CTNF 18/280,385 CTNF 101450 Notice of Pre-AIA or AIA Status 07-03-aia AIA 15-10-aia The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA. Claims 1-8 are presented for examination. Information Disclosure Statement 06-52 The information disclosure statement (IDS) submitted on September 5 th , 2023 and September 3 rd , 2024 was filed. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner. Specification 06-11 AIA The title of the invention is not descriptive. A new title is required that is clearly indicative of the invention to which the claims are directed. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 Step 1 : The claim recites an apparatus; therefore, it is directed to the statutory category of machine. Step2A Prong 1 : The claim recites, inter alia: a processing execution process of processing the logical formulas of at least one of the background knowledge information and the query information that have been acquired in the acquisition process, and acquiring processed background knowledge information and processed query information : This limitation is seen as a mental process which involves processing the logical formulas and the query information, which can be performed mentally in the human mind. and an evaluation process of outputting at least one of the processed background knowledge information and the processed query information, depending on whether or not an execution result of the logical inference satisfies a predetermined requirement: This limitation recites a mental process because it involves the determination of whether a result satisfies a condition/requirement. an inference execution process of executing logical inference using, as inputs, the processed background knowledge information and the processed query information : This limitation is viewed as a mental process because it involves solving the logical inference given the background knowledge and the query information, which can be performed by the human mind. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: [a] logical expression processing apparatus comprising at least one processor, the at least one processor carrying out: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)). an acquisition process of acquiring background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : Data Gather- Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: [a] logical expression processing apparatus comprising at least one processor, the at least one processor carrying out: Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and cannot provide inventive concept (MPEP 2106.05(f)). an acquisition process of acquiring background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept. The elements in combination as an ordered whole still do not amount to significantly more than the judicial exception (i.e., the abstract ideas of mental processes for acquiring, processing, and evaluating logical formulas for logical inference). The claim merely describes obtaining background knowledge and query information expressed as logical formulas, processing the formulas, executing logical inference, determining whether the inference result satisfies a requirement, and outputting the result. These steps correspond to logical reasoning that can be performed mentally or with pen and paper, and the recitation of a processor merely implements the abstract idea on a generic computer. Therefore, the claim as a whole remains focused on the abstract idea and fails Step 2B of the eligibility analysis. Claim 2 Step 1 : A process, as above. Step2A Prong 1 : This claim does not recite any abstract ideas but depends on claim 1 which does. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: in the processing execution process, the at least one processor processes, according to each of one or more processing procedures , the logical formulas of at least one of the background knowledge information and the query information that have been acquired in the acquisition process, and acquires, for each of the processing procedures, the processed background knowledge information and the processed query information; in the inference execution process, the at least one processor executes the logical inference for each of the processing procedures, and in the evaluation unit process, the at least one processor outputs, for each of the processing procedures, the at least one of the processed background knowledge information and the processed query information, depending on whether or not the execution result of the logical inference satisfies the predetermined requirement : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: in the processing execution process, the at least one processor processes, according to each of one or more processing procedures , the logical formulas of at least one of the background knowledge information and the query information that have been acquired in the acquisition process, and acquires, for each of the processing procedures, the processed background knowledge information and the processed query information; in the inference execution process, the at least one processor executes the logical inference for each of the processing procedures, and in the evaluation unit process, the at least one processor outputs, for each of the processing procedures, the at least one of the processed background knowledge information and the processed query information, depending on whether or not the execution result of the logical inference satisfies the predetermined requirement : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)). Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible. Claim 3 Step 1 : A process, as above. Step2A Prong 1 : This claim does not recite any abstract ideas, but depends on claim 1 which does. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: wherein the execution result of the logical inference includes a time taken for the logical inference and the predetermined requirement includes a requirement related to the time taken for the logical inference : The limitation merely provides additional information about the data and does not impose any meaningful limit on the judicial exception. It does not integrate the exception into a practical application because it fails to transform or apply the abstract idea in a specific or technological manner. Accordingly, the limitation does not amount to significantly more than the judicial exception (MPEP 2106.05(e)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: wherein the execution result of the logical inference includes a time taken for the logical inference and the predetermined requirement includes a requirement related to the time taken for the logical inference : The limitation merely provides additional information about the data and does not add a meaningful limitation that would amount to significantly more than the judicial exception. Such extra-solution activity or data characterization is insufficient to provide an inventive concept (MPEP 2106.05(e)). Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible. Claim 4 Step 1 : A process, as above. Step2A Prong 1 : This claim does not recite any abstract ideas, but depends on claim 1 which does. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: wherein the predetermined requirement includes a requirement related to an inference result of the logical inference : The limitation merely provides additional information about the data and does not impose any meaningful limit on the judicial exception. It does not integrate the exception into a practical application because it fails to transform or apply the abstract idea in a specific or technological manner. Accordingly, the limitation does not amount to significantly more than the judicial exception (MPEP 2106.05(e)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: wherein the predetermined requirement includes a requirement related to an inference result of the logical inference : The limitation merely provides additional information about the data and does not add a meaningful limitation that would amount to significantly more than the judicial exception. Such extra-solution activity or data characterization is insufficient to provide an inventive concept (MPEP 2106.05(e)). Claim 5 Step 1 : A process, as above. Step2A Prong 1 : The claim recites, inter alia: in the inference execution process… executes the logical inference using, as inputs, the background knowledge information and the query information that have been acquired by in the acquisition process, and acquires a correct answer inference result; and in the evaluation process… compares the correct answer inference result and the inference result of the logical inference using, as the inputs, the processed background knowledge information and the processed query information, and thereby determines whether or not the execution result satisfies the requirement related to the inference result : This limitation is a mental process that involves solving the logical expression (mentally performable), and comparing between the inference result and the correct answer and determining whether the comparison satisfies a requirement. Step 2A Prong Two and Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under step 2B. Thus, the judicial exception is not integrated into a practical application (see MPEP 2106.04(d) I.), failing step 2A prong 2. The claim is ineligible. Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible. Claim 6 Step 1 : A process, as above. Step2A Prong 1 : The claim recites, inter alia: and in the evaluation process… compares the correct answer inference result and the inference result of the logical inference using, as the inputs, the processed background knowledge information and the processed query information, and thereby determines whether or not the execution result satisfies the requirement related to the inference result : This limitation is a mental process that involves comparing between the inference result and the correct answer and determining whether the comparison satisfies a requirement. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: in the acquisition process… further acquires a correct answer inference result : Data Gather- Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: in the acquisition process… further acquires a correct answer inference result : The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept. Even when considered in combination, these additional elements represent mere instructions to apply an exception and therefore do not provide an inventive concept. The claim is ineligible. Claim 7 Step 1 : The claim recites a method; therefore, it is directed to the statutory category of process. Step2A Prong 1 : The claim recites, inter alia: output at least one of the processed background knowledge information and the processed query information, depending on whether or not an execution result of the logical inference satisfies a predetermined requirement : This limitation recites a mental process because it involves the determination of whether a result satisfies a condition/requirement. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: acquire background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)). Insignificant extra-solution as the limitation amounts to necessary data outputting (MPEP 2106.05(g)(3)). execute logical inference using, as inputs, the processed background knowledge information and the processed query information : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: acquire background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept. execute logical inference using, as inputs, the processed background knowledge information and the processed query information : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and cannot provide inventive concept (MPEP 2106.05(f)). The remainder of claim 7 recites identical limitations to claim 1. Therefore, claim 7 is rejected using the same rationale as claim 1. Claim 8 Step 1: The claim recites a non-transitory computer medium; therefore, it is directed to the statutory category of manufacture. Step2A Prong 1 : The claim recites, inter alia: an evaluation process that outputs of outputting at least one of the processed background knowledge information and the processed query information, depending on whether or not an execution result of the logical inference satisfies a predetermined requirement : This limitation recites a mental process because it involves the determination of whether a result satisfies a condition/requirement. Step2A Prong 2 : This judicial exception is not integrated into a practical application because the additional elements are as follows: an acquisition process of acquiring background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : Mere data gathering recited at a high level of generality, and thus are insignificant extra-solution activity (MPEP 2106.05(g)). A non-transitory storage medium in which a logical expression processing program is stored, the logical expression processing program causing a computer to carry out : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea (MPEP 2106.05(f)). Step 2B : The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements are as follows: an acquisition process of acquiring background knowledge information and query information, the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true, the query information expressing one or more observed facts in one or more logical formulas : The additional element of “receiving” does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of receiving steps amounts to no more than mere data gathering. This element amounts to receiving data over a network and are well-understood, routine, conventional activity. See MPEP 2106.05(d), subsection II (i). This cannot provide an inventive concept. A non-transitory storage medium in which a logical expression processing program is stored, the logical expression processing program causing a computer to carry out : Adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and cannot provide inventive concept (MPEP 2106.05(f)). The remainder of claim 8 recites identical limitations to claim 1. Therefore claim 8 is rejected using the same rationale as claim 1. Claim Rejections - 35 USC § 103 07-06 AIA 15-10-15 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. 07-20-aia AIA 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. 07-23-aia AIA 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. 07-20-02-aia AIA This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention. 07-21-aia AIA Claim s 1-2 and 4-8 are rejected under 35 U.S.C. 103 as being unpatentable over Sakama (“Abductive logic programming and disjunctive logic programming: their relationship and transferability”, 1999) in view of Oyama (WO 2021171358 A1). Regarding claim 1, Sakama teaches an acquisition process of acquiring background knowledge information and query information (Page 2 Introduction, “For instance, consider an abduction problem such that a background knowledge has the rules: PNG media_image1.png 52 204 media_image1.png Greyscale …Given the observation wet-grass, abduction produces either rained or sprinkler-on (or both) as a possible explanation.”, Page 7 Section 2.2, “Let Pi = (P, A) be an abductive program and O a ground literal which represents an observation.”, Page 6 Section 2.2 of Sakama, “An abductive program is defined as a pair (P, A) where P is a program and A is a set of literals from the language of P called abducibles...” In the example provided by Sakama, the method first receives the background knowledge rules such as “wet-grass [Wingdings font/0xDF] rained” and “wet-grass [Wingdings font/0xDF] sprinkler-on.” The method also receives the observation “wet-grass”, which represents the query information.) , the background knowledge information expressing, in one or more logical formulas, a set of rules according to each of which if an antecedent is true, a consequent is true (Page 4 Section 2.1, “A program considered in this paper is an extended disjunctive program (EDP) [15] which is a set of rules of the form: PNG media_image2.png 32 570 media_image2.png Greyscale ” The logic programs are sets of rules where the head is true if the body (antecedent) is true. If the items on the right of L_(l+1)… L_m are true, then the consequent is true which is L_1. In Sakama’s example, the rule “wet-grass [Wingdings font/0xDF] rained” shows that if the antecedent (rained) is true, then the consequent (wet-grass) becomes true.) , the query information expressing one or more observed facts in one or more logical formulas (Page 7 Section 2.2, “Let Pi = (P, A) be an abductive program and O a ground literal which represents an observation.” Sakama explains that an observation is represented by a ground literal O. In the example, the observation “wet-grass” is a ground literal that represents the observed fact in the logical formula.) ; a processing execution process of processing the logical formulas of at least one of the background knowledge information and the query information that have been acquired in the acquisition process, and acquiring processed background knowledge information and processed query information (Page 7 Section 2.2, “Let P ˆhP;Ai be an abductive program and O a ground literal which represents an observation… That is, E is a (minimal) explanation of O with respect to hP;Ai i€ S is an (A-minimal) belief set of {P [Union] [Wingdings font/0xDF] not O }, A}”, Page 9 Definition 3.1, “Let P = (P, A) be an AELP. Then the dlp transformation transforms P to the EDP dlp(P), which is obtained from P by introducing the following disjunctive rules for each abducible A ∈ A: PNG media_image3.png 41 77 media_image3.png Greyscale ”, Page 12 Section 4.1, “Given an EDP P, let us consider the set of normal rules PNG media_image4.png 36 578 media_image4.png Greyscale ”, See Example 3.1 on page 10, PNG media_image5.png 160 343 media_image5.png Greyscale Sakana teaches a process execution process where the background knowledge and the query information are processed into forms for logical inference. The background knowledge is represented in the logic program P_1, which is transformed via dlp or ks transformations to produce modified logical rules. The query information (observation O) is processed by incorporating it into the program as seen in the belief set {P [Union] [Wingdings font/0xDF] not O }, A}. In summary, both the background knowledge and the query are jointly processed into transformed logical representation for subsequent inference.) ; an inference execution process of executing logical inference using, as inputs, the processed background knowledge information and the processed query information (Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.”, Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A.” The logical inference is performed on transformed programs using the processed rules and the observation. Sakama performs logical inference to determine which literals could explain the observation of “wet-grass”. In that example, the inference process would determine that “rained” or “sprinkler-on” may explain why the grass is wet.) ; and an evaluation process of outputting at least one of the processed background knowledge information and the processed query information, depending on whether or not an execution result of the logical inference satisfies a predetermined requirement (Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A.”, Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.” Sakama explains that the system generates several possible belief sets through logical inference and then checks each one to see if it actually explains the observation. It looks at whether the observation O is true in a given belief set S. If it is, that belief set is kept and the corresponding abducibles E = S (Intersection) A are returned as explanations. If not, it becomes discarded. For example, in the “wet-grass” case, explanations like “rained” or sprinkler-on” are only returned if they lead to a belief set where “wet-grass” is true.) . Sakama does not teach [a] logical expression processing apparatus comprising at least one processor, the at least one processor carrying out… Oyama, in the same field of endeavor, teaches [a] logical expression processing apparatus comprising at least one processor, the at least one processor carrying out… (Paragraph 2 of Oyama, “Hardware Configuration of Control Device FIG. 2 shows the hardware configuration of the control device 1. The control device 1 includes a processor 11, a memory 12, and an interface 13 as hardware.”, Paragraph 6-3, “Next, the target logical expression generation unit 32 generates the target logical expression Ltag by adding the constraint condition indicated by the constraint condition information I2 to the logical expression indicating the target task.”) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Sakama’s teaching of logical inference with Oyama’s hardware device executing logical expressions in order to execute logical expressions within a hardware component (Paragraph 6-3 of Oyama). Regarding claim 2, Sakama teaches … the logical formulas of at least one of the background knowledge information and the query information that have been acquired in the acquisition process, and acquires, for each of the processing procedures, the processed background knowledge information and the processed query information (Page 9 Definition 3.1, “Let P ˆhP;Ai be an AELP. Then the dlp transformation transforms P to the EDP dlp…P†, which is obtained from P by introducing the following disjunctive rules for each abducible A 2 A: PNG media_image6.png 34 86 media_image6.png Greyscale ”, Page 13 Definition 4.1, “Then the ks-transformation transforms P to the knowledge system ks(P) = (T, H) where T = disj(P) Union IC”) Sakama teaches multiple transformations (dlp and ks transformations) that process the logical formulas of the program P (background knowledge rules) to produce new transformed programs. Each transformation represents a separate processing procedure that generates a processed version of the program. ; in the inference execution process, the at least one processor executes the logical inference for each of the processing procedures ( See Example 3.1 on Page 10, PNG media_image7.png 136 379 media_image7.png Greyscale , Page 12 Example 3.2, “Then, dlp_pm(P) has five possible models: S1 = {epsilon}, S2 = {epsilon, rained, wet-grass, wet-shoes}…” After the transformations of the program occur (dlp or dlppm), logical inference is performed to produce answer sets of the transferred program. The logical inference is executed for each transformed program produced.) ; and in the evaluation unit process, the at least one processor outputs, for each of the processing procedures, the at least one of the processed background knowledge information and the processed query information, depending on whether or not the execution result of the logical inference satisfies the predetermined requirement (Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. ”, Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.” Sakama evaluates the inference results by determining whether a set of abducibles constitutes a valid explanation for the observation O and whether it satisfies the requirement. The result of the abducible is what is compared to the result of the answer set where if the result of the inference is part of the answer set (predetermined requirement), then the inference result is satisfied.) . Sakama does not teach in the processing execution process, the at least one processor processes, according to each of one or more processing procedures… Oyama, in the same field of endeavor, teaches in the processing execution process, the at least one processor processes, according to each of one or more processing procedures… (Paragraph 2 of Oyama, “Hardware Configuration of Control Device FIG. 2 shows the hardware configuration of the control device 1. The control device 1 includes a processor 11, a memory 12, and an interface 13 as hardware.”, Paragraph 6-3, “Next, the target logical expression generation unit 32 generates the target logical expression Ltag by adding the constraint condition indicated by the constraint condition information I2 to the logical expression indicating the target task.”) Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Sakama’s teaching of logical inference with Oyama’s hardware device executing logical expressions in order to execute logical expressions within a hardware component (Paragraph 6-3 of Oyama). Regarding claim 4, Sakama teaches wherein the predetermined requirement includes a requirement related to an inference result of the logical inference (Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. An explanation E of O is minimal if no E0 E is an explanation of O.”, Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.” Sakama evaluates the inference result by determining whether it satisfies the explanation validity. If the observation O becomes true in the belief set, then the requirement is directly based on the inference result which satisfies a requirement of the result corresponding to the observation.). Regarding claim 5, Sakama teaches in the inference execution process… executes the logical inference using, as inputs, the background knowledge information and the query information that have been acquired by in the acquisition process, and acquires a correct answer inference result (Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. An explanation E of O is minimal if no E0 E is an explanation of O.”, Page 7 Example 2.2, “Given the observation O = p(a), O is true in the (A-minimal) belief set S = {p(a), q(a),s(a)} of Pi and E = S (Intersection) A = {s(a)}. Hence, O has the (minimal) explanation E.” Sakama teaches performing abductive logical inference over a program P (background knowledge) and an observation O (query), where belief sets S are computed. Section 2.2 explains that the explanation represents the correct answer inference result because it is the derived explanation that satisfies the observation given the rules.) ; and in the evaluation process, the at least one processor compares the correct answer inference result and the inference result of the logical inference using, as the inputs, the processed background knowledge information and the processed query information (Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S. Conversely, if T is an answer set of dlp(P), there is a belief set S of P such that S = T (Intersection )Lit.”, Page 18 Theorem 6.1, “If S is a possible model of P, there is an answer set T of dlp(alp (P)) such that T (Intersection) Lit = S.” Sakama teaches that the inference outputs (answer sets) can be evaluated against expected results (belief sets) which satisfies the comparison between the correct answer inference result and another inference result.) , and thereby determines whether or not the execution result satisfies the requirement related to the inference result (Page 4 Section 1.4, “…the belief sets of an abductive program are expressed by the answer sets and the possible models of the transformed disjunctive program.”, Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. ” Sakama defines valid explanations based on the validity of the observation O in a belief set S, meaning that only inference results meeting this condition qualify as acceptable.) . Regarding claim 6, Sakama teaches in the acquisition process, the at least one processor further acquires a correct answer inference result (Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. An explanation E of O is minimal if no E0 E is an explanation of O.”, Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.” Sakama teaches acquiring a correct answer inference result by deriving an explanation E = S Intersection A from a belief set S in which the observation holds.) ; and in the evaluation process, the at least one processor compares the correct answer inference result and the inference result of the logical inference using, as the inputs, the processed background knowledge information and the processed query information (Page 9 Theorem 3.1, “If S is a belief set of P, there is an answer set T of dlp(P) such that T ∩ Lit = S.”, Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A.” Sakama teaches comparing inference results by establishing equivalence between belief sets and answer sets, which is the process of evaluating the outputs.) , and thereby determines whether or not the execution result satisfies the requirement related to the inference result (Page 4 Section 1.4, “…the belief sets of an abductive program are expressed by the answer sets and the possible models of the transformed disjunctive program.”, Page 7 Section 2.2, “A set E ( ⊆ A) is an explanation of O (wrt P) if O is true in a belief set S of P such that E = S ∩ A. ” Sakama teaches verifying that the inferred explanation makes the observation true in a belief set.) . Regarding claim 7, Sakama teaches A logical expression processing method, wherein one or more computers is caused to… (Page 2 Section 1.2, “ALP supplies the ability to perform reasoning with hypotheses. It is known that abduction is useful for various AI problems including diagnosis, planning, and theory revision [24]. ALP enables us to use logic programming as an inference engine for solving these abductive problems. On the other hand, DLP provides us with a method of reasoning with indefinite information.”) : The remainder of claim 7 recites identical limitations to claim 1. Therefore, claim 7 should be rejected using the same rationale as claim 1. Regarding claim 8, Sakama teaches [a] non-transitory storage medium in which a logical expression processing program is stored, the logical expression processing program causing a computer to carry out… (Page 1 Section 1.1, “Abduction is a form of commonsense reasoning in artificial intelligence (AI), and early AI systems realize abduction in first-order logic or default reasoning systems…”, Page 20 7.1 Theorem Proof, “Using the transformation, they prove that the set-membership problem in an NDP under the possible model semantics is NP-complete.”). The remainder of claim 8 recites identical limitations to claim 1. Therefore, claim 8 should be rejected using the same rationale as claim 1 . 07-21-aia AIA Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Sakama (“Abductive logic programming and disjunctive logic programming: their relationship and transferability”, 1999) in view of Oyama (WO 2021171358 A1) and Brass (“Transformation-Based Bottom-Up Computation of the Well-Founded Model”, 2000). Regarding claim 3, Sakama does not teach wherein the execution result of the logical inference includes a time taken for the logical inference and the predetermined requirement includes a requirement related to the time taken for the logical inference. Brass, in the same field of endeavor, teaches wherein the execution result of the logical inference includes a time taken for the logical inference and the predetermined requirement includes a requirement related to the time taken for the logical inference (Page 2 Introduction, “The alternating fixpoint procedure is known to have efficiency problems in the sense that it needs quadratic evaluation time for programs that could be easily computed in linear time w.r.t. their size.”, Page 6 Example 5, “Due to the linear character of the graph of dependencies between the atoms p(b1) to p(bn) we would expect that it is possible to compute the well-founded model of this program in linear time w.r.t. n. However, the alternating fixpoint procedure needs n 2 iterations, each deriving a number of facts that is linear in n.”, Page 18 Example 48, “Figure 1 illustrates execution times of the AFP strategy from Example 46 and the optimized remainder strategy from Example 47 for different program sizes n ranging from 100 to 1000. The quadratic and linear character of the two strategies, respectively, is obvious.” Brass teaches the execution result of logical inference includes the time taken, which is a predetermined requirement.) . Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to combine Sakama’s teaching for logical inference processing with Brass’s evaluation of execution time associated with logical programming in order to improve the computational efficiency of time required to perform logical inference (Page 2 Introduction of Brass). Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to MAJD MAHER HADDAD whose telephone number is (571)272-2265. The examiner can normally be reached Mon-Friday 8-5 pm. 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, Kamran Afshar , can be reached at (571) 272-7796. 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. /M.M.H./Examiner, Art Unit 2125 /KAMRAN AFSHAR/Supervisory Patent Examiner, Art Unit 2125 Application/Control Number: 18/280,385 Page 2 Art Unit: 2125 Application/Control Number: 18/280,385 Page 3 Art Unit: 2125 Application/Control Number: 18/280,385 Page 4 Art Unit: 2125 Application/Control Number: 18/280,385 Page 5 Art Unit: 2125 Application/Control Number: 18/280,385 Page 6 Art Unit: 2125 Application/Control Number: 18/280,385 Page 7 Art Unit: 2125 Application/Control Number: 18/280,385 Page 8 Art Unit: 2125 Application/Control Number: 18/280,385 Page 9 Art Unit: 2125 Application/Control Number: 18/280,385 Page 10 Art Unit: 2125 Application/Control Number: 18/280,385 Page 11 Art Unit: 2125 Application/Control Number: 18/280,385 Page 12 Art Unit: 2125 Application/Control Number: 18/280,385 Page 13 Art Unit: 2125 Application/Control Number: 18/280,385 Page 14 Art Unit: 2125 Application/Control Number: 18/280,385 Page 15 Art Unit: 2125 Application/Control Number: 18/280,385 Page 16 Art Unit: 2125 Application/Control Number: 18/280,385 Page 17 Art Unit: 2125 Application/Control Number: 18/280,385 Page 18 Art Unit: 2125 Application/Control Number: 18/280,385 Page 19 Art Unit: 2125 Application/Control Number: 18/280,385 Page 20 Art Unit: 2125 Application/Control Number: 18/280,385 Page 21 Art Unit: 2125 Application/Control Number: 18/280,385 Page 22 Art Unit: 2125 Application/Control Number: 18/280,385 Page 23 Art Unit: 2125 Application/Control Number: 18/280,385 Page 24 Art Unit: 2125 Application/Control Number: 18/280,385 Page 25 Art Unit: 2125 Application/Control Number: 18/280,385 Page 26 Art Unit: 2125
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