Evidential reasoning system and method
First Claim
1. A computerized method for making decisions based on evidential reasoning, said method comprising:
- providing a model structure including a plurality of processing nodes, each of said processing nodes coupled to receive a set of inputs to supply a respective output;
evaluating a respective attribute assigned to each of the plurality of processing nodes;
specifying a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise known information;
statistically emulating a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise unknown information;
processing said known and said unknown information at said processing nodes to generate the outputs; and
combining the outputs supplied by said processing nodes to reach a decision that emulates expert data.
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Abstract
Computerized method and system for making decisions based on evidential reasoning are provided. The method allows for providing a model structure; including a plurality of processing nodes. Each of the processing nodes is coupled to receive a set of inputs to supply a respective output. The method further allows for evaluating a respective attribute assigned to each of the plurality of processing nodes. A number of possible linguistic evidential values is specified for each of the attributes, wherein some of the evidential values comprise unknown information. A combining step allows for combining the outputs from the processing nodes to reach a decision even in the presence of unknown information.
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Citations
20 Claims
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1. A computerized method for making decisions based on evidential reasoning, said method comprising:
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providing a model structure including a plurality of processing nodes, each of said processing nodes coupled to receive a set of inputs to supply a respective output;
evaluating a respective attribute assigned to each of the plurality of processing nodes;
specifying a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise known information;
statistically emulating a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise unknown information;
processing said known and said unknown information at said processing nodes to generate the outputs; and
combining the outputs supplied by said processing nodes to reach a decision that emulates expert data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A computerized method for making decisions based on evidential reasoning, said decisions used for risk and credit analysis of financial service applications, said method comprising:
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providing a hierarchical model structure for performing risk and credit analysis of financial service applications, said model structure including at least one input layer of processing nodes, said model further including an output layer having a processing node coupled to each of the processing nodes in the input layer;
evaluating a respective attribute indicative of a risk factor assigned to each of the plurality of processing nodes;
specifying a number of possible linguistic evidential values for each of said attributes and wherein said evidential values comprise known financial information;
statistically emulating a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise unknown financial information;
processing said known and said unknown information at said processing nodes to generate the outputs; and
combining the outputs supplied by said processing nodes to reach a decision regarding a given financial service application that emulates expert data, wherein said expert data is collected during a learning stage from a plurality of examples for each of the processing nodes, each of the plurality of examples having a set of inputs, including some indicative of unknown financial information, and a corresponding output indicative of an expert opinion. - View Dependent Claims (13, 14, 15, 16)
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17. A computer-readable medium encoded with computer program code for making decisions based on evidential reasoning, said decisions used for risk and credit analysis of financial service applications, the program code causing a computer to execute a method comprising:
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running a hierarchical model structure for performing risk and credit analysis of financial service applications, said model structure including at least one input layer of processing nodes, said model further including an output layer having a processing node coupled to each of the processing nodes in the input layer;
evaluating a receptive attribute indicative of a risk factor assigned to each of the plurality of processing nodes;
specifying a number of possible linguistic evidential values for each of said attributes and wherein said evidential values comprise known financial information;
statistically emulating a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise unknown financial information;
processing said known and said unknown information at said processing nodes to generate the outputs; and
combining the outputs supplied by said processing nodes to reach a decision regarding a given financial service application that emulates expert data, wherein said expert data is collected during a learning stage from a plurality of examples for each of the processing nodes, each of the plurality of examples having a set of inputs, including some indicative of unknown financial information, and a corresponding output indicative of an expert opinion, said model structure configured to provide a plurality of non-overlapping intervals over its possible output space, said model structure being further configured to optimize separation between any adjacent intervals of said possible output space so that its final output unambiguously maps into a single interval of said output space. - View Dependent Claims (18, 19)
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20. A computerized system for making decisions based on evidential reasoning, said decisions used for risk and credit analysis of financial service applications, said system comprising:
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memory configured to store a hierarchical model structure for performing risk and credit analysis of financial service applications, said model structure including at least one input layer of processing nodes, said model further including an output layer having a processing node coupled to each of the processing nodes in the input layer;
an evaluator module configured to evaluate a respective attribute indicative of a risk factor assigned to each of the plurality of processing nodes;
a data entry module configured to specify a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise known financial information, and statistically emulate a number of possible linguistic evidential values for each of said attributes, wherein said evidential values comprise unknown financial information; and
a processor configured to process said known and said unknown information at said processing nodes to generate outputs and combine the outputs supplied by said processing nodes to reach a decision regarding a given financial service application that emulates expert data, wherein said expert data is collected during a learning stage from a plurality of examples for each of the processing nodes, each of the plurality of examples having a set of inputs, including some indicative of unknown financial information, and a corresponding output indicative of an expert opinion.
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Specification