Abstraction and Complexity Measures

  • Lorenza Saitta
  • Jean-Daniel Zucker
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4612)


Abstraction is fundamental for both human and artificial reasoning. The word denotes different activities and process, but all are intuitively related to the notion of complexity/simplicity, which is as elusive a notion as abstraction. From an analysis of the literature on abstraction and complexity it clearly appears that it is unrealistic to find definitions valid in all disciplines and for all tasks. Hence, we consider a particular model of abstraction, and try to investigate how complexity measures could be mapped to it. Preliminary results show that abstraction and complexity are not monotonically coupled notions, and that complexity may either increase or decrease with abstraction according to the definition of both and to the specificities of the considered domain.


Turing Machine Complexity Measure Representation Framework Kolmogorov Complexity Ground Color 
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 2007

Authors and Affiliations

  • Lorenza Saitta
    • 1
  • Jean-Daniel Zucker
    • 2
    • 3
  1. 1.Università del Piemonte Orientale, Dipartimento di Informatica, Via Bellini 25/G, AlessandriaItaly
  2. 2.LIM&BIO, EA3502, Univ. Paris 13, 74 rue Marcel Cachin, 93017 BobignyFrance
  3. 3.UR 079 GEODES, IRD, 32 avenue Henri Varagnat, 93143 BondyFrance

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