DISTRIBUTED HIERARCHICAL EVOLUTIONARY MODELING AND VISUALIZATION OF EMPIRICAL DATA

Patent №

US 6,941,287

Granted

2005-09-06

Filed 1999

Owner

E. I. DU PONT DE NEMOURS AND COMPANY

Lab

AI components

5

ml · kr · planning · evo · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09466041

A distributed hierarchical evolutionary modeling and visualization of empirical data method and machine readable storage medium for creating an empirical modeling system based upon previously acquired data. The data represents inputs to the systems and corresponding outputs from the system. The method and machine readable storage medium utilize an entropy function based upon information theory and the principles of thermodynamics to accurately predict system outputs from subsequently acquired inputs. The method and machine readable storage medium identify the most information-rich (i.e., optimum) representation of a data set in order to reveal the underlying order, or structure, of what appears to be a disordered system. Evolutionary programming is one method utilized for identifying the optimum representation of data.

AI classification

Machine learning1.00
Planning1.00
Knowledge representation1.00
AI hardware0.99
Evolutionary computation0.99
Vision0.09
Natural language0.01
Speech0.00

Ownership

E. I. DU PONT DE NEMOURS AND COMPANY

assignment · 106250026

Assignors

VAIDYANATHAN, AKHILESWAR GANESH, OWENS, AARON JAMES, WHITCOMB, JAMES ARTHUR, VAIDYANATHAN, AKHILESWAR GANESH, OWENS, AARON JAMES, WHITCOMB, JAMES ARTHUR

On an employer assignment, the assignors are typically the inventors.

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