DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-12 have been presented for examination based on the application filed on 6/26/2023.
Claims 1-12 are rejected under 35 U.S.C. 101.
Claims 1-12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20180229723 A1 by Jiang; Zhen et al.
This action is made Non-Final.
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 1-12 are rejected under 35 U.S.C. 101 because the claimed invention is directed to mental process without any additional elements that provide a practical application or amount to significantly more than the abstract idea.
Claims 1, 9, 10 and 12:
Step 1: the claims 1, 9, 10 and 12 are drawn to a two method, system and article of manufacture respectively, falling under one of the four statutory categories of invention.
Step 2A, Prong 1: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04, subsection II, a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim. The limitations are bolded for abstract idea/judicial expception identification.
Claim 1
Mapping Under Step 2A Prong 1
1. A computer-implemented method for carrying out an experiment using a technical system or using a model of the technical system, the method comprising the following steps:
predefining a first set of input data points for the experiment;
determining a second set of input data points for the experiment as a function of the first set of input data points,
a substitute model for the technical system being configured to determine as a function of the second set of input data points predictions for a result of the experiment for a first prediction statistic, which is to be expected for the second set of input data points when carrying out the experiment using the technical system or using the model of the technical system,
the second set of input data points being determined, for which an estimate of a margin between the first prediction statistic and a second prediction statistic for predictions for a result of the experiment, which is to be expected for the first set of input data points when carrying out the experiment using the technical system or using the model for the technical system, is smaller than for another second set of input data points; and
carrying out the experiment using the second set of input data points at the technical system or at the model of the technical system.
Abstract Idea/Mathematical Concept/Mental Process: The preamble defines design of experiment process for a technical system and is mental process (as in MPEP 2106.04(a)(2)(III)(A)) because it is generally considered a mathematical process (using Gaussian function1) which can be performed with pencil/paper.
See Step 2A Prong 2.
Abstract Idea/Mental Process: the selection of subset of data from first subset is a mental process based on observation.
Abstract Idea/Mathematical Concept/Mental Process: The substitute model is associated with Gaussian process (specification [0010][0047]-[0074] and is considered mathematical concept. Execution of Gaussian model performed with computer as a tool is also considered as abstract idea.
Abstract Idea/Mathematical Concept/Mental Process: The second set is determined based on evaluation of output of multiple second sets to be within a certain threshold (smaller comparison) to outputs of first data set. This is basically design of experiment where the subset represents the larger dataset in results being closest. This is mathematical concept which may be implemented on a computer. The comparison is also mathematical concept. The step may be considered mental step for comparing datum/selecting best second set of input data.
See Step 2A Prong 2.
Under its broadest reasonable interpretation, these covers a mental process including an observation, evaluation, judgment or opinion that could be performed in the human mind or with the aid of pencil and paper. That is, nothing in the claim element precludes the step from practically being performed in the mind or with the aid of pencil and paper but for the recitation of generic computer components.
Claims 9 (broader method claim), Claim 10 (system claim) and Claim 11 (article of manufacture/ non-transitory computer-readable medium) recite similar limitation but being performed by generic computer system or components and would be rejectable in similar manner as claim 1 for abstract idea limitations.
Step 2A, Prong 2: This part of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (2) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. See MPEP 2106.04(d). As per (1) the additional elements are identified as bolded parts of the limitations in column 1 of the table below, and as per (2) the evaluation is shown in the mapping section of the table.
In accordance with this step, the judicial exception is not integrated into a practical application.
Claim 1
Mapping Under Step 2A Prong 2
1. A computer-implemented method for carrying out an experiment using a technical system or using a model of the technical system, the method comprising the following steps:
predefining a first set of input data points for the experiment;
determining a second set of input data points for the experiment as a function of the first set of input data points,
a substitute model for the technical system being configured to determine as a function of the second set of input data points predictions for a result of the experiment for a first prediction statistic, which is to be expected for the second set of input data points when carrying out the experiment using the technical system or using the model of the technical system,
the second set of input data points being determined, for which an estimate of a margin between the first prediction statistic and a second prediction statistic for predictions for a result of the experiment, which is to be expected for the first set of input data points when carrying out the experiment using the technical system or using the model for the technical system, is smaller than for another second set of input data points; and
carrying out the experiment using the second set of input data points at the technical system or at the model of the technical system.
Under MPEP 2106.05(g) determining whether a claim integrates the judicial exception into a practical application in Step 2A Prong Two or recites significantly more in Step 2B is whether the additional elements add more than insignificant extra-solution activity to the judicial exception. In this case this is mere data gathering for first and/or second set of input data.
Under MPEP 2106.05(g) and (h) is extrasolution activity and generic field of use.
In particular, the claim(s) recites the additional elements of a processor for the system claim, at a high-level of generality (i.e. a generic processor/memory performing generic functions of computing and executing information such that it amounts to no more than mere instructions to apply the exception using a generic computer component). 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. See MPEP 2106.05(f).
Step 2B: This part of the eligibility analysis evaluates whether the claim as a whole amounts to significantly more than the recited exception i.e., whether any additional element, or combination of additional elements, adds an inventive concept to the claim. See MPEP 2106.05.
As discussed above with respect to integration of the abstract idea into a practical application, the additional element of using a computer/processor to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer/processing component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (see MPEP 2106.05(f)). The claim is broad & not applicable to any specific technical field and the limitation are not integrated into practical application to contribute significantly more to improve on the technical field (as per MPEP 2106.05(a)). The claims 1, 9, 10 & 12 are therefore considered to be patent ineligible.
Claims 2 recites "... wherein the second set of input data points is selected from the first set of input data points....", which merely adds to abstract idea/mental step of picking subsets of data. The claim does not disclose any additional limitations that integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 3 recites "... wherein the technical system is a computer-controlled machine, the computer-controlled machine being a robot or an at least semi-autonomous vehicle or a drive train or a manufacturing machine or a domestic appliance or a tool or an access control system or a personal assistance system....". This limitation is merely field of use under Step 2A Prong 2 (MPEP 2106.05(h)) and does not integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 4 recites "... wherein a set of scenarios, which characterize in each case a road characteristic including a road curvature, and/or a traffic characteristic including a traffic density, and/or a weather condition, is predefined by one input data point each from the first set of input data points, a set of scenarios, which characterizes in each case a road characteristic including a road curvature, and/or a traffic characteristic including a traffic density, and/or a weather condition, being predefined by one input data point each from the second set of input data points for the experiment....". This is simply enumeration of data gathered under Step 2A Prong 2 (MPEP 2106.05(g)) and does not integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 5 recites "... wherein the technical system includes a vehicle, a result of the experiment including a distance of the vehicle from a center of a lane or to other road users, or the result includes an emission or the vehicle or range of the vehicle....". This limitation is merely field of use under Step 2A Prong 2 (MPEP 2106.05(h)) and does not integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 6 recites "... wherein: i) a result of the experiment is detected,..
and/or ii) an instruction for activating the technical system or an instruction for changing the technical system is determined and/or output as a function of the result of the experiment, and/or iii) the technical system is activated or changed as a function of the result of the experiment, and/or iv) the substitute model is improved as a function of the result of the experiment...." ” This is simply enumeration of data gathered/Outputted (output, control signals gathered, or extra solution activity to be performed) under Step 2A Prong 2 (MPEP 2106.05(g)) and does not integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 7 recites "... wherein an estimate of the second prediction statistic is determined using a Gaussian process and/or an estimate of the first prediction statistic is determined using a Gaussian process....". This limitation is abstract idea/mathematical concept under Step 2A Prong 1 (MPEP 2106.04(a)(2)(I)(C)). The claim does not disclose any additional limitations that integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 8 recites "... wherein the Gaussian process defines a mean value function and a covariance function, the mean value function mapping input data points onto average output data points, the covariance function mapping the input data points onto covariances between the output data points, which are assigned to the input data points, the mean value function and/or the covariance function being adapted to pairs of input data points and output data points, which are observed when carrying out the experiment using the technical system or using the model for the technical system....". This limitation is abstract idea/mathematical concept under Step 2A Prong 1 (MPEP 2106.04(a)(2)(I)(C)). The claim does not disclose any additional limitations that integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
Claim 11 recites "... an interface configured: i) to predefine input data points for carrying out an experiment at the technical system or at the model of the technical system, and/or ii) to detect a result of the experiment carried out at the technical system or at the model of the technical system, and/or iii) to output an instruction for activating the technical system or an instruction for changing the technical system as a function of a result of the experiment carried out at the technical system or at the model of the technical system....". This limitation presents what an interface gathers/displays, which as generically claimed is extra-solution activity under Step 2A Prong 2 (MPEP 2106.05(g) and 2106.05(f)). The claim does not disclose any additional limitations that integrate the judicial exception into practical application (Step 2A Prong 2) or contribute significantly more (Step 2B).
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Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-12 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 20180229723 A1 by Jiang; Zhen et al.
Regarding Claims 1, 10 and 12
Jiang teaches
(Claim 1) A computer-implemented method for carrying out an experiment using a technical system or using a model of the technical system (Jiang: Fig.3 and associated disclosure; Abstract "... Data sets may be collected from users having various demographic and behavioral attributes. Users may be selected using design of experiment (DOE) algorithms to cover a wide range of possible combinations..."),
(Claim 10) A device configured to carrying out an experiment using a technical system or using a model of a technical system (Jiang: Fig.1-2) , the device comprising: at least one processor (Jiang: Fig.2 element 202) ; and at least one memory (Jiang: Fig.2 element 204) , the memory being configured to store instructions, upon the execution of which by the at least one processor, the at least one processor performs the following steps (Jiang: [0081]-[0086]):
(Claim 12) A non-transitory computer-readable medium on which is stored a computer program including instructions for carrying out an experiment using a technical system or using a model of the technical system (Jiang: Abstract; Fig.3) , the instruction, when executed by a computer (Jiang: [0080]-[0081]) , causing the computer to perform the following steps:
the method comprising the following steps:
predefining a first set of input data points for the experiment (Jiang: [0039]-[0040] as collection of sensor and feedback data);
determining a second set of input data points for the experiment as a function of the first set of input data points (Jiang: [0056] as teaching using subset of points for design of experiment, Fig.5 and [0053]-[0060]),
a substitute model for the technical system being configured to determine as a function of the second set of input data points predictions for a result of the experiment for a first prediction statistic, which is to be expected for the second set of input data points when carrying out the experiment using the technical system or using the model of the technical system (Jiang: substitute model as building a stochastic response surface model (SRSM)/RSM as in Fig.3 Step 308, associated with the control model 116 – as in ¶[0040] "... The method 300 may further include collecting 306 data for training and validation of the control model 116. As noted above, this may include collecting some or all of the data described above with respect to the feedback records 126. As noted above, this may include collecting sensor data as well as user feedback...."; [0048] "... The SRSM a relates desired output, positive user feedback to inputs such as sensor data (vehicle state and environmental factors) and control actions taken by the autonomous vehicle...."; discussion on SRSM in [0061]-[0077] ),
the second set of input data points being determined, for which an estimate of a margin between the first prediction statistic and a second prediction statistic for predictions for a result of the experiment, which is to be expected for the first set of input data points when carrying out the experiment using the technical system or using the model for the technical system, is smaller than for another second set of input data points (Jiang: margin is the threshold difference between the validation data sets (second data set) and training data sets (first data sets) as discussed in [0050], Fig.3 steps 310 and 312, where the subsets are iteratively selected to make sure they are above a satisfaction threshold; the subsets (second set of input data) are further discussed in [0049] [0056]-[0058]) ; and carrying out the experiment using the second set of input data points at the technical system or at the model of the technical system (Jiang: Fig.3 step 312, 314, 316; [0051]-[0052]) .
Regarding Claim 2
Jiang teaches The method as recited in claim 1, wherein the second set of input data points is selected from the first set of input data points (Jiang: [0056]; [0049] "... A portion of the data from step 306, e.g. 10 percent or some other portion of the feedback records 126, may be held back and used at step 310 to evaluate the SRSMs....") .
Regarding Claim 3
Jiang teaches The method as recited in claim 1, wherein the technical system is a computer-controlled machine, the computer-controlled machine being a robot or an at least semi-autonomous vehicle or a drive train or a manufacturing machine or a domestic appliance or a tool or an access control system or a personal assistance system (Jiang: Abstract showing technical system to be autonomous vehicle) .
Regarding Claim 4
Jiang teaches The method as recited in claim 1, wherein a set of scenarios, which characterize in each case a road characteristic (Jiang : [0044]-[0046]) including a road curvature (Jiang: [0045]) , and/or a traffic characteristic including a traffic density, and/or a weather condition, is predefined by one input data point each from the first set of input data points (Jiang: [0058] "... [0058] Performing 304 DOE may include using a combination of Latin Hypercube sampling (LHS) and Adaptive Sampling (AS) to design the input settings of the experiments, e.g., weather, road conditions, passengers' attributes, etc. FIG. 8 provides an illustrative example of LHS design with 16 sample points over a two-dimensional input space {x.sub.1, x.sub.2}....") , a set of scenarios, which characterizes in each case a road characteristic including a road curvature, and/or a traffic characteristic including a traffic density, and/or a weather condition, being predefined by one input data point each from the second set of input data points for the experiment (Jiang: 2nd set of points is also a subset as disclosed in [0056] and would share attributes of the inputs as described in mapping [0044]-[0046], [0058]) .
Regarding Claim 5
Jiang teaches The method as recited in claim 1, wherein the technical system includes a vehicle (Jiang: [0026] "... The control model 116 as generated or updated according to the methods described herein may be propagated to various autonomous vehicles, which may then perform autonomous driving according to the control model 116. In some embodiments, the control model 116 may correspond to a particular make and model of vehicle (e.g. Ford Escape) or a particular class of vehicle (e.g., crossover SUV)....") , a result of the experiment including a distance of the vehicle from a center of a lane2 or to other road users3 (Jiang: [0048] "... [0022] The feedback record 126 may record or be associated with a particular location 128c, i.e. the location at which the driving maneuver that is the subject of the feedback record occurred. The location may be a range of locations, e.g. defining a stretch of road traversed; the inlet, apex, and or outlet of a turn; or other range of locations. ..." [0023]), or the result includes an emission or the vehicle or range of the vehicle.
Regarding Claim 6
Jiang teaches The method as recited in claim 1, wherein: i) a result of the experiment is detected (Jiang: [0022]-[0023] the result is also feedback/sensor data which is detected based on sensor) , and/or ii) an instruction for activating the technical system or an instruction for changing the technical system is determined and/or output as a function of the result of the experiment, and/or iii) the technical system is activated or changed as a function of the result of the experiment (Jiang: Fig.3 output is updated controller) , and/or iv) the substitute model is improved as a function of the result of the experiment (Jiang: Fig.3 Updating RSM is iterative process) .
Regarding Claim 7
Jiang teaches The method as recited in claim 1, wherein an estimate of the second prediction statistic is determined using a Gaussian process and/or an estimate of the first prediction statistic is determined using a Gaussian process (Jiang: Abstract; [0066]-[0070]) .
Regarding Claim 8
Jiang teaches The method as recited in claim 7, wherein the Gaussian process defines a mean value function and a covariance function (Jiang: [0068]
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), the mean value function mapping input data points onto average output data points (Jiang: [0066]-[0070] mean function) , the covariance function mapping the input data points onto covariances between the output data points (Jiang: as covariance function in [0068]) , which are assigned to the input data points, the mean value function and/or the covariance function being adapted to pairs of input data points and output data points (Jiang see [0067] x and x as pair in the GP model) , which are observed when carrying out the experiment using the technical system or using the model for the technical system (Jiang: [0066]-[0070] – inputs gathered as sensor and feedback data) .
Regarding Claim 9
Jian teaches A computer-implemented method for determining input data points for an experiment, which is implementable using a technical system or using a model of the technical system, the method comprising the following steps: predefining a first set of input data points for the experiment is predefined; determining a second set of input data points for the experiment as a function of the first set of input data points, a substitute model for the technical system being configured to determine, as a function of the second set of input data points, predictions for a result of the experiment for a first prediction statistic, which is to be expected for the second set of input data points when carrying out the experiment using the technical system or using the model for the technical system, the second set of input data points being determined, for which an estimate of a margin between the first prediction statistic and a second prediction statistic for predictions for a result of the experiment, which is to be expected for the first set of input data points when carrying out the experiment using the technical system or using the model for the technical system, is smaller than for another second set of input data points in a similar manner as claim 1 above. This claim does not have the last limitation of claim 1 and is a subset which is rejected in similar manner as claim 1.
Regarding Claim 11
Jiang teaches The device as recited in claim 10, further comprising: an interface (Jiang: Fig. 4 "... illustrates an interface for receiving passenger feedback in accordance with an embodiment of the present invention...") configured: i) to predefine input data points for carrying out an experiment at the technical system or at the model of the technical system (Jiang: [0077] "... [0077] To obtain a relationship between safety S and the input variable x, one may conduct computer simulations of the testing cycle (i.e. using the sensor data and control actions indicated in the feedback records 126) and determine whether any unsafe conditions occurred....") , and/or ii) to detect a result of the experiment carried out at the technical system or at the model of the technical system (Jiang: [0041]-[0047]) , and/or iii) to output an instruction for activating the technical system or an instruction for changing the technical system as a function of a result of the experiment carried out at the technical system or at the model of the technical system (Jiang: Fig.3 elements 314/316 outputting the instructions to control the vehicle based on optimization performed based on SRM ) .
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Conclusion
All claims are rejected.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Examiner’s Note: Examiner has cited particular columns and line numbers in the references applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the teachings of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant in preparing responses, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
In the case of amending the claimed invention, Applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for proper interpretation and also to verify and ascertain the metes and bounds of the claimed invention.
Communication
Any inquiry concerning this communication or earlier communications from the examiner should be directed to AKASH SAXENA whose telephone number is (571)272-8351. The examiner can normally be reached Mon-Fri, 7AM-3:30PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, RYAN PITARO can be reached on (571) 272-4071. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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AKASH SAXENA
Primary Examiner
Art Unit 2188
/AKASH SAXENA/Primary Examiner, Art Unit 2188 Thursday, September 3, 2026
1 See specification [0010] [0047]-[0074]
2 Also see US 20230206136 A1 by Jia; Bin Fig.11-13 (Source: L22)
3 Also see US 20210276572 A1 by Du; Mingbo et al. Fig.7 (Source: L22)
Prosecution Insights