David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Ezio Di Nucci
Jack Alan Reynolds
Learn more about PhilPapers
In [Book Chapter] (1994)
Given that knowledge consists of finite models of an infinitely complex reality, how can we explain that it is still most of the time reliable? Survival in a variable environment requires an internal model whose complexity (variety) matches the complexity of the environment that is to be controlled. The reduction of the infinite complexity of the sensed environment to a finite map requires a strong mechanism of categorization. A measure of cognitive complexity (C) is defined, which quantifies the average amount of trial-and-error needed to find the adequate category. C can be minimized by "probability ordering" of the possible categories, where the most probable alternatives ("defaults") are explored first. The reduction of complexity by such ordering requires a low statistical entropy for the cognized environment. This entropy is automatically kept down by the natural selection of "fit" configurations. The high probability, "default" cognitive categorizations are then merely mappings of environmentally "fit" configurations.
|Keywords||No keywords specified (fix it)|
|Categories||categorize this paper)|
Setup an account with your affiliations in order to access resources via your University's proxy server
Configure custom proxy (use this if your affiliation does not provide a proxy)
|Through your library|
References found in this work BETA
No references found.
Citations of this work BETA
No citations found.
Similar books and articles
Guy van Orden & Damian G. Stephen (2012). Is Cognitive Science Usefully Cast as Complexity Science? Topics in Cognitive Science 4 (1):3-6.
James W. McAllister (2003). Effective Complexity as a Measure of Information Content. Philosophy of Science 70 (2):302-307.
Douglas Frye & Philip David Zelazo (1998). Complexity: From Formal Analysis to Final Action. Behavioral and Brain Sciences 21 (6):836-837.
John Bickle (2001). Understanding Neural Complexity: A Role for Reduction. [REVIEW] Minds and Machines 11 (4):467-481.
Georg Schulze & Shuji Mori (1993). Increases in Environmental Entropy Demand Evolution. Acta Biotheoretica 41 (3):149-164.
William P. Bechtel (2001). The Compatibility of Complex Systems and Reduction: A Case Analysis of Memory Research. [REVIEW] Minds and Machines 11 (4):483-502.
Jari Talja (1983). On the Complexity-Relativized Strong Reducibilites. Studia Logica 42 (2-3):259 - 267.
Peter Jedlicka (2007). Physical Complexity and Cognitive Evolution. In Carlos Gershenson, Diederik Aerts & Bruce Edmonds (eds.), Worldviews, Science, and Us: Philosophy and Complexity. World Scientific 221--231.
Added to index2009-01-28
Total downloads6 ( #461,743 of 1,796,321 )
Recent downloads (6 months)1 ( #468,135 of 1,796,321 )
How can I increase my downloads?