC!)
  • winter term 2015/2016 (lecture Tue, 12-14 WE5/04.003, tutorials Wed 14-16 WE5/05.017); please sign in at VC
  • winter term 2014/2015 (lecture Wed., 10–12 WE 05.004, tutorials to be decided), please sign in at VC (the VC course is named "Wissen über Raum, Zeit, Ereignisse") !
  • winter term 2013/2014, please sign in at VC!