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 .
This action is in response to the application and claims filed 9/05/2023. Claims 1-8 are pending and have been examined. Claims 1-8 are rejected.
Priority
Applicant’s claim for the benefit of a prior-filed application under 35 U.S.C. 119(e) or under 35 U.S.C. 120, 121, 365(c), or 386(c) is acknowledged. The present application claims foreign priority based on Japanese Patent Application No. JP2022-152020 filed 09/23/2022
The examiner acknowledges that a certified copy (in Japanese) of Japanese application number JP2022-152020 has been retrieved (on 10/03/2023) as required by 37 CFR 1.55.
Information Disclosure Statement
Acknowledgment is made of the information disclosure statement filed 9/05/2023, which complies with 37 CFR 1.97. As such, the information disclosure statement has been placed in the application file and the information referred to therein has been considered by the examiner.
Drawings
The drawings are objected to as failing to comply with 37 CFR 1.84(p)(5) because they include the following reference character not mentioned in the description:
S3 in FIG. 5 (see, e.g., pages 27-28 describing FIG. 5).
Corrected drawing sheets in compliance with 37 CFR 1.121(d), or amendment to the specification to add the reference character(s) in the description in compliance with 37 CFR 1.121(b) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required:
Claims 5 and 7 do not appear to have support in the originally filed specification. There does not appear to be any discussion of any “recording medium” or recording media. The specification fails to mention, let alone describe or discuss any “recording medium with an aircraft control program making a computer execute” as recited in claim 5 or any “recording medium” as recited in claim 7. Appropriate correction is required.
On page 1 in the “BACKGROUND” section of the specification, references are referred to. The listing of references in the specification is not a proper information disclosure statement. 37 CFR 1.98(b) requires a list of all patents, publications, or other information submitted for consideration by the Office, and MPEP § 609.04(a) states, "the list may not be incorporated into the specification but must be submitted in a separate paper." Therefore, unless the references have been cited by the examiner on form PTO-892, they have not been considered. It is noted, however, that applicant appears to have furnished citations to and copies of the references where appropriate (i.e., for the foreign references “Japanese Patent Application Publication JP H11-015807A and Japanese Patent Application Publication JP H11-306216A” and “Japanese Patent Application Publication JP 2019-105891A” referred to on page 1) in the above-referenced information disclosure statement filed 9/05/2023. Appropriate correction is required.
Reference character S3 shown in Figure 5 is not described in applicant’s specification (see, e.g., pages 27-28 describing FIG. 5). Appropriate correction is required.
Claim Objections
Claims 1-8 are objected to because of the following informalities:
Line 3 of independent claim 1 recites “set a rule, first decision making being performed prior to second decision making”. This recitation is grammatically incorrect and appears to be missing one or more words between “rule,” and “first decision making”. Appropriate correction is required.
Independent claims 4 and 5 both recite “setting a rule, first decision making being performed prior to second decision making” (see, lines 2-3 of claim 4 and lines 3-4 of claim 5). These recitations are grammatically incorrect and appear to be missing one or more words between “rule,” and “first decision making”. Appropriate correction is required.
Also, claims 2-3 and 8 are objected to based on their respective dependencies from claim 1, claim 6 is objected to based on its dependency from claim 4, and claim 7 is objected to based on its dependency from claim 5.
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 5 and 7 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. It appears independent claim 5 and its dependent claim 7 would reasonably be interpreted by one of ordinary skill as software per se and/or data per se, failing to fall within a statutory category of invention. The claims do not fall within at least one of the four categories of patent eligible subject matter because they are directed to “A recording medium with an aircraft control program making a computer execute” (claim 5) and “The recording medium according to claim 5” (claim 7) which can be considered either purely software, purely data, or some combination of both.
Applicants’ disclosure contains no explicit and deliberate definition for the term “A recording medium with an aircraft control program making a computer execute” recited in claim 5, and in the context of the disclosure (see, e.g., page 5, which merely repeats the claim language in stating “an aircraft control program makes a computer execute” without mentioning, let alone describing any “recording medium” or recording media) and claim in question, one of ordinary skill would reasonably interpret this term as a software application (i.e., a computer-implemented aircraft control program/software application), data (i.e., data/instructions of the “aircraft control program” stored in the “recording medium”), or some combination of both. As such, the claim does not recite actual structure or a hardware component/device (i.e., no computer is positively recited, much less a processor/CPU/GPU or memory). Rather, the claim merely recites that the aircraft control program is stored on “A recording medium” where the aircraft control program appears to be a software component. Thus, the aircraft control program of software alone of claim 5 is not a machine, is clearly not a process, manufacture nor composition of matter (See MPEP 2106.03).
Data per se and/or software per se that is not tied to a tangible medium, such as a non-transitory computer readable storage medium, is non-statutory subject matter. MPEP §2106.03 expressly lists “data per se” and “software per se” as non-statutory.
Also, claim 7, which depends directly from claim 5, and also fails to recite actual structure or a hardware component/device, is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject under the same rationale as claim 5.
Claims 1-8 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The analysis below of the claims’ subject matter eligibility follows the 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (January 7, 2019) (“2019 PEG”) and the 2024 Guidance Update on Patent Subject Matter Eligibility, Including on Artificial Intelligence, 89 Fed. Reg. 58128-58138 (July 17, 2024) (“2024 AI SME Update”).
When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (Step 1). If the claim does fall within one of the statutory categories, the second step in the analysis is to determine whether the claim is directed to a judicial exception (Step 2A). The Step 2A analysis is broken into two prongs. In the first prong (Step 2A, Prong 1), it is determined whether or not the claims recite a judicial exception (e.g., mathematical concepts, mental processes, certain methods of organizing human activity). If it is determined in Step 2A, Prong 1 that the claims recite a judicial exception, the analysis proceeds to the second prong (Step 2A, Prong 2), where it is determined whether or not the claims integrate the judicial exception into a practical application. If it is determined at step 2A, Prong 2 that the claims do not integrate the judicial exception into a practical application, the analysis proceeds to determining whether the claim is a patent-eligible application of the exception (Step 2B). If an abstract idea is present in the claim, any element or combination of elements in the claim must be sufficient to ensure that the claim integrates the judicial exception into a practical application, or else amounts to significantly more than the abstract idea itself.
Regarding independent claim 1, this claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 1 is directed to a system, corresponding to a machine, which is one of the statutory categories.
Step 2A Prong One Analysis: The claim is directed to an abstract idea. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
The limitations:
set a rule, first decision making being performed prior to second decision making, the first decision making and the second decision making being performed for flying an aircraft, the rule being used for performing the second decision making based on an initial result of the first decision making; …
evaluate results of the first decision making and results of the second decision making; and
generate information for supporting pilot of the aircraft, based on the first learning result and the second learning result, …
settle the first learning result by evaluating the initial result of the first decision making through the first reinforcement learning and a result of the second decision making based on the rule when the second learning result has not been acquired prior to the first reinforcement learning, and
settle the first learning result by evaluating another result of the first decision making through the first reinforcement learning and another result of the second decision making based on the second learning result when the second learning result has been acquired prior to the first reinforcement learning.
As drafted, under their broadest reasonable interpretation (BRI), cover concepts performed in the human mind (including evaluation, judgement, or opinion to set/establish a rule, make a 1st decision before a 2nd decision, the 1st and 2nd decisions being made for flying an aircraft1 where the rule is used to make the 2nd decision based on an observed initial result of the 1st decision, and evaluation, judgement, or opinion to generate/create information for supporting piloting of the aircraft2, based on observing the 1st and 2nd learning results and then evaluation, judgement, or opinion to settle the 1st learning result by evaluating the observed initial result of the 1st decision through 1st reinforcement learning and an observed result of the 2nd decision based on the rule when the 2nd learning result has not been acquired prior to the 1st reinforcement learning, and then settle the first learning result by evaluating another result of the 1st decision through the 1st reinforcement learning and another result of the 2nd decision making based on observing the 2nd learning result when it has been acquired prior to the 1st reinforcement learning).
The above limitations in the context of this claim encompass, inter alia, evaluation, judgement, or opinion to set/establish a rule, make 1st and 2nd decisions, evaluate results of the decisions, generate information based on observed 1st and 2nd learning results, and then settle the 1st learning result by evaluating observed decision results from reinforcement learning (corresponding to mental processes which can be done mentally or by pen and paper).
Regarding the “first reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable to produce a “result of the first decision making”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the “first reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the “first decision making through the first reinforcement learning” from being performed mentally or with pen and paper.
Step 2A Prong Two Analysis: The judicial exception is not integrated into a practical application.
The claim recites the following additional elements: An aircraft control system comprising:
circuitry configured to: <perform the above-noted set a rule, evaluate and generate operations> and
wherein the circuitry is configured to: <perform the above-noted settle and evaluating operations> - The system is recited at a high level of generality as mere instructions to implement an abstract idea on a computer (i.e., an aircraft control system including generically-recited circuitry) and amounts to the recitation of the words “apply it” (or an equivalent) or amount to no more than mere instructions to implement an abstract idea or other exception on a computer or merely use a computer as a tool to perform an abstract idea (i.e., as generic computer components performing generic computer functions). See MPEP 2106.05(f).
The claim also recites the additional limitation:
acquire a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning targeting a first learning case, the second learning result being acquired by second reinforcement learning targeting a second learning case different from the first learning case, the first learning result being used for the first decision making, the second learning result being used for the second decision making3 – These are insignificant extra-solution activities that are not integrated into the claim as a whole and do not add a meaningful limitation to the above-noted mental processes specified in this claim.
That is, “acquire a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” amounts to mere data gathering (i.e., receiving provided/transmitted input data) (See MPEP § 2106.05(g)).
Regarding the “first reinforcement learning” and “second reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable for “targeting a first learning case” and “targeting a second learning case”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the 1st and 2nd “reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the 1st and 2nd “reinforcement learning” from being performed mentally or with pen and paper.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B Analysis: The claim does not recite additional elements that are sufficient to amount to significantly more than the judicial exception.
The above-noted “acquire a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation is adding insignificant extra-solution activity (amounts to necessary data gathering) to the judicial exception, as discussed in MPEP § 2106.05(g).
According to MPEP 2106.05(d) Subsection II, "The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)". Therefore, the recitation of “acquire a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation are the well-understood, routine, conventional activities of receiving or transmitting data over a network, as discussed in MPEP § 2106.05(d). A mere act to apply an exception using a generic act of acquiring/receiving cannot provide an inventive concept.
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of “An aircraft control system comprising: circuitry configured to:” <perform the above-noted set a rule, evaluate and generate operations> and “wherein the circuitry is configured to:” <perform the above-noted settle and evaluating operations> amount to no more than using generic computer components to implement the exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
As an ordered whole, the claim is directed to a system to set/establish a rule, make 1st and 2nd decisions, evaluate results of the decisions, generate information based on observed 1st and 2nd learning results, and then settle the 1st learning result by evaluating observed decision results from reinforcement learning. Nothing in the claim provides significantly more than this. As such, the claim is not patent eligible.
Regarding independent claim 4, this claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 4 is directed to a method, corresponding to a process, which is one of the statutory categories.
Step 2A Prong One Analysis: The claim is directed to an abstract idea. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
The limitations: A method of controlling an aircraft comprising:
setting a rule, first decision making being performed prior to second decision making, the first decision making and the second decision making being performed for flying the aircraft, the rule being used for performing the second decision making based on an initial result of the first decision making; …
evaluating results of the first decision making and results of the second decision making; and
generating information for supporting pilot of the aircraft, based on the first learning result and the second learning result,
wherein the first learning result is settled by evaluating the initial result of the first decision making through the first reinforcement learning and a result of the second decision making based on the rule when the second learning result has not been acquired prior to the first reinforcement learning, and
the first learning result is settled by evaluating another result of the first decision making through the first reinforcement learning and another result of the second decision making based on the second learning result when the second learning result has been acquired prior to the first reinforcement learning.
As drafted, under their BRI, cover concepts performed in the human mind (including evaluation, judgement, or opinion to set/establish a rule, make a 1st decision before a 2nd decision, the 1st and 2nd decisions being made for flying the aircraft4 where the rule is used to make the 2nd decision based on an observed initial result of the 1st decision, and evaluation, judgement, or opinion to generate/create information for supporting piloting of the aircraft5, based on observing the 1st and 2nd learning results and then evaluation, judgement, or opinion to settle the 1st learning result by evaluating the observed initial result of the 1st decision through 1st reinforcement learning and an observed result of the 2nd decision based on the rule when the 2nd learning result has not been acquired prior to the 1st reinforcement learning, and then settle the first learning result by evaluating another result of the 1st decision through the 1st reinforcement learning and another result of the 2nd decision making based on observing the 2nd learning result when it has been acquired prior to the 1st reinforcement learning).
The above limitations in the context of this claim encompass, inter alia, evaluation, judgement, or opinion to set/establish a rule, make 1st and 2nd decisions, evaluate results of the decisions, generate information based on observed 1st and 2nd learning results, and then settle the 1st learning result by evaluating observed decision results from reinforcement learning (corresponding to mental processes which can be done mentally or by pen and paper).
Regarding the “first reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable to produce a “result of the first decision making”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the “first reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the “first decision making through the first reinforcement learning” from being performed mentally or with pen and paper.
Step 2A Prong Two Analysis: The judicial exception is not integrated into a practical application.
The claim recites the following additional elements:
acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning targeting a first learning case, the second learning result being acquired by second reinforcement learning targeting a second learning case different from the first learning case, the first learning result being used for the first decision making, the second learning result being used for the second decision making6; – These are insignificant extra-solution activities that are not integrated into the claim as a whole and do not add a meaningful limitation to the above-noted mental processes specified in this claim.
That is, “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” amounts to mere data gathering (i.e., receiving provided/transmitted input data) (See MPEP § 2106.05(g)).
Regarding the “first reinforcement learning” and “second reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable for “targeting a first learning case” and “targeting a second learning case”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the 1st and 2nd “reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the 1st and 2nd “reinforcement learning” from being performed mentally or with pen and paper.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B Analysis: The claim does not recite additional elements that are sufficient to amount to significantly more than the judicial exception.
The above-noted “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation is adding insignificant extra-solution activity (amounts to necessary data gathering) to the judicial exception, as discussed in MPEP § 2106.05(g).
According to MPEP 2106.05(d) Subsection II, "The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)". Therefore, the recitation of “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation are the well-understood, routine, conventional activities of receiving or transmitting data over a network, as discussed in MPEP § 2106.05(d). A mere act to apply an exception using a generic act of acquiring/receiving cannot provide an inventive concept.
As an ordered whole, the claim is directed to a method of setting/establishing a rule, making 1st and 2nd decisions, evaluating results of the decisions, generating information based on observed 1st and 2nd learning results, and then settling the 1st learning result by evaluating observed decision results from reinforcement learning. Nothing in the claim provides significantly more than this. As such, the claim is not patent eligible.
Regarding independent claim 5, this claim is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 5 is directed to a recording medium with an aircraft control program, corresponding to an article of manufacture, which is one of the statutory categories.
Step 2A Prong One Analysis: The claim is directed to an abstract idea. In particular, the claim recites mental processes that are concepts performed in the human mind (including an observation, evaluation, judgment, opinion).
The limitations:
setting a rule, first decision making being performed prior to second decision making, the first decision making and the second decision making being performed for flying an aircraft, the rule being used for performing the second decision making based on an initial result of the first decision making; …
evaluating results of the first decision making and results of the second decision making; and
generating information for supporting pilot of the aircraft, based on the first learning result and the second learning result,
wherein the first learning result is settled by evaluating the initial result of the first decision making through the first reinforcement learning and a result of the second decision making based on the rule when the second learning result has not been acquired prior to the first reinforcement learning, and
the first learning result is settled by evaluating another result of the first decision making through the first reinforcement learning and another result of the second decision making based on the second learning result when the second learning result has been acquired prior to the first reinforcement learning.
As drafted, under their BRI, cover concepts performed in the human mind (including evaluation, judgement, or opinion to set/establish a rule, make a 1st decision before a 2nd decision, the 1st and 2nd decisions being made for flying an aircraft7 where the rule is used to make the 2nd decision based on an observed initial result of the 1st decision, and evaluation, judgement, or opinion to generate/create information for supporting piloting of the aircraft8, based on observing the 1st and 2nd learning results and then evaluation, judgement, or opinion to settle the 1st learning result by evaluating the observed initial result of the 1st decision through 1st reinforcement learning and an observed result of the 2nd decision based on the rule when the 2nd learning result has not been acquired prior to the 1st reinforcement learning, and then settle the first learning result by evaluating another result of the 1st decision through the 1st reinforcement learning and another result of the 2nd decision making based on observing the 2nd learning result when it has been acquired prior to the 1st reinforcement learning).
The above limitations in the context of this claim encompass, inter alia, evaluation, judgement, or opinion to set/establish a rule, make 1st and 2nd decisions, evaluate results of the decisions, generate information based on observed 1st and 2nd learning results, and then settle the 1st learning result by evaluating observed decision results from reinforcement learning (corresponding to mental processes which can be done mentally or by pen and paper).
Regarding the “first reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable to produce a “result of the first decision making”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the “first reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the “first decision making through the first reinforcement learning” from being performed mentally or with pen and paper.
Step 2A Prong Two Analysis: The judicial exception is not integrated into a practical application.
The claim recites the following additional element: A recording medium with an aircraft control program making a computer execute: <the above-noted setting a rule, evaluating and generating steps> - The recording medium with an aircraft control program (i.e., a recording medium storing instructions) is recited at a high level of generality as mere instructions to implement an abstract idea on a computer (i.e., “a computer” executing the program instructions to carry out the steps) and amount to the recitation of the words “apply it” (or an equivalent) or amount to no more than mere instructions to implement an abstract idea or other exception on a computer or merely use a computer as a tool to perform an abstract idea (i.e., as generic computer components performing generic computer functions). See MPEP 2106.05(f).
The claim also recites the following additional elements:
acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning targeting a first learning case, the second learning result being acquired by second reinforcement learning targeting a second learning case different from the first learning case, the first learning result being used for the first decision making, the second learning result being used for the second decision making9; – These are insignificant extra-solution activities that are not integrated into the claim as a whole and do not add a meaningful limitation to the above-noted mental processes specified in this claim.
That is, “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” amounts to mere data gathering (i.e., receiving provided/transmitted input data) (See MPEP § 2106.05(g)).
Regarding the “first reinforcement learning” and “second reinforcement learning”, no details of the reinforcement learning are recited, and the reinforcement learning is recited at a high level of generality and can be carried out as a mental process or by hand with pen and paper. Thus, the claimed “reinforcement learning”, under the BRI, in light of the specification, could be any learning (i.e., a mental process) useable for “targeting a first learning case” and “targeting a second learning case”, which can be done mentally or by pen and paper based on a reasonable amount of observed data (i.e., the “initial result of the first decision”). That is, the 1st and 2nd “reinforcement learning” limitations give the indication that the learning can be carried out as a mental process. Given a sufficiently small amount of data in the “initial result of the first decision”, nothing in the claim prohibits the 1st and 2nd “reinforcement learning” from being performed mentally or with pen and paper.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
Step 2B Analysis: The claim does not recite additional elements that are sufficient to amount to significantly more than the judicial exception.
The above-noted “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation is adding insignificant extra-solution activity (amounts to necessary data gathering) to the judicial exception, as discussed in MPEP § 2106.05(g).
According to MPEP 2106.05(d) Subsection II, "The courts have recognized the following computer functions as well-understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)". Therefore, the recitation of “acquiring a first learning result and a second learning result, the first learning result being acquired by first reinforcement learning …, the second learning result being acquired by second reinforcement learning” limitation are the well-understood, routine, conventional activities of receiving or transmitting data over a network, as discussed in MPEP § 2106.05(d). A mere act to apply an exception using a generic act of acquiring/receiving cannot provide an inventive concept.
Also, as discussed above with respect to integration of the abstract idea into a practical application, the additional element of “A recording medium with an aircraft control program making a computer execute:” <the above-noted setting a rule, evaluating and generating steps> amounts to no more than using generic computer components to implement the exception. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept.
As an ordered whole, the claim is directed to a method of setting/establishing a rule, making 1st and 2nd decisions, evaluating results of the decisions, generating information based on observed 1st and 2nd learning results, and then settling the 1st learning result by evaluating observed decision results from reinforcement learning. Nothing in the claim provides significantly more than this. As such, the claim is not patent eligible.
Regarding claims 2, 6 and 7, these claims are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 2 is directed to a system as depending from claim 1, claim 6 is directed to a method as depending from claim 4, and claim 7 is directed to a recording medium as depending from claim 5, thus the analysis for patent eligibilities of claims 1, 4 and 5 are incorporated herein.
Step 2A Prong 1: These claims each recite “wherein the first decision making includes determining a target point of the aircraft while the second decision making includes determining a flight path of the aircraft to the target point.”
These limitations do nothing to alter the fundamental nature of the claims as an abstract idea. This is because the additional limitations merely limit the invention to a narrower abstract idea by further narrowing what the 1st and 2nd “decision making” includes, i.e., “determining a target point of the aircraft” and “determining a flight path of the aircraft to the target point”, respectively.
Dependent claims 2, 6 and 7, when analyzed as a whole, are not patent eligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The additional limitation added by these claims cover a concept performed in the human mind (evaluation, judgement, or opinion to make the 1st decision by determining/identifying a target point of the aircraft and to make the 2nd decision making by determining/identifying a flight path of the aircraft based on the determined target point.
Thus, these limitations do nothing to alter the analysis of base claims 1, 4 and 5.
Step 2A Prong Two: The judicial exceptions are not integrated into a practical application.
The claims do not recite any additional elements that integrate the abstract idea into a practical application or provide significantly more than the abstract idea, and thus the claims are subject-matter ineligible.
Step 2B: The claims do not recite additional elements that are sufficient to amount to significantly more than the judicial exception.
These claims are not patent eligible.
Regarding claims 3 and 8, these claims are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1 Analysis: Claim 3 is directed to a system as depending from claim 1, and claim 8 is directed to a system as depending from claim 3, thus the analysis for patent eligibilities of base claim 1 and intervening claim 2 (in the case of claim 8) are incorporated herein.
Step 2A Prong 1: Claim 3 recites “An aircraft comprising the aircraft control system according to claim 1.” and claim 8 recites “An aircraft comprising the aircraft control system according to claim 2.”
These additional limitations merely limit the invention to a narrower abstract idea by further narrowing where the generically-recited aircraft control system is installed or able to execute (i.e., the generically-recited “An aircraft”). Dependent claims 3 and 8, when analyzed as a whole, are not patent eligible under 35 U.S.C. 101 because the additional recited limitations fail to establish that the claims are not directed to an abstract idea.
Thus, these new limitations do nothing to alter the analysis of base claim 1 and intervening claim 2 (in the case of claim 8).
Step 2A Prong Two Analysis: The judicial exceptions are not integrated into a practical application.
The additional element of “An aircraft comprising the aircraft control system” can be considered as “generally linking the use of judicial exception to a particular technological environment or field of use”. See MPEP 2106.05(h). See MPEP 2106.05(h).
Thus, there are no additional elements to integrate the abstract idea into a practical application or to impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Step 2B Analysis: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Viewing the additional element of this dependent claim as a combination does not add anything further than the individual elements.
As discussed above with respect to integration of the abstract idea into a practical application, there are no additional elements recited that impose any meaningful limits on practicing the abstract idea. Further, limiting the abstract idea to a particular technological context or field of use, does not render the claims patent eligible. Therefore, the additional elements of these dependent claims are not sufficient to amount to significantly more than the abstract idea. These claims are not patent eligible.
Conclusion
The prior art made of record, listed on form PTO-892, and not relied upon, is considered pertinent to applicants’ disclosure.
The references listed on form PTO-892 are all generally related to techniques, methods and systems for using reinforcement learning to assist with functions relating to aircraft such as unmanned aerial vehicles (UAVs) and drones.
For example, Fujishima et al. (U.S. Patent No. 12,140,913 B2, hereinafter “Fujishima patent”) discloses “An unmanned system 1 … includes a control device 10”, The control device 10 according to the present embodiment further has a function of executing a more preferable control … within a related art control scheme determined on a rule base. The apparatus 20 is an apparatus that operates in an unmanned manner such as an autonomous vehicle or an automated aerial vehicle (AAV)” and “According to the unmanned system 1 of the present embodiment, it is possible to achieve both easy understanding of an action generation ground that is an advantage of rule base of related-art and performance improvement that is an advantage of reinforcement learning.” (see, e.g., col. 3, line 66-col. 4, line 29 and col. 7, lines 13-17).
Also, for example, Fujishima et al. (U.S. Patent Application Pub. No. 2020/0285202 A1, part of the prior art made of record cited in applicant’s IDS filed 9/05/2023, hereinafter “Fujishima”) discloses “An unmanned system … includes a control device 10, an apparatus 20,” “The control device 10 is a computer that controls the apparatus 20, and includes a central processing unit (CPU) or a micro processing unit (MPU). … The apparatus 20 is an apparatus that operates in an unmanned manner such as … an automated aerial vehicle (AAV)”, “the control device 10 and the like may be realized using hardware such as a microcomputer, an LSI (Large Scale Integration), an ASIC (Application Specific Integrated Circuit),” and “an unmanned system related to a moving object such as an aircraft” [i.e., an aircraft/AAV control system including a CPU/MPU-circuitry] (see, e.g., paragraphs 32-33, 115 and 118).
Fujishima further discloses that “control device 10 determines predetermined environment information (for example, an ambient temperature, or the like) on the basis of a predetermined rule, and determines a control to be performed next (control based on an IF-THEN rule) … The apparatus 20 is … an automated aerial vehicle (AAV)” and “the action parameter calculation in the control device 10 may be used for a decision making system … the decision making system receives input of parameters necessary for decision making, determines a decision making scheme on a rule base, and determines variable parameters in the scheme using a learning model constructed by reinforcement learning. The decision making system evaluates the result of the decision made in this way and updates the learning model.” [i.e., set a rule, make a 1st decision before a 2nd decision, decisions are for flying an aircraft/AAV, and evaluating results of decisions using reinforcement learning] (see, e.g., paragraphs 34 and 118).
Additionally, for example, Choi (U.S. Patent Application Pub. No. 2023/0297859 A1, hereinafter “Choi”10) discloses “a method and apparatus for generating a multi-drone network operation plan based on reinforcement learning.” and “In an embodiment of the present disclosure, the state-action history information may include location information of a drone for each decision step. In this case, the step (c) may include generating flight path information of the drone included in the operation plan based on the location information.” where “a multi-drone agent reinforcement learning method based on a multi-agent deep deterministic policy gradient (MADDPG) algorithm includes steps of (a) defining a reinforcement learning hyperparameter, (b) initializing a state of a Markov game and obtaining observation for each drone agent based on the initialized state of the Markov game, ( c) generating tuple data comprising observation, an action, a reward, and next observation for each drone agent” (see, Abstract and paragraphs 10 and 14).
The examiner requests, in response to this office action, support be shown for language added to any original claims on amendment and any new claims. That is, indicate support for newly added claim language by specifically pointing to page(s) and line no(s) in the specification and/or drawing figure(s). This will assist the examiner in prosecuting the application.
When responding to this office action, Applicant is advised to clearly point out the patentable novelty which he or she thinks the claims present, in view of the state of the art disclosed by the reference cited or the objections made. He or she must also show how the amendments avoid such references or objections See 37 CFR 1.111 (c).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RANDY K BALDWIN whose telephone number is (571)270-5222. The examiner can normally be reached on Mon - Fri 9:00-6:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kamran Afshar can be reached on 571-272-7796. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RANDALL K. BALDWIN/Primary Examiner, Art Unit 2125
1 Also, the limitation includes intended use language with no patentable weight (e.g., “for flying an aircraft”).
2 Also, the limitation includes intended use language with no patentable weight (e.g., “for supporting pilot of the aircraft”).
3 Also, the limitation includes intended use language with no patentable weight (e.g., “the first learning result being used for the first decision making, the second learning result being used for the second decision making”).
4 Also, the limitation includes intended use language with no patentable weight (e.g., “for flying the aircraft”).
5 Also, the limitation includes intended use language with no patentable weight (e.g., “for supporting pilot of the aircraft”).
6 Also, the limitation includes intended use language with no patentable weight (e.g., “the first learning result being used for the first decision making, the second learning result being used for the second decision making”).
7 Also, the limitation includes intended use language with no patentable weight (e.g., “for flying an aircraft”).
8 Also, the limitation includes intended use language with no patentable weight (e.g., “for supporting pilot of the aircraft”).
9 Also, the limitation includes intended use language with no patentable weight (e.g., “the first learning result being used for the first decision making, the second learning result being used for the second decision making”).
10 Choi was filed on October 12, 2022 and claims foreign priority to Korean patent application No. 10-2022-0033925 filed on March 18, 2022, and this date is before the effective filing date of this application, i.e., September 23, 2022. Therefore, Choi constitutes prior art under 35 U.S.C. 102(a)(2)
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