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 .
Claim Objections
Claims objected to because of the following informalities:
Regarding Claim 1, it is suggested to replace “,” with “;” at the end each of limitations. Appropriate correction is required.
Claim Interpretation
Regarding Claim 1, this claim recites the limitation “wherein the technical system has different components that are adjustable by the system parameters”. In particular, claim 1 recites contingent limitations (See MPEP 2111.04 II). “The broadest reasonable interpretation of a method (or process) claim having contingent limitations requires only those steps that must be performed and does not include steps that are not required to be performed because the condition(s) precedent is not met. For example, assume a method claim requires step A if a first condition happens and step B if a second condition happens. If the claimed invention may be practiced without either the first or second condition happening, then neither step A or B is required by the broadest reasonable interpretation of the claim. If the claimed invention requires the first condition to occur, then the broadest reasonable interpretation of the claim requires step A. If the claimed invention requires both the first and second conditions to occur, then the broadest reasonable interpretation of the claim requires both steps A and B.”
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 1-9 are rejected under 35 U.S.C. 101 because 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: This part of the eligibility analysis evaluates whether the claim falls within any statutory category. MPEP 2106.03.
The claim is to a computer-implemented method, i.e. one of the statutory categories.
Step 2A prong one: This part of the eligibility analysis evaluates whether the claim recites a judicial exception. As explained in MPEP 2106.04(11) and the October 2019 Update, a claim "recites" a judicial exception when the judicial exception is "set forth" or "described" in the claim.
The claim recites:
“providing a cost function for the purpose of determining updated system parameters of the technical system, wherein the technical system has different components that are adjustable by the system parameters, and wherein, when the system parameters are set, the technical system generates different output values for the different components,
determining, by the processor, a function space, wherein the function space corresponds to a set of functions in which the cost function lies,
generating, by the processor, a plurality of probability functions based on the historical system parameters and corresponding historical output values using one or more rules, wherein each of the probability functions indicates the probability with which the rule is satisfied by any cost function from the function space,
combining, by a computer system of which the processor and the memory are a part, all probability functions in order to determine the cost function by maximizing increasing overall probability of all rules,”
These limitations recite concepts that can be practically performed in the human mind but for the recitation of generic computer components. Thus, the limitations fall into the “Mental Processes” grouping of abstract ideas. (Step 2A prong one: YES).
Step 2A prong two: 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 (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application. 2019 PEG Section lll{A){2), 84 Fed. Reg. at 54-55.
This judicial exception is not integrated into a practical application because: Besides the abstract idea, the claim recites the additional limitations of:
“A computer-implemented method for determining updated system parameters of a technical system using a cost function, the method comprising:
receiving, by a processor from memory, historical system parameters and corresponding historical output values for the individual ones of the different components,
receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values,
updating, by the computer system, the system parameters given the cost function, and
outputting, by the computer system, the updated system parameters in order to adjust the different components of the technical system.”
The computer-implemented method, the processor from the memory, and the computer system are a recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Thus, these limitations represent no more than mere instructions to apply the judicial exceptions on a computer.
The limitations “receiving, by a processor from memory, historical system parameters and corresponding historical output values for the individual ones of the different components,” and “receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values,” merely add insignificant extra-solution activity to the judicial exception because they claim mere data gathering.
The limitations “updating, by the computer system, the system parameters given the cost function, and outputting, by the computer system, the updated system parameters in order to adjust the different components of the technical system” do not integrate the invention into a practical application because it’s just “applying” the abstract idea. It can also be viewed as generally linking the use of the judicial exception to a technological environment.
It should be noted that because the courts have made it clear that mere physicality or tangibility of an additional element or elements is not a relevant consideration in the eligibility analysis, the computer-implemented method, the processor from the memory, and the computer system do not affect this analysis. See MPEP 2106.05(1) for more information on this point, including explanations from judicial decisions including Alice Corp. Pty. Ltd. v. CLS Bank lnt'I, 573 U.S. 208, 224-26 (2014).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application and the claim is directed to the judicial exception (Step 2A prong two: NO).
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. MPEP 2106.05
Regarding the additional elements:
The computer-implemented method, the processor from the memory, and the computer system are recited at a high level of generality and are recited as performing generic computer functions routinely used in computer applications. Thus, these limitations represent no more than mere instructions to apply the judicial exceptions on a computer. See MPEP 2106.05(f) Implementing an abstract idea on generic electronic components as a tool to perform an abstract idea does not amount to significantly more. See Elec. Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1355 (Fed. Cir. 2016) (“Nothing in the claims, understood in light of the specification, requires anything other than off-the-shelf, conventional computer, network, and display technology for gathering, sending, and presenting the desired information.”)
The limitations “receiving, by a processor from memory, historical system parameters and corresponding historical output values for the individual ones of the different components,” and “receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values,” represent mere instructions to apply a judicial exception and is recited at high level of generality. These limitation in the claim are thus insignificant extra-solution activity. This is also well-understood, routine, conventional activity (See MPEP 2106.05(d) – receiving or transmitting data over a network.). Kokotov (US 20080021571 A1) discloses receive the historical information and a set of coefficients from the collector. Further, Brummel (US 20150278697 A1) discloses reviewing a set of rules used for automated monitoring of a technical system.
The limitations “updating, by the computer system, the system parameters given the cost function, and outputting, by the computer system, the updated system parameters in order to adjust the different components of the technical system” merely add insignificant extra-solution activity to the judicial exception because it claims mere data outputting. Chen (US 20170286860 A1) discloses update the model parameters based on the gradient of the cost function, e.g., according to a gradient-descent algorithm, and return the value of the cost function with the new parameters. Further, Robinson (US 20200356835 A1) discloses update the parameters of the agent to reduce a cost function.
In view of the foregoing, in accord with MPEP 2106.05(d), simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception does not qualify the claim as reciting “significantly more”. Even when considered in combination, these additional elements represent mere instructions to apply an exception and insignificant extra-solution activity, which do not provide an inventive concept (Step 2B: NO). The claim is not patent eligible.
Regarding claims 2-7, under their broadest reasonable interpretation, the limitations of claims 3-4 further defines the computer-implemented method, which have been established to include abstract ideas. There are no additional limitations in the claims to apply, rely on, or use the judicial exception in a manner that would impose a meaningful limit on the judicial exception. Accordingly, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Thus, claims 2-7 are not patent eligible.
Regarding claim 8, the claim has similar limitations as claim 1; moreover, claim 8 recites a computer system, which is generic computer component and does not practically integrate the invention nor amount to significantly more. The claim 8 is not patent eligible.
Dependent claim 9 is the claim have similar limitations as claim 6; therefore, the rejections applied to claim 6 above also apply to claim 9, and as such, it is not patent eligible.
Claim Rejections - 35 USC § 103
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 (i.e., changing from AIA to pre-AIA ) 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 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.
Claim(s) 1 and 8 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang et al. (US20210306201A1 -hereinafter Wang) in view of Brochu et al. (NPL: "A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning." -hereinafter Brochu). Regarding Claim 1, Wang teaches a computer-implemented method for determining updated system parameters of a technical system using a cost function, the method comprising:
providing a cost function for the purpose of determining updated system parameters of the technical system (see [0052]; Wang: “The cost function field 326 defines a cost function for the action. At least some of the disclosed embodiments utilize a cost function defined by the field 326 to determine a cost of invoking the action”), wherein the technical system has different components that are adjustable by the system parameters (see [0158]; Wang: “Examples, as described herein, may include, or may operate on, logic or a number of components, modules, or mechanisms. Modules are tangible entities (e.g., hardware) capable of performing specified operations and may be configured or arranged in a certain manner.”), and wherein, when the system parameters are set, the technical system generates different output values for the different components; (see [0044]; Wang: “Based on the monitored activity and the operational parameters, the network management system is configured to perform one or more actions on one or more of the components of the system 100, at least when particular conditions are detected.”)
receiving, by a processor from memory, historical system parameters and corresponding historical output values for the individual ones of the different components, (see [0056]; Wang: “The injection history table 360 includes an action identifier field 362, injection time field 364, component identifier field 366, and a probability improvement field 368.”)
generating, by the processor, a plurality of probability functions based on the historical system parameters and corresponding historical output values using one or more rules (see [0129]; Wang: “Some embodiments of operation 1335 determine multiple differences in confidence levels or probabilities between multiple pairs of root cause determinations. Some embodiments predict a difference in a probability determination based on prior differences in probability determinations resulting from previous injections of the action. For example, some embodiments examine a history of injections of an action and predict a next probability improvement of injecting the action based on the history of probability differences.”),
updating, by the computer system, the system parameters given the cost function, and (see [0068]; Wang: “In operation 520, an action is selected based on the root cause. As discussed above, a root cause can be associated with multiple possible actions. Operation 520 evaluates the possible actions with respect to their respective cost and probability or confidence of resolving the problem.”)
outputting, by the computer system, the updated system parameters in order to adjust the different components of the technical system. (see [0069]; Wang: “The selected action can include one or more of restarting a software process or component of a network device included in the network system being monitored, resetting an entire network device (e.g. power cycle), adjusting one or more configuration parameters of a network device or software component of a network device, resetting a particular hardware component of a network device (e.g. resetting a network card or chip of a network device while maintaining operation of a GPU of the device)”)
However, Wang does not explicitly teach:
receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values,
determining, by the processor, a function space, wherein the function space corresponds to a set of functions in which the cost function lies,
wherein each of the probability functions indicates the probability with which the rule is satisfied by any cost function from the function space,
combining, by a computer system of which the processor and the memory are a part, all probability functions in order to determine the cost function by maximizing increasing overall probability of all rules,
Brochu from the same or similar field of endeavor teaches:
receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values, (see page 37, first paragraph; Brochu: “Figure 11: Task Hierarchies. Each composite task is a separate SMDP whose policy is optimal given the optimal policies of its subtasks (recursive optimality).” See page 32, paragraph 4; Brochu: “Each task in an HRL hierarchy is a semi-Markov Decision Process [Sutton et al., 1999], that models repeated decision making in a stochastic environment, where the actions can take more than one time step. Formally, an SMDP is defined as a tuple: {S, A, P(s’, N|s,a), R(s,a)} where S is the set of state variables, A is a set of actions, P(s’, N|s,a) is the transition probability of arriving to state s’ in N time steps after taking action a in s, and R(s,a)is the reward received. The solution of this process is a policy π* ϵ A, that selects the action with the highest expected discounted reward in each state.” See page 33, last paragraph: “Recursive optimality, satisfied by MAXQ and RAR, means that each subtask is locally optimal, given the optimal policies of the descendants.”) [The policies read on ‘rules’]
determining, by the processor, a function space (see page 5, last paragraph; Brochu: “Bayesian optimization uses the prior and evidence to define a posterior distribution over the space of functions.), wherein the function space corresponds to a set of functions in which the cost function lies, (see page 5, last paragraph; Brochu: “Bayesian optimization uses the prior and evidence to define a posterior distribution over the space of functions. The Bayesian model allows for an elegant means by which informative priors can describe attributes of the objective function, such as smoothness or the most likely locations of the maximum, even when the function itself is not known.”)
wherein each of the probability functions indicates the probability with which the rule is satisfied by any cost function from the function space, (see page 32, paragraph 4; Brochu: “The function V*(s) is the value of state s when following the optimal policy. Equivalently, the Q* (s,a) function stores the value of taking action a in state s and following the optimal policy thereafter.”)
combining, by a computer system of which the processor and the memory are a part, all probability functions in order to determine the cost function by maximizing increasing overall probability of all rules, (see page 11, second paragraph; Brochu: “The early work of Kushner [1964] suggested maximizing the probability of improvement over the incumbent f(x+) … This function is also sometimes called MPI (for maximum probability of improvement") or \the P-algorithm" (since the utility is the probability of improvement).”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Wang to include Brochu’s features of receiving, by the processor from the memory, a plurality of rules on which the technical system is based and which are based on the different system parameters and their output values, determining, by the processor, a function space, wherein the function space corresponds to a set of functions in which the cost function lies, wherein each of the probability functions indicates the probability with which the rule is satisfied by any cost function from the function space, combining, by a computer system of which the processor and the memory are a part, all probability functions in order to determine the cost function by maximizing increasing overall probability of all rules. Doing so would significantly speed up the learning process. (Brochu, page 31, third paragraph)
Regarding Claim 8, the limitations in this claim is taught by the combination of Wang and Brochu as discussed connection with claim 1.
Claim(s) 2 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Brochu in view of Schneegass et al. (US20090271340A1 -hereinafter Schneegass).
Regarding Claim 2, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein a probability function is generated by the processor based on one rule of the plurality of rules.
Schneegass from the same or similar field of endeavor teaches: wherein a probability function is generated by the processor based on one rule of the plurality of rules. (see [0012]; Schneegass: “the action selection rule that must be learned is a stochastic action selection rule which, for a state of the technical system, specifies a probability distribution for the executable actions.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Wang and Brochu to include Schneegass’s features of a probability function is generated by the processor based on one rule of the plurality of rules. Doing so would maximize the performance of the technical system with reference to the statistical uncertainty. (Schneegass, [0008])
Claim(s) 3-4 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Brochu in view of Ewert (EP1542102A1 -hereinafter Ewert -Note: As the machine translation attached).
Regarding Claim 3, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein the technical system is a physical system in which the system behavior may be changed using freely adjustable system parameters of the plurality of system parameters.
Ewert from the same or similar field of endeavor teaches wherein the technical system is a physical system in which the system behavior may be changed using freely adjustable system parameters of the plurality of system parameters. (see page 4, paragraph 6; Ewet: “In many cases, the technical system may want to change the controlled variable not immediately implement, but requires for a certain time. This behavior will described with a model for the time behavior of the change of the control variable, the can be considered within the scope of the invention in the search strategy.” See page 3, paragraph 8: “For the determination of this suboptimal future course of the controlled variable is now used a search strategy, in which simplified assumptions about the possibilities the change in the controlled variable can be specified.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Klenske and Brochu to include Ewert’s features of the technical system is a physical system in which the system behavior may be changed using freely adjustable system parameters of the plurality of system parameters. Doing so would perform increases in the setpoint as early as possible and reductions as late as possible. (Ewert, page 11, paragraph 4)
Regarding Claim 4, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein certain manipulated variables of the different components are mechanically, electrically or digitally alterable using the freely adjustable parameters. (see page 3, paragraph 9; Ewert: “In the case of a one-dimensional control variable, the possibilities of change are formed in the simplest case by three values, for example by an increase A + of the manipulated variable per unit time, a reduction Δ- of the manipulated variable per unit time (eg Δ- = - Δ +) and the value zero (constant manipulated variable).”)
Ewert from the same or similar field of endeavor teaches wherein certain manipulated variables of the different components are mechanically, electrically or digitally alterable using the freely adjustable parameters. (see page 3, paragraph 9; Ewert: “In the case of a one-dimensional control variable, the possibilities of change are formed in the simplest case by three values, for example by an increase A + of the manipulated variable per unit time, a reduction Δ- of the manipulated variable per unit time (eg Δ- = - Δ +) and the value zero (constant manipulated variable).”)
The same motivation to combine Wang, Brochu, and Ewert a set forth for Claim 3 equally applies to Claim 4.
Claim(s) 5-7 and 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Wang in view of Brochu in view of Gustafsson et al. (US20060136184A1 -hereinafter Gustafsson)
Regarding Claim 5, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein the rules are weighted.
Gustafsson from the same or similar field of endeavor teaches wherein the rules are weighted. (see [0037]; Gustafsson: “In some embodiments, the contribution of each respective rule in the plurality of rules to the biopolymer sequence space is independently weighted by a rule weight in a plurality of rule weights corresponding to the respective rule.”)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to modify the teaching of Wang and Brochu to include Gustafsson’s features of the rules are weighted. Doing so would improve the accuracy with which the system can identify beneficial substitutions. (Gustafsson, [0094])
Regarding Claim 6, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein the rules are determined using an expert system.
Gustafsson from the same or similar field of endeavor teaches wherein the rules are determined using an expert system. (see [0125]; Gustafsson: “Some embodiments of expert system 100 include knowledge base editor 114 to allow an administrator to add, delete, or modify components of knowledge base 108 including, but not limited to, rules 120.”)
The same motivation to combine Wang, Brochu, and Gustafsson a set forth for Claim 5 equally applies to Claim 6.
Regarding Claim 7, the combination of Wang and Brochu teaches all the limitations of claim 1 above; however, it does not explicitly teach wherein different output values are weighted.
Gustafsson from the same or similar field of endeavor teaches wherein different output values are weighted. (see [0541]; Gustafsson: “f) Repeat steps c-e. However, for each new set of variants that is synthesized and tested, compare the measured activity values for each variant with the values predicted by each sequence-activity correlating method. Use this information to weight and combine the different sequence-activity modeling methods so that the predictions more closely match the measured values. (FIG. 2, step 10)”)
The same motivation to combine Wang, Brochu, and Gustafsson a set forth for Claim 5 equally applies to Claim 7.
Regarding Claim 9, the limitations in this claim is taught by the combination of Wang, Brochu, and Gustafsson as discussed connection with claim 6.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Klenske (US11762346B2) discloses creating a control process for a technical system using a Bayesian optimization method, the control process being created and executable based on model parameters of a control model, the following steps being performed in order to optimize the control process.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VI N TRAN whose telephone number is (571)272-1108. The examiner can normally be reached Mon-Fri 9:00-5:00.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, ROBERT FENNEMA can be reached at (571) 272-2748. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/V.N.T./Examiner, Art Unit 2117
/ROBERT E FENNEMA/Supervisory Patent Examiner, Art Unit 2117
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