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Cogent confabulation.

Robert Hecht-Nielsen1

  • 1Computational Neurobiology, Institute for Neural Computation, Electrical and Computer Engineering Department, University of California, San Diego, La Jolla, CA 92093-0407, USA. rh-n@ucsd.edu

Neural Networks : the Official Journal of the International Neural Network Society
|March 30, 2005
PubMed
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A new model of vertebrate cognition, maximization of cogency, generalizes Aristotelian logic. It functions by supporting assumed facts, not just finding probable conclusions, especially in non-Aristotelian environments.

Area of Science:

  • Cognitive Science
  • Logic
  • Vertebrate Cognition

Background:

  • Existing models of cognition often focus on finding the most probable conclusion.
  • Aristotelian logic provides a foundation for logical reasoning in certain information environments.

Purpose of the Study:

  • Introduce a novel model of vertebrate cognition: maximization of cogency p(alphabetagammadelta|epsilon).
  • Demonstrate this model as a generalization of Aristotelian logic.
  • Relate the model to a calculable quantity.

Main Methods:

  • Formalizing a new cognitive model based on maximization of cogency.
  • Analyzing the model's behavior in both Aristotelian and non-Aristotelian information environments.
  • Comparing the model's function to probabilistic approaches and the 'duck test' heuristic.

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Main Results:

  • The maximization of cogency model is a direct generalization of Aristotelian logic.
  • The model is rigorously related to a calculable quantity.
  • In non-Aristotelian environments, the model identifies conclusions most supportive of assumed facts, akin to the 'duck test'.

Conclusions:

  • The proposed cognitive model offers a new framework for understanding vertebrate cognition.
  • This model extends logical principles beyond traditional Aristotelian constraints.
  • Its unique function in non-Aristotelian settings provides a novel perspective on decision-making under uncertainty.