How much information should we drop to become intelligent?

Ophir Nave, Yair Neuman, Leonid Perlovsky, Newton Howard

Research output: Contribution to journalArticlepeer-review


Cognitive processing by intelligent systems involves the deletion of information in favor of higher level abstractions. This process can be addressed through the physics of computation but a formal model that explains this process has not been proposed yet. In this short paper, we propose a model that through physical constraints only generates optimal solution to the collapse of n objects into n sets. A numerical simulation of the model results in a logarithmic function of information loss and condensation that perfectly fits our knowledge of cognitive processes.

Original languageEnglish
Pages (from-to)261-264
Number of pages4
JournalApplied Mathematics and Computation
StatePublished - 19 Aug 2014


  • Cognition and physics
  • Entropy
  • Interdisciplinary research
  • Set partition

ASJC Scopus subject areas

  • Computational Mathematics
  • Applied Mathematics


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