FUZZY DYNAMIC LOGIC

Leonid I. Perlovsky ()
Additional contact information
Leonid I. Perlovsky: Air Force Research Lab., 80 Scott Rd., Hanscom AFB, MA 01731, USA

New Mathematics and Natural Computation (NMNC), 2006, vol. 02, issue 01, 43-55

Abstract: Fuzzy logic is extended toward dynamic adaptation of the degree of fuzziness. The motivation is to explain the process of learning as a joint model improvement and fuzziness reduction. A learning system with fuzzy models is introduced. Initially, the system is in a highly fuzzy state of uncertain knowledge, and it dynamically evolves into a low-fuzzy state of certain knowledge. We present an image recognition example of patterns below clutter. The paper discusses relationships to formal logic, fuzzy logic, complexity and draws tentative connections to Aristotelian theory of forms and working of the mind.

Keywords: Fuzzy logic; complexity; fuzzy dynamic logic; mind; image recognition (search for similar items in EconPapers)
Date: 2006
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S1793005706000300
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:nmncxx:v:02:y:2006:i:01:n:s1793005706000300

Ordering information: This journal article can be ordered from

DOI: 10.1142/S1793005706000300

Access Statistics for this article

New Mathematics and Natural Computation (NMNC) is currently edited by Paul P Wang

More articles in New Mathematics and Natural Computation (NMNC) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().