The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 23, 1996
Filed:
Aug. 04, 1994
Karl P Sims, Somerville, MA (US);
Thinking Machines Corporation, Bedford, MA (US);
Abstract
A system processes directed graphs, each directed graph comprising a plurality of nodes interconnected by arrows defining a relationship among the nodes, each node defining a selected attribute. The system comprises an initial population means, a subsequent generation population generating means, and a competition simulation means. The initial population means provides an initial population of directed graphs that comprises an initial current generation during an initial iteration. The subsequent generation population generating means generates, in response to selected ones of the directed graphs in each of a plurality of current generations, modified directed graphs for use generation during a subsequent iteration. The competition simulation means performs a processing operation in connection with attributes of the nodes of the graphs to simulate a competition among the current generation of directed graphs in connection with a selected goal, to develop the ranking information for use by the subsequent generation population generating means. The operations of the initial population means, the subsequent generation population generating means and the competition simulation means are controlled through a series of iterations. In the successive iterations, the performance of the graphs in response to the selected goal is anticipated to improve, since the population of graphs for each iteration is based on the graphs determined to have the best fitness during the previous iteration.