6 found
Order:
  1.  1
    Handbook of Knowledge Representation.Frank Van Harmelen, Vladimir Lifschitz & Bruce Porter - 2008 - Elsevier.
    Knowledge representation, which lies at the core of artificial intelligence, is concerned with encoding knowledge on computers to enable systems to reason automatically. The aims are to help readers make their computer smarter, handle qualitative and uncertain information, and improve computational tractability.
    No categories
    Direct download  
     
    Export citation  
     
    Bookmark   4 citations  
  2.  7
    Towards the Semantic Web: Ontology-Driven Knowledge Management.John Davies, Dieter Fensel & Frank van Harmelen - 2003 - Wiley.
    With the current changes driven by the expansion of the World Wide Web, this book uses a different approach from other books on the market: it applies ontologies to electronically available information to improve the quality of knowledge management in large and distributed organizations. Ontologies are formal theories supporting knowledge sharing and reuse. They can be used to explicitly represent semantics of semi-structured information. These enable sophisticated automatic support for acquiring, maintaining and accessing information. Methodology and tools are developed for (...)
    Direct download  
     
    Export citation  
     
    Bookmark   3 citations  
  3. Rippling: A Heuristic for Guiding Inductive Proofs.Alan Bundy, Andrew Stevens, Frank van Harmelen, Andrew Ireland & Alan Smaill - 1993 - Artificial Intelligence 62 (2):185-253.
  4. Explanation-Based Generalisation = Partial Evaluation.Frank van Harmelen & Alan Bundy - 1988 - Artificial Intelligence 36 (3):401-412.
  5.  2
    Analyzing Differentiable Fuzzy Logic Operators.Emile van Krieken, Erman Acar & Frank van Harmelen - 2022 - Artificial Intelligence 302:103602.
    Direct download (2 more)  
     
    Export citation  
     
    Bookmark  
  6.  1
    Logic-Based Knowledge Representation.Peter Jackson, Han Reichgelt & Frank Van Harmelen - 1989 - Mit Press.
    This book explores the building of expert systems using logic for knowledge representation and meta-level inference for control. It presents research done by members of the expert systems group of the Department of Artificial Intelligence in Edinburgh, often in collaboration with others, based on two hypotheses: that logic is a suitable knowledge representation language, and that an explicit representation of the control regime of the theorem prover has many advantages. The editors introduce these hypotheses and present the arguments in their (...)
    Direct download  
     
    Export citation  
     
    Bookmark