DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
This action is in response to the application filed on 01/06/2022. Claims 1-20 are pending in the application and have been considered below.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding Claim 1:
For Step 1, the claim is a method so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “computing (i.e. calculating) a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “computing (i.e. calculating) a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: “receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy” and “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.”
The recited "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The recited “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
Step 2B
Under the Subject Matter Eligibility, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 2:
Claim 2, which incorporates the rejection of claim 1, recites further limitations such as “
input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 3:
Claim 3, which incorporates the rejection of claim 1, recites further limitations such as
“an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 4:
Claim 4, which incorporates the rejection of claim 1, recites further limitations such as
“computing (i.e. calculating) a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 5:
Claim 5, which incorporates the rejection of claim 1, recites further limitations such as
“taking a Cartesian product of the intermediate explanations” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 6:
Claim 6, which incorporates the rejection of claim 1, recites further limitations such as
“ensuring that non-modifiable characteristics of the input case keep their values from the input case” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 7:
Claim 7, which incorporates the rejection of claim 1, recites further limitations such as
“the decision nodes represent intermediate and final results of the hierarchical rule-based decision policy” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 8:
For Step 1, the claim is a computer program product so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “computing (i.e. calculating) a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “computing (i.e. calculating) a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: computer readable storage media, processors, “receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy” and “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.”
The processors are recited at a high level of generality, i.e., as generic processors performing a generic computer function of processing data. These generic processors’ limitation is no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f).
The “computer readable storage media” “is a generic computer component that amounts to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The recited "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The recited “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The additional elements “computer readable storage media and processors”
do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Step 2B
Here the "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “computer readable storage media and processors” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 9:
Claim 9, which incorporates the rejection of claim 8, recites further additional elements:
“stored program instructions are stored in a computer readable storage device in a data processing system,” and “stored program instructions are transferred over a network from a remote data processing system.”
The recited “stored program instructions are stored in a computer readable storage device in a data processing system” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The “computer readable storage device,” “data processing system” and “remote data processing system” are generic computer components that amount to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The recited “stored program instructions are transferred over a network from a remote data processing system step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The additional element “computer readable storage device,” “data processing system” and “remote data processing system” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Here the “stored program instructions are stored” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(g)). This appears to be well-understood, routine, conventional as evidenced by Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93.
Here the “stored program instructions are transferred over a network” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “computer readable storage device,” “data processing system” and “remote data processing system” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 10:
Claim 6, which incorporates the rejection of claim 1, recites further limitations such as
“program instructions to meter use of the program instructions associated with the request; and program instructions to generate an invoice based on the metered use” that are part of the abstract idea. (MPEP 2106.04(a)(2)(III)(C)).
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 11:
Claim 11, which incorporates the rejection of claim 8, recites further limitations such as
dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy” that are part of the abstract idea. (MPEP 2106.04(a)(2)(III)(C)).
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 12:
Claim 12, which incorporates the rejection of claim 8, recites further limitations such as
“an intermediate explanation for a first decision node that is a conjunction of range
constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 13:
Claim 13, which incorporates the rejection of claim 8, recites further limitations such as
“computing (i.e. calculating) a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first
intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 14:
Claim 14, which incorporates the rejection of claim 8, recites further limitations such as
“taking a Cartesian product of the intermediate explanations” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 15:
Claim 15, which incorporates the rejection of claim 8, recites further limitations such as
“ensuring that non-modifiable characteristics of the input case keep their values from the input case” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 16:
Claim 16, which incorporates the rejection of claim 8, recites further limitations such as
decision nodes represent intermediate and final results of the hierarchical rule-based decision policy” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 17:
For Step 1, the claim is a computer system so it does recite a statutory category of invention.
For Step 2A, Prong 1:
The claim recites the limitation of “computing (i.e. calculating) a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
The claim recites the limitation of “computing (i.e. calculating) a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations.” The computing imitation, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is nothing in the claim precludes the computing step from practically being performed in the human mind. This limitation is a mental process. (MPEP 2106.04(a)(2)(III)(C)).
For Step 2A, Prong 2, the claim recites additional elements: computer system, computer readable storage media, processors, “receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy” and “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.”
The processors are recited at a high level of generality, i.e., as generic processors performing a generic computer function of processing data. These generic processors’ limitation is no more than mere instructions to apply the exception using a generic computer component. See MPEP 2106.05(f).
The “computer system and computer readable storage media” are generic computer components that amount to mere instructions to apply the abstract idea. See MPEP 2106.05(f).
The recited "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The recited “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step is a form of insignificant extra-solution activity. See MPEP 2106.05(g).
The additional elements “computer system, computer readable storage media and processors” do not amount to significantly more for the reasons set forth in step 2A above.
Additionally, under the 2019 PEG, a conclusion that an additional element is insignificant extra-solution activity in Step 2A should be reevaluated in Step 2B.
Step 2B
Here the "receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
Here the “transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation” step was considered to be extra-solution activity in Step 2A, and thus it is reevaluated in Step 2B to determine if it is more than what is well-understood, routine, conventional activity in the field. The addition of insignificant extra-solution activity does not amount to an inventive concept, particularly when the activity is well-understood or conventional (MPEP 2106.05(d)). This appears to be well-understood, routine, conventional as evidenced by MPEP 2106.05(d)(II)(i).
i. Receiving or transmitting data over a network, e.g., using the Internet to gather data”.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “computer system, computer readable storage media and processors” to perform the claim steps amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claim is not patent eligible.
Regarding Claim 18:
Claim 18, which incorporates the rejection of claim 17, recites further limitations such as “input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 19:
Claim 19, which incorporates the rejection of claim 17, recites further limitations such as
“an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Regarding Claim 20:
Claim 20, which incorporates the rejection of claim 17, recites further limitations such as
“computing (i.e. calculating) a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph” that are part of the abstract idea.
There are no additional elements recited in this claim that amount to an integration of the judicial exception into a practical application or significantly more than the judicial exception. Therefore, the claim is not eligible.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3-4, 6-9, 12, 15-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable Abadi et al. (US 2018/0121315 A1, hereinafter referred to as Abadi) in view of Agarini et al. (US 2019/0156225 A1, hereinafter referred to as Agarini).
As to claim 1, Abadi teaches a computer implemented method comprising:
receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy (paragraphs [0057]-[0059] Optionally, the system monitors traffic activities between the server and the client terminal. The system
identifies rule violation by a traffic activity. Rules may be business or enterprise rules such as what type of requests the system allows for an application operated by certain users, which type of accesses to data bases, servers or other system resources are allowed from different types of networks. A rule may define that access to secured data bases are allowed only through the enterprise local area network (LAN), but not allowed through wireless networks like wireless LAN (WLAN) network or Bluetooth (BT) or other wireless networks. When the system identifies a violation of a rule (interpreted by Examiner as undesired outputs), it conducts a corrective action. A corrective action may be blocking accesses to the network by the client terminal monitored for access requests of the type violated the rule The corrective action may be applying a new application configuration to the application such that the new configuration prevents generating requests (interpreted by Examiner as an alternative desired output). for the traffic activities identified as violating the rules; [0062], The present invention provides the ability to identify broken dependencies and violations of data assignments (interpreted by Examiner as undesired outputs) as described above, thus verifying that a new configuration of application that is applied is valid and correct. When the configuration is identified as including broken dependencies or unassigned variables, notification is produced. This is a feature of the present invention that provides a significant improvement to the functionality and performance of the client terminal, as invalid states of the executed application are prevented, and the execution of the application is not interrupted, stalled or generates undesired outputs; [0074]-[0077] The graph includes, for example, nodes and directive connectors connecting
between nodes. Each node represents a source code segment responsible for an application's functionality. Each directive connector connects between two source code segments representing the execution flow from one of the source code segments to the other. The execution of the source code).
However, Abadi fails to explicitly teach
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy;
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations; and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.
Agarini, in combination with Abadi, teaches:
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy (paragraphs [0063] Firstly, all rules to be analyzed need to contribute
to the same intermediate decision. Hence, the policymaker (or analyst) needs to conduct a dedicated rule analysis for each intermediate decision. At each step of this process, the policymaker has to select all relevant rules for the current decision. Secondly, the policymaker has to provide a description of the intermediate cases, which means the information that is available when the intermediate decision is made. Thirdly, the policymaker has to provide a definition of the intermediate decision and describe the possible options that may be chosen for making the decision. Given all this information about the intermediate cases and intermediate decisions, existing rule analysis methods will be able to generate missing rules for making the considered piece of the decision policy complete and arbitration rules for making this piece consistent. [0066]-[0068] For example, the policymaker may state that the discount depends on two intermediate decisions (interpreted by Examiner as intermediate explanation), namely a number of fidelity points of the customer and the product family. Each product may belong to a clearly defined product family, meaning that the decision of the product family only depends on the product and not on the other attributes (interpreted by Examiner as intermediate explanation));
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well); and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation (paragraphs [0083] For this purpose, decision domain detection component
170 analyzes the action of each rule and checks whether this action may make the given decision. If yes, the rule is included in a list of rules that are making the decision.
If no, the rule is irrelevant and not included in this list. At 906, ruleset application modeler 172 then builds a rule application constraint graph for each relevant rule to
describe that the rule condition is satisfied and a second one that states that the action has been applied. For example, this can be illustrated by a rule that attributes 50 fidelity points if the category is Bronze and the promotional period is false.
The rule can be more clearly stated as: if the category is Bronze and the promotional period is false, then set the number of fidelity points to 50. The condition of this rule is
satisfied if the category is Bronze and the promotional period is false. This can be directly formulated in a constraint language that has comparison and Boolean constraints. The action of the rule has been applied if the number of fidelity points is 50).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 3, which incorporates the rejection of claim 1, Abadi fails to explicitly teach
wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node.
Agarini, in combination with Abadi, teaches wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 4, which incorporates the rejection of claim 1, Abadi fails to explicitly teach
wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph.
Agarini, in combination with Abadi, teaches wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph (paragraph [0003] Other pieces aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions. Each piece of the decision policy may
be represented by several rules as described before, but those rules inspect only a subset of the attributes or intermediate decisions and their actions are limited to the intermediate decision of the considered piece).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 6, which incorporates the rejection of claim 1, Abadi fails to explicitly teach wherein the aggregating of the intermediate explanations comprises ensuring that non-modifiable characteristics of the input case keep their values from the input case.
Agarini, in combination with Abadi, teaches wherein the aggregating of the intermediate explanations comprises ensuring that non-modifiable characteristics of the input case keep their values from the input case (paragraph [0068], the policymaker may state that the discount depends on two intermediate decisions (interpreted by Examiner as non-modifiable characteristics), namely a number of fidelity points of the customer and the product family.
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 7, which incorporates the rejection of claim 1, Abadi fails to explicitly teach wherein the decision nodes represent intermediate and final results of the hierarchical rule-based decision policy.
Agarini, in combination with Abadi, teaches wherein the decision nodes represent intermediate and final results of the hierarchical rule-based decision policy (paragraph [0003] Other pieces aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision (interpreted by Examiner as final result) is aggregated from lower-lever decisions. Each piece of the decision policy may be represented by several rules as described before, but those rules inspect only a subset of the attributes or intermediate decisions and their actions are limited to the intermediate decision of the considered piece).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 8, Abadi teaches a computer program product, the computer program product comprising one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by one or more processors (paragraph [0022] processor) to cause the one or more processors to perform operations comprising:
receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy (paragraphs [0057]-[0059] Optionally, the system monitors traffic activities between the server and the client terminal. The system
identifies rule violation by a traffic activity. Rules may be business or enterprise rules such as what type of requests the system allows for an application operated by certain users, which type of accesses to data bases, servers or other system resources are allowed from different types of networks. A rule may define that access to secured data bases are allowed only through the enterprise local area network (LAN), but not allowed through wireless networks like wireless LAN (WLAN) network or Bluetooth (BT) or other wireless networks. When the system identifies a violation of a rule (interpreted by Examiner as undesired outputs), it conducts a corrective action. A corrective action may be blocking accesses to the network by the client terminal monitored for access requests of the type violated the rule The corrective action may be applying a new application configuration to the application such that the new configuration prevents generating requests (interpreted by Examiner as an alternative desired output). for the traffic activities identified as violating the rules; [0062], The present invention provides the ability to identify broken dependencies and violations of data assignments (interpreted by Examiner as undesired outputs) as described above, thus verifying that a new configuration of application that is applied is valid and correct. When the configuration is identified as including broken dependencies or unassigned variables, notification is produced. This is a feature of the present invention that provides a significant improvement to the functionality and performance of the client terminal, as invalid states of the executed application are prevented, and the execution of the application is not interrupted, stalled or generates undesired outputs; [0074]-[0077] The graph includes, for example, nodes and directive connectors connecting
between nodes. Each node represents a source code segment responsible for an application's functionality. Each directive connector connects between two source code segments representing the execution flow from one of the source code segments to the other. The execution of the source code).
However, Abadi fails to explicitly teach
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy;
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations; and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.
Agarini, in combination with Abadi, teaches:
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy (paragraphs [0063] Firstly, all rules to be analyzed need to contribute
to the same intermediate decision. Hence, the policymaker (or analyst) needs to conduct a dedicated rule analysis for each intermediate decision. At each step of this process, the policymaker has to select all relevant rules for the current decision. Secondly, the policymaker has to provide a description of the intermediate cases, which means the information that is available when the intermediate decision is made. Thirdly, the policymaker has to provide a definition of the intermediate decision and describe the possible options that may be chosen for making the decision. Given all this information about the intermediate cases and intermediate decisions, existing rule analysis methods will be able to generate missing rules for making the considered piece of the decision policy complete and arbitration rules for making this piece consistent. [0066]-[0068] For example, the policymaker may state that the discount depends on two intermediate decisions (interpreted by Examiner as intermediate explanation), namely a number of fidelity points of the customer and the product family. Each product may belong to a clearly defined product family, meaning that the decision of the product family only depends on the product and not on the other attributes (interpreted by Examiner as intermediate explanation));
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well); and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation (paragraphs [0083] For this purpose, decision domain detection component
170 analyzes the action of each rule and checks whether this action may make the given decision. If yes, the rule is included in a list of rules that are making the decision.
If no, the rule is irrelevant and not included in this list. At 906, ruleset application modeler 172 then builds a rule application constraint graph for each relevant rule to
describe that the rule condition is satisfied and a second one that states that the action has been applied. For example, this can be illustrated by a rule that attributes 50 fidelity points if the category is Bronze and the promotional period is false.
The rule can be more clearly stated as: if the category is Bronze and the promotional period is false, then set the number of fidelity points to 50. The condition of this rule is
satisfied if the category is Bronze and the promotional period is false. This can be directly formulated in a constraint language that has comparison and Boolean constraints. The action of the rule has been applied if the number of fidelity points is 50).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 9, which incorporates the rejection of claim 8, Abadi teaches wherein the stored program instructions are stored in a computer readable storage device in a data processing system, and wherein the stored program instructions are transferred over a network from a remote data processing system (paragraph [0067] The computer readable program instructions may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server).
As to claim 12, which incorporates the rejection of claim 8, Abadi fails to explicitly teach
wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node.
Agarini, in combination with Abadi, teaches wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 13, which incorporates the rejection of claim 8, Abadi fails to explicitly teach wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph.
Agarini, in combination with Abadi, teaches wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph (paragraph [0003] Other pieces aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions. Each piece of the decision policy may
be represented by several rules as described before, but those rules inspect only a subset of the attributes or intermediate decisions and their actions are limited to the intermediate decision of the considered piece).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 15, which incorporates the rejection of claim 8, Abadi fails to explicitly teach
wherein the aggregating of the intermediate explanations comprises ensuring that non-modifiable characteristics of the input case keep their values from the input case.
Agarini, in combination with Abadi, teaches wherein the aggregating of the intermediate explanations comprises ensuring that non-modifiable characteristics of the input case keep their values from the input case (paragraph [0068], the policymaker may state that the discount depends on two intermediate decisions (interpreted by Examiner as non-modifiable characteristics), namely a number of fidelity points of the customer and the product family.
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 16, which incorporates the rejection of claim 8, Abadi fails to explicitly teach
wherein the decision nodes represent intermediate and final results of the hierarchical rule-based decision policy.
Agarini, in combination with Abadi, teaches wherein the decision nodes represent intermediate and final results of the hierarchical rule-based decision policy (paragraph [0003] Other pieces aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision (interpreted by Examiner as final result) is aggregated from lower-lever decisions. Each piece of the decision policy may be represented by several rules as described before, but those rules inspect only a subset of the attributes or intermediate decisions and their actions are limited to the intermediate decision of the considered piece).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 17, Abadi teaches a computer system comprising one or more processors and one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the program instructions executable by the one or more processors (paragraph [0022] processor) to cause the one or more processors to perform operations comprising:
receiving an explanation request that includes an undesired output resulting from an input case of a hierarchical rule-based decision policy specified by an acyclic dependency graph, and further includes an alternative desired output from the hierarchical rule-based decision policy (paragraphs [0057]-[0059] Optionally, the system monitors traffic activities between the server and the client terminal. The system
identifies rule violation by a traffic activity. Rules may be business or enterprise rules such as what type of requests the system allows for an application operated by certain users, which type of accesses to data bases, servers or other system resources are allowed from different types of networks. A rule may define that access to secured data bases are allowed only through the enterprise local area network (LAN), but not allowed through wireless networks like wireless LAN (WLAN) network or Bluetooth (BT) or other wireless networks. When the system identifies a violation of a rule (interpreted by Examiner as undesired outputs), it conducts a corrective action. A corrective action may be blocking accesses to the network by the client terminal monitored for access requests of the type violated the rule The corrective action may be applying a new application configuration to the application such that the new configuration prevents generating requests (interpreted by Examiner as an alternative desired output). for the traffic activities identified as violating the rules; [0062], The present invention provides the ability to identify broken dependencies and violations of data assignments (interpreted by Examiner as undesired outputs) as described above, thus verifying that a new configuration of application that is applied is valid and correct. When the configuration is identified as including broken dependencies or unassigned variables, notification is produced. This is a feature of the present invention that provides a significant improvement to the functionality and performance of the client terminal, as invalid states of the executed application are prevented, and the execution of the application is not interrupted, stalled or generates undesired outputs; [0074]-[0077] The graph includes, for example, nodes and directive connectors connecting
between nodes. Each node represents a source code segment responsible for an application's functionality. Each directive connector connects between two source code segments representing the execution flow from one of the source code segments to the other. The execution of the source code).
However, Abadi fails to explicitly teach
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy;
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations; and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation.
Agarini, in combination with Abadi, teaches:
computing a network of intermediate explanations for required ranges of respective decision nodes that achieve the desired output from the hierarchical rule-based decision policy (paragraphs [0063] Firstly, all rules to be analyzed need to contribute to the same intermediate decision. Hence, the policymaker (or analyst) needs to conduct a dedicated rule analysis for each intermediate decision. At each step of this process, the policymaker has to select all relevant rules for the current decision. Secondly, the policymaker has to provide a description of the intermediate cases, which means the information that is available when the intermediate decision is made. Thirdly, the policymaker has to provide a definition of the intermediate decision and describe the possible options that may be chosen for making the decision. Given all this information about the intermediate cases and intermediate decisions, existing rule analysis methods will be able to generate missing rules for making the considered piece of the decision policy complete and arbitration rules for making this piece consistent. [0066]-[0068] For example, the policymaker may state that the discount depends on two intermediate decisions (interpreted by Examiner as intermediate explanation), namely a number of fidelity points of the customer and the product family. Each product may belong to a clearly defined product family, meaning that the decision of the product family only depends on the product and not on the other attributes (interpreted by Examiner as intermediate explanation));
computing a user-facing explanation that includes a range constraint for achieving the desired output by aggregating the intermediate explanations (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well); and
transmitting, as a response to the explanation request, an explanation for achieving the desired output from the hierarchical rule-based decision policy based on the user-facing explanation (paragraphs [0083] For this purpose, decision domain detection component
170 analyzes the action of each rule and checks whether this action may make the given decision. If yes, the rule is included in a list of rules that are making the decision.
If no, the rule is irrelevant and not included in this list. At 906, ruleset application modeler 172 then builds a rule application constraint graph for each relevant rule to
describe that the rule condition is satisfied and a second one that states that the action has been applied. For example, this can be illustrated by a rule that attributes 50 fidelity points if the category is Bronze and the promotional period is false.
The rule can be more clearly stated as: if the category is Bronze and the promotional period is false, then set the number of fidelity points to 50. The condition of this rule is
satisfied if the category is Bronze and the promotional period is false. This can be directly formulated in a constraint language that has comparison and Boolean constraints. The action of the rule has been applied if the number of fidelity points is 50).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 19, which incorporates the rejection of claim 17, Abadi fails to explicitly teach wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node.
Agarini, in combination with Abadi, teaches wherein the network of intermediate explanations comprises an intermediate explanation for a first decision node that is a conjunction of range constraints for the first decision node and range constraints for a second decision node that directly precedes the first decision node (paragraphs [0081], the rules may make a decision by assigning a value to an attribute. The domain of this
decision should therefore contain all values such that there exists some rule that assigns this value and that is applicable supposing that lower-level decisions have values that belong to their reduced domains. These values can be determined by
modeling the rule behavior in form of constraint graphs and by leveraging known constraint solving techniques as it will be described below. Other embodiments may involve more complex forms of making decisions, e.g., by aggregating values resulting from applying multiple rules. Whereas those embodiments may require more complex forms of constraint graphs, the overall approach for computing reduced domains can be used for these more complex decisions as well).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
As to claim 20, which incorporates the rejection of claim 17, Abadi fails to explicitly teach wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph.
Agarini, in combination with Abadi, teaches wherein computing of the network of intermediate explanations comprises computing a first intermediate explanation for an output node of the acyclic dependency graph and generating refined intermediate explanations of the first intermediate explanation for respective intermediate decision nodes from the output node to an input node of the acyclic dependency graph (paragraph [0003] Other pieces aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions. Each piece of the decision policy may
be represented by several rules as described before, but those rules inspect only a subset of the attributes or intermediate decisions and their actions are limited to the intermediate decision of the considered piece).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the system of Abadi to add intermediate explanations system as taught by Agarini above. The modification would have been obvious because one of ordinary skill would be motivated to aggregate information from first-level decisions into decisions of a second level and this process may be repeated until the final decision is aggregated from lower-lever decisions, as suggested by Agarini (paragraph [0003]).
Claims 2, 11, 18 are rejected under 35 U.S.C. 103 as being unpatentable Abadi et al. (US 2018/0121315 A1, hereinafter referred to as Abadi) in view of Agarini et al. (US 2019/0156225 A1, hereinafter referred to as Agarini), and further in view of BAR-OR et al. (US 2009/0063515 A1, hereinafter referred to as BAR-OR).
As to claim 2, which incorporates the rejection of claim 1, Abadi and Agarini fail to explicitly teach wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy.
BAR-OR, in combination with Abadi and Agarini, teaches wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy (paragraphs [0065] analyzing the dependencies carried by a set of vector nodes of the hierarchical data 160 in an input schema 170….; [0077] suppose an input vector contains data nodes that are sorted on keys. The nodes contain those keys and also a variety of other integer values).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add input data nodes to the combination system of Abadi and Agarini, as taught by BAR-OR above. The modification would have been obvious because one of ordinary skill would be motivated to analyze the dependencies carried by vector nodes, as suggested by BAR-OR (paragraph [0065]).
As to claim 11, which incorporates the rejection of claim 8, Abadi and Agarini fail to explicitly teach wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy.
BAR-OR, in combination with Abadi and Agarini, teaches wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy (paragraphs [0065] analyzing the dependencies carried by a set of vector nodes of the hierarchical data 160 in an input schema 170….; [0077] suppose an input vector contains data nodes that are sorted on keys. The nodes contain those keys and also a variety of other integer values).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add input data nodes to the combination system of Abadi and Agarini, as taught by BAR-OR above. The modification would have been obvious because one of ordinary skill would be motivated to analyze the dependencies carried by vector nodes, as suggested by BAR-OR (paragraph [0065]).
As to claim 18, which incorporates the rejection of claim 17, Abadi and Agarini fail to explicitly teach wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy.
BAR-OR, in combination with Abadi and Agarini, teaches wherein the dependency graph comprises input data nodes describing the input case and a plurality of decision nodes describing respective rules of the hierarchical rule-based policy (paragraphs [0065] analyzing the dependencies carried by a set of vector nodes of the hierarchical data 160 in an input schema 170….; [0077] suppose an input vector contains data nodes that are sorted on keys. The nodes contain those keys and also a variety of other integer values).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add input data nodes to the combination system of Abadi and Agarini, as taught by BAR-OR above. The modification would have been obvious because one of ordinary skill would be motivated to analyze the dependencies carried by vector nodes, as suggested by BAR-OR (paragraph [0065]).
Claim 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable Abadi et al. (US 2018/0121315 A1, hereinafter referred to as Abadi) in view of Agarini et al. (US 2019/0156225 A1, hereinafter referred to as Agarini), and further in view of Tzoref et al. (US 2009/0276379 A1, hereinafter referred to as Tzoref).
As to claim 5, which incorporates the rejection of claim 1, Abadi and Agarini fail to explicitly teach wherein the aggregating of the intermediate explanations comprises taking a Cartesian product of the intermediate explanations.
Tzoref, in combination with Abadi and Agarini, teaches wherein the aggregating of the intermediate explanations comprises taking a Cartesian product of the intermediate explanations (paragraphs [0054] The nodes of the decision tree are the input attributes, the leaves of the tree is the output attribute, and the outgoing edges of a node are marked with the corresponding attribute's values. If more than one output attribute exists, the output is the Cartesian product of all output attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add a Cartesian product to the combination system of Abadi and Agarini, as taught by Tzoref above. The modification would have been obvious because one of ordinary skill would be motivated to figure out the best order of explanation, as suggested by Tzoref (paragraph [0054]).
As to claim 14, which incorporates the rejection of claim 1, Abadi and Agarini fail to explicitly teach wherein the aggregating of the intermediate explanations comprises taking a Cartesian product of the intermediate explanations.
Tzoref, in combination with Abadi and Agarini, teaches wherein the aggregating of the intermediate explanations comprises taking a Cartesian product of the intermediate explanations (paragraphs [0054] The nodes of the decision tree are the input attributes, the leaves of the tree is the output attribute, and the outgoing edges of a node are marked with the corresponding attribute's values. If more than one output attribute exists, the output is the Cartesian product of all output attributes).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add a Cartesian product to the combination system of Abadi and Agarini, as taught by Tzoref above. The modification would have been obvious because one of ordinary skill would be motivated to figure out the best order of explanation, as suggested by Tzoref (paragraph [0054]).
Claim 10 is rejected under 35 U.S.C. 103 as being unpatentable Abadi et al. (US 2018/0121315 A1, hereinafter referred to as Abadi) in view of Agarini et al. (US 2019/0156225 A1, hereinafter referred to as Agarini), and further in view of DiMascio et al. (US 2018/0121972 A1, hereinafter referred to as DiMascio).
As to claim 10, which incorporates the rejection of claim 8, Abadi and Agarini fail to explicitly teach wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising: program instructions to meter use of the program instructions associated with the request; and program instructions to generate an invoice based on the metered use.
DiMascio, in combination with Abadi and Agarini, teaches wherein the stored program instructions are stored in a computer readable storage device in a server data processing system, and wherein the stored program instructions are downloaded in response to a request over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system, further comprising: program instructions to meter use of the program instructions associated with the request; and program instructions to generate an invoice based on the metered use (paragraph [0034], generates an invoice based on the user interaction data. At user preconfigured intervals, the direct payment program 110A, 110B may generate an invoice based on the stored user interaction data for each content creator. When generating the invoice, the direct payment program 110A, 110B may prompt the user to specify the amount of funds to be disbursed to content creators).
It would have been obvious to one of ordinary skill in the art before the effective filing of the claimed invention to modify the combination system of Abadi and Agarini to add a generated invoice to the combination system of Abadi and Agarini, as taught by DiMascio above. The modification would have been obvious because one of ordinary skill would be motivated to improve the technical field of payment systems, as suggested by Tzoref (paragraph [0013]).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Patents and patent related publications are cited in the Notice of References Cited (Form PTO-892) attached to this action to further show the state of the art with respect to the invention.
Sandepudi et al. (US 2020/0387835 A1) teaches a method for identifying and suggesting data classification rules using machine learning classifiers, involves accessing a machine learning classifier having multiple decision trees by a computer system.
Dalli et al. (US 2022/0114417 A1) teaches a system for providing explanations and interpretations for creating explanations in different human, has abductive logic system diagnoses observed effect to identify cause of observed effect and recommendations have course of action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ABABACAR SECK whose telephone number is (571)270-7146. The examiner can normally be reached Monday-Friday 8:00 A.M.-6:00 P.M..
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lamardo Viker can be reached at 5712705871. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/ABABACAR SECK/Examiner, Art Unit 2147
/VIKER A LAMARDO/Supervisory Patent Examiner, Art Unit 2147
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