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 .
DETAILED ACTION
Status of Claims
The following is a Final Office Action in response to Applicant’s amendment received 07/18/2025.
In accordance with Applicant’s amendment, claims 1, 3-4, 7, 10, 13 are amended, claims 2, 5-6, 8-9, 11-12, and 14-15 are canceled, and claims 16-19 are added as new claims. Claims 1, 3-4, 7, 10, 13, and 16-19 are currently pending.
Response to Amendment
Applicant’s amendment necessitated the new ground(s) of rejection set forth in this Office Action.
The amendment to the title of the invention is entered and the objection to the Specification is withdrawn.
The 35 U.S.C. §112(f) interpretation invoked by claims 1 and 4-8 is no longer applicable because the amended claims no longer invoke §112(f).
The 35 U.S.C. §112(a) and §112(b) rejections of claims 1-12 are withdrawn in response to applicant’s amendment. However, a new ground of rejection is applied to claims 1, 3-4, 7, 10, 13, and 16-19, which was necessitated by the amendment.
The 35 U.S.C. §102 rejection of claims 1-3, 7, 9, and 13 and the §103 rejection of claims 4-6, 8, 10-12, and 14-15 are withdrawn in response to applicant’s amendment.
Response to Arguments
Response to §101 Arguments – Applicant’s arguments (Remarks at pgs. 15-18) are directed to the amended claims, however it is noted that all of the previous limitations recited in independent claims 1 and 13 have been deleted and replaced with new limitations, which have not been previously presented or considered. Accordingly, the amended claims and supporting arguments are believed to be fully addressed in the updated §101 rejection set forth below.
Response to §102/§103 Arguments – Applicant’s arguments (Remarks at pgs. 19-21) are directed to the amended claims, however the arguments are moot in view of withdrawal of the §102 and §103 rejections.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1, 3-4, 7, 10, 13, and 16-19 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
The first paragraph of 35 U.S.C. 112 requires that the “specification shall contain a written description of the invention.” This requirement is separate and distinct from the enablement requirement. See, e.g., Vas-Cath, Inc. v. Mahurkar, 935 F.2d 1555, 1560, 19 USPQ2d 1111, 1114 (Fed. Cir. 1991). See also Univ. of Rochester v. G.D. Searle & Co., 358 F.3d 916, 920-23, 69 USPQ2d 1886, 1890-93 (Fed. Cir. 2004) (discussing history and purpose of the written description requirement). To satisfy the written description requirement, a patent specification must describe the claimed invention in sufficient detail that one skilled in the art can reasonably conclude that the inventor had possession of the claimed invention. See, e.g., Moba, B.V. v. Diamond Automation, Inc., 325 F.3d 1306, 1319, 66 USPQ2d 1429, 1438 (Fed. Cir. 2003); Vas-Cath, Inc. v. Mahurkar, 935 F.2d at 1563, 19 USPQ2d at 1116. However, a showing of possession alone does not cure the lack of a written description. Enzo Biochem, Inc. v. Gen-Probe, Inc., 323 F.3d 956, 969-70, 63 USPQ2d 1609, 1617 (Fed. Cir. 2002).
In particular, claims 1/13 were amended on 07/18/2025 to include the following new limitations: receiving…environmental data from predictive disaster models, infrastructure monitoring systems, and emergency response databases; generate a disaster response strategy based on the environmental data received; user input from a user that defines a disaster scenario; shortage of emergency personnel; receive a user-defined response plan from the user and the disaster response strategy to the disaster scenario by selectively holding certain environmental conditions constant, isolating effectiveness of a respective strategy for specified conditions; generate an explanation of the disaster response strategy, associating resource allocations with projected disaster effects and response outcomes; produce a comparative analysis that highlight key differences in projected disaster mitigation between the disaster response strategy and the user-defined disaster response plan; and retrain the reinforcement learning model based on the comparative analysis. For example, the Specification refers mentions the term “disaster” in two briefly instances, first at page 1 of the Specification in the Background of the Invention, noting “For example, in order to minimize damage caused by an expected natural disaster or the like, it is possible to formulate an advance measure plan…,” and at pg. 9 line 13 similarly referring to “an expected natural disaster or the like.” While these generic references to “an expected natural disaster” allude to a potential field of use, they are wholly insufficient to show possession of the claim limitations for generating a disaster response strategy, defining a disaster scenario, generating an explanation of the disaster response strategy, or retraining an reinforcement learning model based on a comparative analysis of a user-defined response plan and a disaster response strategy. Applicant’s remarks filed on 07/19/2025 (at pgs. 10-11) cite pars. 116-125 and Fig. 12 as supporting the amendment, including the above-noted limitations. These paragraphs and Fig. 12 have been reviewed, but fail to provide sufficient descriptive support for these limitations. Notably, these paragraphs are silent regarding the above-noted limitations, whereas Fig. 12 displays “an example of a screen output of machine learning system evaluation results,” which at most displays intended output, however the figure and the paragraphs are silent regarding support sufficient to show how the claim functions are performed to provide the displayed output. The above-noted limitations require specific results that cannot be achieved by merely applying a one-size-fits-all model or plan or generalized machine learning techniques, but would be reasonably understood by one skilled in the art as requiring specific techniques, algorithms, actions, considerations, analysis, and models to apply the disclosed machine learning to such a specific context (disaster preparedness), none of which have been disclosed in the originally filed Specification in a manner that supports the subject matter encompassed by the amended claims.
Accordingly, there is no evidence of a complete specific application or embodiment to satisfy the requirement that the description is set forth “in such full, clear, concise, and exact terms” to show possession of the claimed invention. See Fields v. Conover, 443 F.2d 1386, 1392, 170 USPQ 276, 280 (CCPA 1971).
Dependent claims 3-4, 7, 10, and 16-19 depend from one of claims 1/13 and therefore inherit their deficiencies under §112(a).
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 3-4, 7, 10, 13, and 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
Claims 1, 3-4, 7, 10, 13, and 16-19 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The judicial exception is not integrated into a practical application. The claims do include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance with the subject matter eligibility guidance set forth in MPEP 2106.
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106.03), it is first noted that the claimed device (claims 1, 3-4, 7, and 10) and method (claims 13 and 16-19) are each directed to a potentially eligible category of subject matter (i.e., machine and process). Accordingly, claims 1, 3-4, 7, 10, 13, and 16-19 satisfy Step 1 of the eligibility inquiry.
With respect to Step 2A Prong One of the eligibility inquiry (as explained in MPEP 2106.04), it is next noted that the claims recite an abstract idea that falls under the “Mental Processes” abstract idea grouping by setting forth activities that, but for the generic computer implementation, could be performed mentally by a human (including an observation, evaluation, judgment, opinion). With respect to independent claim 1, the limitations reciting the abstract idea are indicated in bold below, whereas the additional elements are identified in plain text and are separately evaluated under Step 2A Prong Two and Step 2B:
an information processing device for disaster preparedness (field-of-use language), the information processing device comprising: a memory; a communication interface; and a processor communicatively coupled to the memory and the communication interface (These are additional elements addressed below under Step 2A Prong Two and Step 2B), wherein the processor is configured to:
receive, using the memory, environmental data from predictive disaster models, infrastructure monitoring systems, and emergency response databases (This limitation describes activity that, but for the generic implementation using the memory and information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion, and the “receive” activity may also be considered as insignificant extra-solution activity, which is not enough to amount to a practical application (MPEP 2106.05(g)), and such extra-solution activity has also been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - 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); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); 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));
apply a reinforcement learning model to generate a disaster response strategy based on the environmental data received (This limitation describes activity that, but for the generic computer implementation by the information processing device and reinforcement learning model, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion);
receive user input from a user that defines a disaster scenario, wherein the user input specifies at least one of: a power outage in a designated region, or a shortage of emergency personnel, receive a user-defined disaster response plan from the user (This limitation describes activity that, but for the generic implementation using the memory and information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion, and the “receive” activity may also be considered as insignificant extra-solution activity, which is not enough to amount to a practical application (MPEP 2106.05(g)), and such extra-solution activity has also been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - 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); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); 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)),
evaluate the user-defined disaster response plan and the disaster response strategy to the disaster scenario by selectively holding certain environmental conditions constant, isolating effectiveness of a respective strategy for specified conditions (The “evaluate” step describes activity that, but for the generic computer implementation by the information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion);
generate an explanation of the disaster response strategy, associating resource allocations with projected disaster effects and response outcomes (The “generate” step describes activity that, but for the generic computer implementation by the information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion);
produce a comparative analysis that highlight key differences in projected disaster mitigation between the disaster response strategy and the user-defined disaster response plan (The “produce a comparative analysis” step describes activity that, but for the generic computer implementation by the information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion, such as with the aid of pen and paper to depict a graph or written analysis of the key differences); and
retrain the reinforcement learning model based on the comparative analysis (The “retrain” step describes activity that, but for the generic computer implementation by the information processing device, could be performed as a mental process, such as by human observation, evaluation, judgment or opinion).
Independent claim 13 recites similar limitations as those set forth in claim 1 as discussed above, and therefore has been determined to recite the same abstract idea as claim 1.
With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP 2106.04(d)), the judicial exception is not integrated into a practical application. Independent claims 1 and 13 include the additional elements of an information processing device, a memory; a communication interface; and a processor communicatively coupled to the memory and the communication interface, reinforcement learning. The additional elements have been evaluated, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (generic computing environment). See MPEP 2106.05(f) and 2106.05(h). Even if the receive activities are interpreted as additional elements, these activities at most amount to insignificant extra-solution activity, which is not indicative of a practical application, as noted in MPEP 2106.05(g). The reinforcement learning is recited at a high level of generality, has not been shown to involve anything other than generic computer implementation, and has not been shown to integrate the claim into a practical application. In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry (as explained in MPEP 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent claims 1 and 13 include the additional elements of an information processing device, a memory; a communication interface; and a processor communicatively coupled to the memory and the communication interface, reinforcement learning. These additional elements have been evaluated, but fail to add significantly more to the claims because they amount to using generic computing elements or instructions/software to perform the abstract idea. The computing elements (information processing device, memory; communication interface; processor communicatively coupled to the memory and the communication interface) are similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (generic computing environment) and does not amount to significantly more than the abstract idea itself. Notably, Applicant’s Specification lists a litany of devices that may be used to implement the invention, which suggests that virtually any computing device(s) under the sun may be used to implement the invention, including generic computers. See, e.g., Specification at pgs. 12-13, noting for example that “The processing device1002 is a general-purpose computer.” Therefore, the additional elements serve to tie the abstract idea to a particular operating environment, which does not add significantly more to the abstract idea. See, e.g., Alice Corp., 134 S. Ct. 2347, 110 USPQ2d 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
Next the reinforcement learning model is recited at a high level of generality and has not been shown to involve anything other than generic computer implementation of the corresponding steps, and furthermore it is noted that machine learning models, particularly when recited at a high level of generality, are considered well-understood, routine, and conventional in the art, and therefore insufficient to add significantly more to the claims. See, e.g., Yeazel et al., US 2022/0366378 (par. 65: “As is known in the art, reinforcement learning may generally include a computing device interacting in a dynamic environment”). See also, Gansner, US Pat. No. 8,447,713 (col. 8, lines 35-37: “There are three major learning paradigm…reinforcement learning--all of which are well known in the art”).
Lastly, even if the receive steps are interpreted as additional elements, these activities at most amount to insignificant extra-solution activity, which has been recognized as well-understood, routine, and conventional, and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - 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); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); 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).
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrate the abstract idea into a practical application. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent claims 3-4, 7, 10, and 16-19 recite the same abstract idea as the independent claims along with further steps/details falling under the “Mental Processes” abstract idea grouping along with the same or substantially the same additional generic computing elements (information processing device, computer-implemented) addressed above in the analysis of independent claims 1/13 (which is incorporated herein) and which, as discussed above, is insufficient to add a practical application or significantly more to the abstract idea, and the additional elements addressed below.
The reinforcement learning description of the model in dependent claims 4, 10, 17, and 19 is recited at a high level of generality, has not been shown to involve anything other than generic computer implementation, and has not been shown to integrate the claims into a practical application, nor has the reinforcement learning model been shown to improve upon the information processing device or any technology, nor otherwise or add anything that otherwise serves to integrate the claim into a practical application. Under Step 2B, the reinforcement learning model recited is considered well-understood, routine, and conventional in the art, and therefore insufficient to add significantly more to the claims. See, e.g., Yeazel et al., US 2022/0366378 (par. 65: “As is known in the art, reinforcement learning may generally include a computing device interacting in a dynamic environment”). See also, Gansner, US Pat. No. 8,447,713 (col. 8, lines 35-37: “There are three major learning paradigm…reinforcement learning--all of which are well known in the art”). Lastly, even if the receive activity (claim 4) is interpreted as additional elements, this activity at most amounts to insignificant extra-solution activity, which is not indicative of a practical application, as noted in MPEP 2106.05(g), and such extra-solution activity has also been recognized as well-understood, routine, and conventional and thus insufficient to add significantly more to the abstract idea. See MPEP 2106.05(d) - 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); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); 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). Furthermore, regarding the display activity in claim 6, this activity could be implemented with a GUI of a general purpose computer, and is therefore insufficient for eligibility. See, Affinity Labs of Texas LLC v. DirecTV LLC, 838 F.3d 1253, 1257-1258 (Fed. Cir. 2016) (mere recitation of a GUI does not make a claim patent-eligible); Intellectual Ventures I LLC v. Capital One Bank, 792 F.3d 1363, 1370 (Fed. Cir. 2015) (“the interactive interface limitation is a generic computer element”).
The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Luo et al. (US 2019/0081980): discloses an intelligence-interaction honeypot for IOT devices, including Q-learning reinforcement learning techniques (at least pars. 116-119).
Hynes et al. (US 2022/0292408): discloses a storm damage response system, including a scenario comparator to select a probabilistic model associated with a forecast model (pars. 38-40 and Fig. 7).
Anagnostou et al. (US 2019/0228362): discloses features for outage prediction, including machine learning models that may be inputted with different combinations of weather variables, joining aggregated outage data to weather analysis forecast data and GIS data and subsequently added to a historic calibration dataset, and an outage prediction model adaptive as new data is added and new patterns are found or reinforced, resulting in an improved outage prediction model (par. 9).
Constrained Deep Q-Learning Gradually Approaching Ordinary Q-Learning. Ohnishi, Shota; Uchibe, Eiji; Yamaguchi, Yotaro; Nakanishi, Kosuke; Yasui, Yuji; et al. Frontiers in Neurorobotics Frontiers Research Foundation. (Dec 10, 2019): discloses deep Q reinforcement learning features, including value-based reinforcement learning.
Traffic Light Cycle Configuration of Single Intersection Based on Modified Q-Learning. Hung-Chi, Chu; Yi-Xiang Liao; Lin-huang, Chang; Yen-Hsi, Lee. Applied Sciences9.21: 4558. MDPI AG. (2019): discloses the application of Q-learning to optimize traffic cycle configuration.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the date of this final action.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Timothy A. Padot whose telephone number is 571.270.1252. The Examiner can normally be reached on Monday-Friday, 8:30 - 5:30. If attempts to reach the examiner by telephone are unsuccessful, the Examiner’s supervisor, Brian Epstein can be reached at 571.270.5389. The fax phone number for the organization where this application or proceeding is assigned is 571- 273-8300.
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/TIMOTHY PADOT/
Primary Examiner, Art Unit 3625
09/24/2025