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 instant application filed 07/29/2024.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 07/29/24 and 06/23/25 are being considered by the examiner.
Claim Objections
Claim 11 is objected to because of the following informalities: an information processing device comprising: a memory; and a . Appropriate correction is required.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Regarding claim 1:
Step 1: The claim recites a method which falls into the statutory category of process.
Step 2A Prong 1: The claim recites abstract ideas: the arithmetic method comprising: a first processing of repeating generation evolution by a first optimization algorithm that causes generation evolution by a genetic algorithm such that an objective function satisfies a predetermined condition by giving variations to an input variable for each individual; and a second processing of repeating generation evolution by a second optimization algorithm that repeats to give variations to an input variable for each individual after a predetermined generation obtained by the first processing to obtain an individual a plurality of times, and causes generation evolution by a genetic algorithm such that a statistical value of an objective function of each individual obtained satisfies a predetermined condition. The claim essentially recites an algorithm involving objective functions, genetic algorithms, statistical values, and satisfying conditions and as such recites a series of mathematical calculations and concepts.
Step 2A Prong 2: Claim 1 does not integrate the abstract idea into a practical application since the only additional element is a computer which is merely instructions to apply the abstract idea with a generic computer (MPEP 2106.05(f)).
Step 2B: Claim 1 does not include additional elements that are sufficient to amount to
significantly more than a judicial exception when taken alone or in combination given the computer merely applies the abstract idea (MPEP 2106.05(f)). The claim merely recites an algorithm without demonstrating any improvement to technology or anything significantly more; claim 1 is not patent eligible.
Regarding claim 2, the rejection of claim 1 is incorporated, further the claim recites wherein, in the second processing, for an individual of the predetermined generation, to give variations to an input variable to obtain an individual is repeated a plurality of times, and generation evolution is caused such that a statistical value of an objective function of each obtained individual satisfies a predetermined condition. This limitation amounts to more specifics of the abstract idea given it provides more details on how the second processing and optimization algorithm work. Claim 2 is not patent eligible.
Regarding claim 3, The rejection of claim 1 is incorporated, further the claim recites wherein, in the first processing, generation evolution is repeated up to a generation that exceeds the predetermined generation, and in the second processing, to extract an individual after the predetermined generation obtained by the second optimization algorithm and to give variations to an input variable for the extracted individual to obtain an individual is repeated a plurality of times, and generation evolution is caused such that a statistical value of an objective function of each obtained individual satisfies a predetermined condition. This limitation amounts to more specifics of the abstract ideas given it merely provides more details on how the first and second processing work. Claim 3 is not patent eligible.
Regarding claim 4, the rejection of claim 1 is incorporated, further the claim recites wherein an average value and variance are used as the statistical values. This limitation amounts to more specifics of the abstract idea given it merely describes the statistical values used, additional mathematical concepts. Claim 4 is not patent eligible.
Regarding claim 5, the rejection of claim 1 is incorporated, further the claim recites wherein the computer executes processing of causing a display device to display an individual obtained by repeating generation evolution in the second processing. This limitation amounts to insignificant extra-solution activity: mere data gathering (MPEP 2106.05(g)). The claim does not include any additional elements that amount to an integration of the judicial exception into a practical application, nor to significantly more than the judicial exceptions given the limitation merely recites displaying data which is considered well-understood, routine, conventional (MPEP§2106.05(d)).
Regarding claims 6-10, the limitations are essentially the same as claims 1-5 with the addition of a non-transitory computer-readable medium which falls into the statutory category of manufacture. Additionally, the non-transitory computer-readable medium is merely instructions to apply the abstract idea with a generic computer (MPEP 2106.05(f)). As such, the claims do not include additional elements that are sufficient to amount to significantly more than a judicial exception when taken alone or in combination given the non-transitory computer-readable medium merely applies the abstract idea (MPEP 2106.05(f)).
Regarding claims 11-15, the limitations are essentially the same as claims 1-5 with the addition of an information processing device comprising: a memory; and a process coupled to the memory which falls into the statutory category of machine. Additionally, the information processing device comprising: a memory; and a processor coupled to the memory is merely instructions to apply the abstract idea with a generic computer (MPEP 2106.05(f)). As such, the claims do not include additional elements that are sufficient to amount to significantly more than a judicial exception when taken alone or in combination given the information processing device merely applies the abstract idea (MPEP 2106.05(f)).
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-4, 6-9, 11-14 are rejected under 35 U.S.C. 103 as being unpatentable over Fritz (Genetic Algorithm Based Robust and Optimal Path Planning for Sample-Return Mission from an Asteroid on an Earth Fly-By Trajectory) in view of Hacker (ROBUST DESIGN THROUGH THE USE OF A HYBRID GENETIC ALGORITHM).
Regarding claim 1, Fritz teaches a first processing of repeating generation evolution by a first optimization algorithm that causes generation evolution by a genetic algorithm such that an objective function satisfies a predetermined condition (Section 2, Optimization can be performed in two rounds: first to find the optimum trajectory where the mission objective is to minimize the ∆V through optimal trajectory and maneuvers….This will be achieved using a genetic algorithm due to their effective nature when exploring large, non-linear search domains, Fig 1, predetermined condition is convergence) by giving variations to an input variable for each individual (Section 2.2, For each gene in the chromosomes a random number is generated between (0, 1). If it is less than 0.05, that particular gene has a random value added to it. This random value is generated from a normal distribution whose range is unique to that gene); and a second processing of repeating generation evolution by a second optimization algorithm (Section 1, a second application of the genetic algorithm for optimization) that repeats to give variations to an input variable for each individual after a predetermined generation obtained by the first processing to obtain an individual a plurality of times (Section 2.2, For the purposes of termination of the Genetic Algorithm, a convergence of total fitness, within a specified tolerance, for over 30 generations or surpassing a maximum number of generations is used, Fig 1, the claim does not specify if the generation is predetermined for the first processing or the second; therefore, predetermined generation is the generation at which the pool has been converged which is obtained through the first processing and is predetermined before the second processing, Section 2.4.1, instead of operating uniformly across the inputs, the perturbations were implemented as a normally distributed randomized error with a maximum 0.1% error on the magnitude and a 0.5◦ offpointing of the first (outbound) ∆V maneuver. This first maneuver was deemed the most critical as it is responsible for setting the spacecraft on a rendezvous trajectory to the asteroid. 50 Monte Carlo simulations were performed on each trial solution, Fig 1, second stage begins when monte Carlo is activated, it is run on every output of the first stage a plurality of times and includes variations (perturbations)).
Fritz fails to teach and causes generation evolution by a genetic algorithm such that a statistical value of an objective function of each individual obtained satisfies a predetermined condition
Hacker teaches and causes generation evolution by a genetic algorithm such that a statistical value of an objective function of each individual obtained satisfies a predetermined condition (Section 2, The general procedure for using Monte Carlo simulation in robust design in this work is as follows….. Determine the distribution characteristics that uniquely identify it (e.g., µx and σx 2 for a normal distribution. Specify how many points to sample or specify a required confidence level for the estimates of mean and variance (i.e., take 50 samples or sample until a specified confidence level is achieved in the estimate of error). Use the estimates of mean and variance of the performance as the objectives in the optimization.)
Hacker is analogous to the claimed invention because it is in the field of Robust design using Monte Carlo. Therefore, it would have obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have substituted the general procedure of using Monte Carlo in robust design found in Hacker into Fritz because Fritz already discusses the optimization process attempting to center and tighten the scatter (which is produced from the Monte Carlo simulations done on each trial target) which can effectively be done by requiring a confidence level for the mean and variance of the Monte Carlo simulations given center is essentially equivalent to mean and spread to variance (Fritz section 2.4.1, 50 Monte Carlo simulations were performed on each trial solution. This resulted in 50 position errors at the end of the first leg of the mission. These errors were RSS’d into a single value that represented the tendency of that solution to scatter in the presence of propulsive perturbations…. The optimization process attempts to center and tighten the scatter).
Regarding claim 2, Fritz in view of Hacker teaches the method of claim 1, further Hacker teaches wherein, in the second processing, for an individual of the predetermined generation, to give variations to an input variable to obtain an individual is repeated a plurality of times, and generation evolution is caused such that a statistical value of an objective function of each obtained individual satisfies a predetermined condition (Section 2, The general procedure for using Monte Carlo simulation in robust design in this work is as follows….. Determine the distribution characteristics that uniquely identify it (e.g., µx and σx 2 for a normal distribution. Specify how many points to sample or specify a required confidence level for the estimates of mean and variance (i.e., take 50 samples or sample until a specified confidence level is achieved in the estimate of error). Use the estimates of mean and variance of the performance as the objectives in the optimization). The rationale for using the Monte Carlo simulation described in Hacker is explained in the rejection for claim 1.
Regarding claim 3, Fritz in view of Hacker teaches the method of claim 1, further Fritz teaches wherein, in the first processing, generation evolution is repeated up to a generation that exceeds the predetermined generation, and in the second processing, to extract an individual after the predetermined generation obtained by the second optimization algorithm and to give variations to an input variable for the extracted individual to obtain an individual is repeated a plurality of times (Section 2.2, For the purposes of termination of the Genetic Algorithm, a convergence of total fitness, within a specified tolerance, for over 30 generations or surpassing a maximum number of generations is used, Fig 1, predetermined generation is the generation at which the pool has been converged which is obtained through the first processing; however the first algorithm goes on for 30 more generations after that predetermined generation, Section 2.4.1, instead of operating uniformly across the inputs, the perturbations were implemented as a normally distributed randomized error with a maximum 0.1% error on the magnitude and a 0.5◦ offpointing of the first (outbound) ∆V maneuver. This first maneuver was deemed the most critical as it is responsible for setting the spacecraft on a rendezvous trajectory to the asteroid. 50 Monte Carlo simulations were performed on each trial solution, Fig 1, second stage begins when Monte Carlo is activated, it is run on every output of the first stage a plurality of times and includes variations (perturbations)).
Furthermore, Hacker teaches and generation evolution is caused such that a statistical value of an objective function of each obtained individual satisfies a predetermined condition (Section 2, The general procedure for using Monte Carlo simulation in robust design in this work is as follows…... Determine the distribution characteristics that uniquely identify it (e.g., µx and σx 2 for a normal distribution. Specify how many points to sample or specify a required confidence level for the estimates of mean and variance (i.e., take 50 samples or sample until a specified confidence level is achieved in the estimate of error). Use the estimates of mean and variance of the performance as the objectives in the optimization). The rationale for using the Monte Carlo simulation described in Hacker is explained in the rejection for claim 1.
Regarding claim 4, Fritz in view of Hacker teaches the method of claim 1, further Hacker teaches wherein an average value and variance are used as the statistical values (Section 2, (i.e., take 50 samples or sample until a specified confidence level is achieved in the estimate of error). Use the estimates of mean and variance of the performance as the objectives in the optimization). The rationale for using the Monte Carlo simulation described in Hacker is explained in the rejection for claim 1.
Regarding claims 6-9, the claims teach essentially the same limitations as claims 1-4, with the addition of a non-transitory computer readable recording medium which is implied in Fritz through the mention of code and computing time (Section 2.4.1). As such, the claims are rejected for at least the same reasons.
Regarding claims 11-14, the claims teach essentially the same limitations, with minor rewording, as claims 1-4, with the addition of a memory and process which is implied in Fritz through the mention of code and computing time (Section 2.4.1). As such, the claims are rejected for at least the same reasons.
Claim(s) 5, 10, and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Fritz in view of Hacker as applied to claims 1, 6, and 11 above, and further in view of Taylor (US20080270331A1).
Regarding claim 5, Fritz in view of Hacker teaches the method of claim 1 but fails to teach wherein the computer executes processing of causing a display device to display an individual obtained by repeating generation evolution in the second processing.
Taylor teaches wherein the computer executes processing of causing a display device to display an individual obtained by repeating generation evolution in the second processing (Par.0062, Preferably the highest ranked solution is displayed via a monitor or other display device to the planner, and information about all the solutions in each generation are stored so that the planner can review and/or use solutions from the most recent completed generation or previously-completed generations).
Taylor is analogous to the claimed invention because it is in the field of using genetic algorithms to find solutions. Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have used the display device in Taylor alongside the combination of Fritz and Hacker to allow users to view solutions.
Regarding claim 10, the claim teaches essentially the same limitation as claim 5, with the addition of a non-transitory computer readable recording medium which is implied in Fritz through the mention of code and computing time (Section 2.4.1) and mentioned in Taylor (Par. 0008).
Regarding claim 15, the claim teaches essentially the same limitation as claim 5, with the addition of a memory and processor which is implied in Fritz through the mention of code and computing time (Section 2.4.1) and mentioned in Taylor (Par. 0008).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to NATNAEL A ASEGDEW whose telephone number is (571)270-0407. The examiner can normally be reached 7:30-5.
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/NATNAEL A ASEGDEW/ Examiner, Art Unit 2122
/MICHAEL H HOANG/ PRIMARY EXAMINER, Art Unit 2122
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