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 .
Status of Claim
This action is in reply in response to application filed on 8 of September 2026.
Claims 1-20 are currently pending and are rejected as described below.
Allowable Subject Matter
Claims 1-20 are objected to as being currently rejected as below but would be allowable if the independent claims were amended in such a way as to overcome the 35 USC 101 rejection set forth in the action. The prior art of record most closely resembling the applicant’s claimed invention includes Villa et. al. (US 20220114506), Ballester et. al. (US 20240354666), Johnson et. al. (US 20170323239), and Li (CN 111047917A).
Villa teaches a simulation system configured to generate simulation data, a servicing system configured to generate servicing data, and a planning system configured to determine a multi-modal transportation itinerary based on the simulation and servicing data. The simulation data can identify a plurality of simulated flights performed in a simulated world corresponding to the real world. The system can determine the impact of scheduling a multi-modal transportation itinerary based on the impact of the multi-modal transportation itinerary on the simulated flights. The servicing data can include a servicing schedule that plans anticipated servicing events based on the impact of the servicing event to the simulated itineraries. Once scheduled, future simulated flights can be generated that account for the multi-modal transportation itinerary and the servicing schedule.
Ballester teaches methods, systems, and apparatus, including computer programs encoded on computer storage media, for determining elements of a shipping network. One of the methods includes obtaining environmental input data, wherein the environmental input data includes weather forecast data; providing the environmental input data to a circulation model; and providing output environmental condition from the circulation model to a machine learning model trained to generate a route for a ship.
Johnson teaches a method of providing a first set of computer systems with access to a recommendation pertaining to operation of one aircraft in one or more fleets of aircraft is disclosed. Operations data is collected at the first set of computer systems. The operations data pertains to operations of the one or more fleets of aircraft over a time period. The operations data is stored in one or more databases of a second set of computer systems. The operations data includes values corresponding to fields in the one or more databases. The fields represent at least one of policy data pertaining to one or more operations policies, flight schedule data pertaining to one or more flight schedules, and operating cost data pertaining to operating costs associated with the one or more fleets of aircraft. Assumptions of control input values are derived for use by the first set of computer systems based on the operations data. A cost savings analysis is performed with a simulation system for at least one aircraft of the one or more fleets of aircraft, the cost savings analysis including identifying a modification of at least one of the control input values. An estimated reduction of operating costs is computed for the aircraft over one or more time periods. The computing is based on comparisons of a first subset of the operations data with a second subset of the operations data.
Li teaches a flight landing scheduling method based on an improved DQN (deep Q network) algorithm, belonging to the technical field of flight scheduling. The invention solves the problems of overlarge aircraft landing cost in the traditional flight landing scheduling algorithm and limited traditional DQN action space. The method comprises the following steps: step one, constructing a landing cost model suitable for deep reinforcement learning according to information of an airplane to be landed; step two, establishing a deep reinforcement learning intelligent agent; step three, calculating a specific landing time sequence and a minimum cost for landing in the sequence by using an improved algorithm; and step four, transmitting the landing sequence of the airplane and the corresponding minimum cost to a landing cost model and calculating a return to the intelligent agent. And outputting the sequence of a group of airplanes by using the DQN network, and calculating the specific landing time and the total landing cost of each airplane in the group of airplanes by using an improved algorithm.
None of the above prior art explicitly teaches “a delay cost model for computing delay cost metrics is integrated into the probabilistic operational simulation; receive operational data related to operation of the plurality of vehicles across at least a portion of the plurality of routes; using the operational data, run a scenario in the probabilistic operational simulation comprising operating the plurality of vehicles over a timeframe; utilize the delay model to compute a plurality of delay times occurring over the timeframe; input the plurality of delay times into the delay cost model to compute a plurality of delay cost metrics over the timeframe” and these are the reasons which adequately reflect the Examiner's opinion as to why Claims 1-20 are allowable over the prior art of record, and are objected to as provided below.
Claim Rejections - 35 USC § 101
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 therefore, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
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, machines, article of manufacture, or composition of matter. If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea), and if so, it must additionally be determined whether the claim is a patent-eligible application of the exception.
The claims are then analyzed to determine whether the claims are directed to a judicial exception. MPEP §2106.04(a). In determining, whether the claims are directed to a judicial exception, the claims are analyzed to evaluate whether the claims recite a judicial exception (Prong One of Step 2A), and whether the claims recite additional elements that integrate the judicial exception into a practical application (Prong Two of Step 2A). See 2019 Revised Patent Subject Matter Eligibility Guidance (“PEG” 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50-57 (Jan. 7, 2019)).
With respect to 2A Prong 1, claim 1 recites “one or more processing devices configured to: execute the probabilistic operational simulation to generate interactions among a plurality of component simulations; wherein: a plurality of operational models is integrated into the probabilistic operational simulation and generates the component simulations, the plurality of operational models comprising: a route model comprising information describing a route schedule comprising a plurality of routes for the plurality of vehicles; a preparation model comprising information describing tasks to prepare a vehicle for departure; a delay model for computing delay information; a delay cost model for computing delay cost metrics is integrated into the probabilistic operational simulation; receive operational data related to operation of the plurality of vehicles across at least a portion of the plurality of routes; using the operational data, run a scenario in the probabilistic operational simulation comprising operating the plurality of vehicles over a timeframe; utilize the delay model to compute a plurality of delay times occurring over the timeframe; input the plurality of delay times into the delay cost model to compute a plurality of delay cost metrics over the timeframe; output the plurality of delay cost metrics”. Claims 10 and 19 disclose similar limitations as Claim 1 and therefore recite an abstract idea.
More specifically, claims 1, 10, and 19 are directed to “Mathematical Concepts” in particular “mathematical calculations)”, and “Mental Processes” in particular “concepts performed in the human mind (including an observation, evaluation, judgment, opinion)” as discussed in MPEP §2106.04(a)(2), and in the 2019-01-08 Revised Patent Subject Matter Eligibility Guidance. Accordingly, the claims recite an abstract idea.
Dependent claims 2-9, 11-18, and 20 further recite abstract idea(s) contained within the independent claims, and do not contribute to significant more or enable practical application. Thus, the dependent claims are rejected under 101 based on the same rationale as the independent claims.
Under Prong Two of Step 2A of the Alice/Mayo test, the examiner acknowledges that Claims 1, 10, and 19 recite additional elements yet the additional elements do not integrate the abstract idea into a practical application. In order for the judicial exception to be “integrated into a practical application”, an additional element or a combination of additional elements in the claim “will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.” PEG, 84 Fed. Reg. 54 (Jan. 7, 2019). The courts have identified examples in which a judicial exception has not been integrated into a practical application when “an additional element does no more than generally link the use of a judicial exception to a particular technological environment or field of use.” PEG, 84 Fed. Reg. 55 (Jan. 7, 2019); MPEP § 2106.05(h). The claims are directed to an abstract idea.
In particular, claims 1, 10, and 19 recite additional elements boldened and underlined above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process. Further, the remaining additional element(s) italicized above reflect insignificant extra solution activities to the judicial exception, see MPEP 2106.05(g). Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
With respect to step 2B, claims 1, 10, and 19 do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements when considered both individually and as an ordered combination do not amount to significantly more than the abstract idea. The claim recites the additional elements described above. These are generic computer components recited as performing generic computer functions that are mere instructions to apply an exception, because it does no more than merely invoke computers or machinery as a tool to perform an existing process, as evidenced by at least in ¶21, 56 “As shown, computing system 100 includes a processing device 104 (e.g., a logic processor such as a central processing unit (CPU)) and a memory device 106 (e.g., volatile and non-volatile memory) operatively coupled to each other. Other components such as input/output subsystems (not shown) can also be included. The memory device 106 stores instructions that, upon execution by the processing device 104, cause the processing device 104 to perform the probabilistic operational simulation 102. Additional details regarding processing device 104, memory device 106, and other components, subsystems, and algorithms of computing system 100 are described further below with reference to FIG. 9. FIG. 9 schematically shows a non-limiting embodiment of a computing system 300 that can enact one or more of the methods and processes described above.
Computing system 300 is shown in simplified form. Computing system 300 may embody the computing system 100 described above and illustrated in FIGS. 1, 4, and 6. Components of computing system 300 may be included in one or more personal computers, server computers, tablet computers, network computing devices, mobile computing devices, mobile communication devices (e.g., smart phone), and/or other computing devices”.
Dependent claims 2-9, 11-18, and 20 do not disclose additional elements, further narrowing the abstract ideas of the independent claims and thus not practically integrated under prong 2A as part of a practical application or under 2B not significantly more for the same reasons and rationale as above.
After considering all claim elements, both individually and in combination, Examiner has determined that the claims are directed to the above abstract ideas and do not amount to significantly more. See Alice Corporation Pty. Ltd. v. CLS Bank International, No. 13–298.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MATHEUS R STIVALETTI whose telephone number is (571)272-5758. The examiner can normally be reached on M-F 8:30-5:30.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Rutao Wu can be reached on (571)272-6045. The fax phone number for the organization where this application or proceeding is assigned is 571-273-1822.
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/MATHEUS RIBEIRO STIVALETTI/Primary Examiner, Art Unit 3623 9/10/2026
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