Analyzing Conflicts with Concept-Based Learning

  • Boris A. Galitsky
  • Sergei O. Kuznetsov
  • Mikhail V. Samokhin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3596)


A machine learning technique for handling scenarios of interaction between conflicting agents is suggested. Scenarios are represented by directed graphs with labeled vertices (for mental actions) and arcs (for temporal and causal relationships between these actions and their parameters). The relation between mental actions and their descriptions gives rise to a concept lattice. Classification of an undetermined scenario is realized by comparing partial matchings of its graph with graphs of positive and negative examples. Developed scenario representation and comparative analysis techniques are applied to the classification of textual customer complaints.


Multiagent System Mental Action Concept Lattice Situation Calculus Mental Entity 
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 2005

Authors and Affiliations

  • Boris A. Galitsky
    • 1
  • Sergei O. Kuznetsov
    • 2
  • Mikhail V. Samokhin
    • 2
  1. 1.School of Computer Science and Information Systems, Birkbeck CollegeUniversity of LondonLondonUK
  2. 2.All-Russian Institute for Scientific and Technical Information (VINITI)MoscowRussia

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