The spiral discovery method: An interpretable tuning model for CogInfoCom channels

Adam Csapo, Péter Baranyi

Research output: Contribution to journalArticle

18 Citations (Scopus)


Cognitive Infocommunications (CogInfoCom) messages that are used to carry information on the state of the same high-level concept can be regarded as belonging to a CogInfoCom channel. Such channels can be generated using any kind of parametric model. By changing the values of the parameters, it is possible to arrive at a large variety of CogInfoCom messages, a subset of which can belong to a CogInfoCom channel -provided they are perceptually well-suited to the purpose of conveying information on the same highlevel concept. Thus, for any CogInfoCom channel, we may speak of a parameter space and a perceptual space that is created by the totality of messages in the CogInfoCom channel. In this paper, we argue that in general, the relationship between the parameter space and the perceptual space is highly non-linear. For this reason, it is extremely difficult for the designer of a CogInfoCom channel to tune the parameters in such a way that the resulting CogInfoCom messages are perceptually continuous, and suitable to carry information on a single high-level concept. To address this problem, we propose a cognitive artifact that uses a rank concept available in tensor algebra to provide the designer of CogInfoCom channels with practical tradeoffs between complexity and interpretability. We refer to the artifact as the Spiral Discovery Method (SDM).

Original languageEnglish
Pages (from-to)358-367
Number of pages10
JournalJournal of Advanced Computational Intelligence and Intelligent Informatics
Issue number2
Publication statusPublished - Mar 2012


  • CogInfoCom channels
  • CogInfoCom messages
  • Cognitive artifacts
  • Cognitive infocommunications

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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