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.:

US 8001063 B1

PDF
Full Text
Expired
Date of Patent:
Aug. 16, 2011

Filed:

Jun. 30, 2008
Applicants:

Gerald James Tesauro, Croton-on-Hudson, NY (US);

Rajarshi Das, New Rochelle, NY (US);

Nicholas K. Jong, Bridgewater, NJ (US);

Jeffrey O. Kephart, Cortlandt Manor, NY (US);

Inventors:

Gerald James Tesauro, Croton-on-Hudson, NY (US);

Rajarshi Das, New Rochelle, NY (US);

Nicholas K. Jong, Bridgewater, NJ (US);

Jeffrey O. Kephart, Cortlandt Manor, NY (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 15/18 (2006.01);
U.S. Cl.
CPC ...
Abstract

In one embodiment, the present invention is a method for reward-based learning of improved systems management policies. One embodiment of the inventive method involves obtaining a decision-making entity and a reward mechanism. The decision-making entity manages a plurality of application environments supported by a data processing system, where each application environment operates on data input to the data processing system. The reward mechanism generates numerical measures of value responsive to actions performed in states of the application environments. The decision-making entity and the reward mechanism are applied to the application environments, and results achieved through this application are processed in accordance with reward-based learning to derive a policy. The reward mechanism and the policy are then applied to the application environments, and the results of this application are processed in accordance with reward-based learning to derive a new policy.


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