Decision support systems with adaptive reasoning strategies

  • Kerstin Schill
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1337)


The ultimate goal in the development of decision support systems is to reach the competence and flexibility set by the human standard. We present an approach which is aimed at the efficient handling of situations with incomplete and partially inconsistent data. Its static structure is derived from a hierarchical implementation of the Dempster/Shafer Belief theory, which is extended towards a multi-layered representation by a set of hierarchies. The dynamic behavior is controlled by an adaptive strategy which can reduce the specific problems which may arise due to the predetermined strategies like “best hypotheses”, “establish-refinetechniques”, “hypothetic-deductive strategies”. The suggested strategy is based on the principle of maximum information gain and is able to take the complete “activation pattern” of the representation into account. Acting together, both components can provide reasonable reactions even in ambiguous and ill-defined situations.


Decision Support System Information Gain Data Collection Process Information Increment Belief Theory 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Kerstin Schill
    • 1
  1. 1.Institut für Medizinsche PsychologieLudwig-Maximilians-UniversitätMünchen

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