Data processing: artificial intelligence – Knowledge processing system – Creation or modification
Reexamination Certificate
2000-10-18
2003-10-07
Davis, George B. (Department: 2121)
Data processing: artificial intelligence
Knowledge processing system
Creation or modification
C706S021000, C706S047000
Reexamination Certificate
active
06631362
ABSTRACT:
FIELD OF THE INVENTION
This invention relates to methods and systems that assist users in evaluating multiple alternatives and decision-making based on this evaluation.
BACKGROUND OF THE INVENTION
Based on a natural model of team deliberation, a system that enables team decision support has been developed. This is the result of over fifteen years of studying and modeling design engineers and the integration of research results from the fields of negotiation and argumentation modeling, design rationale capture, decision theoretics, and engineering best practices. The method underlying the system integrates concepts such as criteria development, value modeling, argumentation, negotiation and evaluation into the engineering design workflow.
Patents in the field of general decision support are not common. U.S. Pat. No. 5,182,793 to Alexander et al., entitled “Computer-Aided Decision Making With A Symbolic Spreadsheet,” issued Jan. 26, 1993, and U.S. Pat. No. 6,012,051 to Sammon Jr. et al., entitled “Consumer Profiling System With Analytic Decision Processor,” issued Jan. 4, 2000, both use other methods to support decision-makers.
Accordingly, a need remains for a way to assign semantic meaning to documents without requiring user involvement, and for a way to search for documents with content similar to a given document.
SUMMARY OF THE INVENTION
One aspect of this invention is a method for aiding individuals or teams in making a decision that requires selecting from a list of alternatives. The method is applicable to any problem that has: known or discoverable boundaries; many potentially acceptable alternatives for solving the problem; criteria that can be developed to measure how well the alternatives solve the problem; one or more decision-makers that have a stake in the solution of the problem; decision-makers with expertise in different areas and may represent different, even conflicting viewpoints; and all decision-makers must be interested in solving the problem.
Features of the method allow for analytical support even when information about the alternatives is incomplete or conflicting and when the decision-makers have different opinions about what features of the alternatives are important. Information describing the evaluation can be both quantitative and qualitative and can be changing as more is learned about the problem. Results from the analysis are measures of each alternative's satisfaction, its probability of being the best choice, decision-maker consensus and a sensitivity analysis tailored to give guidance about what to do next to refine the decision.
Technical advantages of this system are that it supports human decision-makers by enhancing their natural behavior. It helps them organize information and encourages sound decision-making skills. Further, it provides an analytical basis for decision-making that is transparent and can be used with no need for analysis by the decision-makers. The results help the decision-makers by giving them a strategy to resolve issues. Often, if a problem is not being resolved, the only action is frustration. The methods help get problems unstuck by giving cost/benefit information so they can rationally decide what to do next to reach a decision.
The input, evaluation, and resulting information serve as a medium to communicate what is important to other team members. The largest single problem in teamwork is poor communication. The method and system presented give a framework for decision-making communication. The representation and analysis also helps the team develop a common understanding of issues and alternative solutions. Further it provides documentation of the decision and the rationale for it.
The foregoing and other features, objects, and advantages of the invention will become more readily apparent from the following detailed description, which proceeds with reference to the accompanying drawings.
REFERENCES:
patent: 5182793 (1993-01-01), Alexander et al.
patent: 5870730 (1999-02-01), Furuya et al.
patent: 5999923 (1999-12-01), Kowalski et al.
patent: 6012051 (2000-01-01), Sammon Jr. et al.
patent: 6389406 (2002-05-01), Reed et al.
patent: 2002/0107824 (2002-08-01), Ahmed
Balasubramanian et al, “A Systematic Approach to Support the Idea Generation Phase of the Interface Design Process”, IEEE Proc. 31st Annual Hawaii International Conference on System Sciences, 1998.*
Derald Herling and David G. Ullman, “Engineering Decision Support System (EDSS),” 1995, pp. 619-626.
David G. Ullman and Derald Herling, “Computer Support for Design Team Decisions,” Lancaster Workshop on AI System Support for Conceptual Design, Mar. 1995, pp. 1-13.
D. G. Ullman and B. D'Ambrosio; “An Introduction to the Consensus Model of Engineering Design Decision Making”; ASME 1998 Proceeding of the Design Theory and Methodolgy Conference; Sep. 1998; Atlanta, GA; there are no page numbers as the proceeding is on CD (14 pages).
David G. Ullman, Derald Herling and Bruce D'Ambrosio; “What to Do Next: Using Problem Status to Determine the Course of Action”;Research in Engineering Design 1997; pp. 214-227.
David G. Ullman; “The Mechanical Design Process”; McGraw-Hill Companies 1997; pp. 152-172.
Lucienne T.M. Blessing; “A Process-Based Approach to Computer-Supported Engineering Design”; Black Bear Press Ltd., Cambridge, Great Britain 1994; p. 182.
Bruce D'Ambrosio; “Local Expression Languages for Probabilistic Dependence”;International Journal of Approximate Reasoning; Elsevier Science, Inc., New York, New York; 1994; pp. 1-16.
David G. Ullman, Thomas G. Dietterich and Larry A. Stauffer; “A Model of the Mechanical Design Process Based on Empirical Data”;Artificial Intelligence for Engineering Design, Analysis and Manufacturing; vol. 2, Issue 1; 1988; pp. 33-52.
Larry A. Stauffer & David G. Ullman; “Fundamental Processes of Mechanical Designers Based on Empirical Data”;Journal of Engineering Design; vol. 2; No. 2; 1991; pp. 113-125.
Yakemovic & Conklin; Report on a Development Project Use of an Issue Based Information System; Technical Report STP279-90; MCC; Jun. 1990; 18 pages.
Yakemovic & Conklin; The Capture of Design Rationale on an Industrial Development Project; Preliminary Report; Technical Report STP279-89; MCC; Jul. 1989; 14 pages.
D'Ambrosio Bruce D.
Ullman David G.
Davis George B.
Marger & Johnson & McCollom, P.C.
Robust Decisions
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