Accession Number:

AD0610740

Title:

THE STUDY OF MATHEMATICAL MODELS FOR SELF-ORGANIZING SYSTEMS.

Descriptive Note:

Final rept. for 27 Mar 63-8 May 64,

Corporate Author:

PENNSYLVANIA UNIV PHILADELPHIA

Personal Author(s):

• Rubinoff,Morris
• Rosenberg,Aaron
• eliasoff,Amy L.
• White,J. F.
• Korsh,J.

Report Date:

1965-01-01

Pagination or Media Count:

241.0

Abstract:

Emphasis of the work is concentrated on three of the more promising models of self-organizing systems namely, the cellular model, the linear statistical model and the list structure model. The discussion of the cellular model describes experiments in a two-dimensional rectangular space initially containing binary elements. The experiments gave insight into rules of element behavior that lead to stability and pattern formation. The linear statistical predictor provides a method for determining the structures of time-varying systems within a behavioral class. The list structure model began with an examination of state classes and regular expressions. It became clear early in the study that a primary prerequisite was a language suited to description of such a model capable of being programmed on a computer. It was demonstrated that the second-order predicate logic was a suitable language.

Descriptors:

• *ARTIFICIAL INTELLIGENCE
• AUTOMATA
• MATHEMATICAL MODELS
• SIMULATION
• STATISTICAL ANALYSIS
• MATHEMATICAL LOGIC
• BIONICS
• IDENTIFICATION
• TIME
• LINEAR SYSTEMS
• INPUT OUTPUT DEVICES
• CONTROL SYSTEMS

Subject Categories:

Distribution Statement:

APPROVED FOR PUBLIC RELEASE