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 .
Election/Restrictions
Applicant’s election without traverse of Group 1, Species 1 in the reply filed on 12/29/2025 is acknowledged.
Claims 11-13, 15, 17-18, and 20 are withdrawn from further consideration pursuant to 37 CFR 1.142(b) as being drawn to a nonelected invention, there being no allowable generic or linking claim. Election was made without traverse in the reply filed on 12/29/2025.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1-10, 14, 19, and 21 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding claims 1 and 19, “the information gain” lacks antecedent basis in the claim.
Regarding claim 1, the second recitation of “a function of the prediction” renders the claim indefinite because it is unclear if antecedence is claimed back to the first recitation or if the second recitation is connected to “or as a function of a value of the first variable”, the “or” being exclusive.
Regarding claims 1 and 14, the definition of the first leaf is unclear because it is recited as being in both the right and left subtree. As best understood by the Examiner, the right and left subtrees are independent branches from a single node and thereby have independent leaves thereon.
Regarding claim 2, the definition of the second leaf is unclear because it is recited as being in both the right and left subtree. As best understood by the Examiner, the right and left subtrees are independent branches from a single node and thereby have independent leaves thereon.
Regarding claim 4, “the subtree of the node” lacks antecedent basis in the claims.
Claims 2-10, 19, and 21 are indefinite by virtue of dependency on an indefinite base claim.
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 1-10, 14, 19 and 21 rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 1 is drawn to a process.
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 1 recites the following abstract ideas:
“mapping a first variable of the technical system onto a prediction for a second variable of the technical system using a Gaussian process…the Gaussian process, depending on a sum of a first Gaussian process which is weight with a first weight function, is determined with a second Gaussian process, the first Gaussian process is configured to map the first variable onto a first prediction for the second variable, and the second Gaussian process is configured to map the first variable onto a second prediction for the second variable, sub-domains of a domain and/or a value range of the Gaussian process are determined depending on a numerical representation of a binary tree with leaves and nodes, a first leaf of the leaves is assigned to the first Gaussian process, the nodes are each assigned a vector representing one of the sub-domains” – Mapping can be considered an observation, evaluation, judgement, or opinion, i.e. a concept performed in the human mind. See MPEP 2106.04(a)(2), III, and the Gaussian processes and their accompanying specifics are a mathematical concept.
“operating the technical system as a function of the prediction or as a function of a value of the first variable, for which a measure for the information gain, defined as a function of the prediction, indicates a greater information gain than for a different value of the first variable” – Operating a system based on a judgement as to whether an information gain is higher is an observation, evaluation, judgement, or opinion, i.e. a concept performed in the human mind. See MPEP 2106.04(a)(2), III.
“the nodes are each assigned a first weight that depends on the first variable and the vector assigned to the respective node, and the first weight function is determined depending on the first weights of the nodes in a left subtree of which the first leaf is located and/or each of the nodes is assigned a second weight, depending on the first variable and the vector assigned to the node and the first weight function is determined depending on the second weights of the nodes in a right subtree of which the first leaf is located” – The assignment of values can be considered an observation, evaluation, judgement, or opinion, i.e. a concept performed in the human mind. See MPEP 2106.04(a)(2), III.
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 1 recites the following additional elements:
“A computer-implemented method…” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Step 2B: Does the claim recite additional elements that amount ot significantly more than the judicial exception?
No. Claim 1 recites the following additional elements:
“A computer-implemented method…” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Regarding claims 2-9, the assignment of variables and/or weights, their descriptions, and the defining features of the Gaussian process can be considered observation, evaluation, judgement, or opinion, i.e. a concept performed in the human mind. See MPEP 2106.04(a)(2), III, or mathematical concepts. No additional elements are recited.
Claim 10
Step 1: Is the claim to a process, machine, manufacture, or composition of matter?
Yes. Claim 10 is drawn to a process.
Step 2A, Prong One: Does the claim recite an abstract idea, law of nature, or natural phenomenon?
Yes. Claim 10 recites the following abstract ideas:
The abstract ideas of claim 1
Step 2A, Prong Two: Does the claim recite additional elements that integrate the judicial exception into a practical application?
No. Claim 10 recites the following additional elements:
“wherein the first variable is a target variable for an actuator of the technical system or a target variable for an actuator of the technical system is determined depending on the first variable, wherein the technical system is a computer controlled machine, the computer controlled machine including (i) a robot, or (ii) a vehicle, or (iii) a household appliance, or (iv) a tool powered electrically or pneumatically or hydraulically or by an internal combustion engine, or (v) a fabrication machine, or (vi) a personal assistance system, or (vii) a locking system.” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Step 2B: Does the claim recite additional elements that amount ot significantly more than the judicial exception?
No. Claim 10 recites the following additional elements:
“wherein the first variable is a target variable for an actuator of the technical system or a target variable for an actuator of the technical system is determined depending on the first variable, wherein the technical system is a computer controlled machine, the computer controlled machine including (i) a robot, or (ii) a vehicle, or (iii) a household appliance, or (iv) a tool powered electrically or pneumatically or hydraulically or by an internal combustion engine, or (v) a fabrication machine, or (vi) a personal assistance system, or (vii) a locking system.” - merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
Claims 14, 19, and 21 are ineligible for the same reasons as claims 1 (claims 14 and 19) and 10 (claim 21), where the additional element of the processor system and memory in claim 14 fall under merely reciting the words “apply it” (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea. See MPEP 2106.05(f).
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-2, 4-5, 14, 19, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kitanov (US20200272171A1) in view of Shen (Shen, Yirong, Matthias Seeger, and Andrew Ng. "Fast gaussian process regression using kd-trees." Advances in neural information processing systems 18 (2005).)
Regarding claim 1, Kitanov teaches a computer-implemented method of operating a technical system (¶8, “The present invention provides an application of a topological approach to Belief Space Planning (BSP) to solving multi-robot active Simultaneous Localization and Mapping (SLAM) problems.”), comprising:
mapping a first variable of the technical system onto a prediction for a second variable of the technical system using a Gaussian process (¶20, “Assuming the belief is modeled by a multivariate Gaussian distribution…the objective function becomes:”; and
operating the technical system as a function of the prediction or as a function of a value of the first variable, for which a measure for the information gain, defined as a function of the prediction, indicates a greater information gain than for a different value of the first variable (¶20, “Notice that minimizing the global entropy (2) corresponds to maximizing the total information gain obtained by executing this trajectory, i.e. maximizing the estimation accuracy.”).
Kitanov does not teach wherein
the Gaussian process, depending on a sum of a first Gaussian process which is weighted with a first weight function, is determined with a second Gaussian process;
first Gaussian process is configured to map the first variable onto a first prediction for the second variable, and the second Gaussian process is configured to map the first variable onto a second prediction for the second variable,
sub-domains of a domain and/or a value range of the Gaussian process are determined depending on a numerical representation of a binary tree with leaves and nodesi,
a first leaf of the leaves is assigned to the first Gaussian process,
the nodes are each assigned a vector representing one of the sub-domain
the nodes are each assigned a first weight that depends on the first variable and the vector assigned to the respective node, and the first weight function is determined depending on the first weights of the nodes in a left subtree of which the first leaf is located, and/or each of the nodes is assigned a second weight, depending on the first variable and the vector assigned to the node; and
the first weight function is determined depending on the second weights of the nodes in a right subtree of which the first leaf is located.
Shen teaches
the Gaussian process, depending on a sum of a first Gaussian process which is weighted with a first weight function, is determined with a second Gaussian process (§3.1, “The computations in Equation 2 can be thought of as a weighted sum…”);
first Gaussian process is configured to map the first variable onto a first prediction for the second variable, and the second Gaussian process is configured to map the first variable onto a second prediction for the second variable (Figure 1: Level 2 shows first and second Gaussian processes (the red rectangles) mapping the first variable onto first and second predictions (one prediction per red rectangle) which are then summed to make the prediction, §3.2,
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which can be calculated by using the right and left subtree sums),
sub-domains of a domain and/or a value range of the Gaussian process are determined depending on a numerical representation of a binary tree with leaves and nodes (see Figure 1)
a first leaf of the leaves is assigned to the first Gaussian process (See Figure 1, Level 2, which has two leaves one for each Gaussian process),
the nodes are each assigned a vector representing one of the sub-domain (Equation 3, x*)
the nodes are each assigned a first weight that depends on the first variable and the vector assigned to the respective node (Equation 3, K(x*,xi)), and the first weight function is determined depending on the first weights of the nodes in a left subtree of which the first leaf is located, and/or each of the nodes is assigned a second weight, depending on the first variable and the vector assigned to the node (Equation 3, where the function can be considered a weight function); and
the first weight function is determined depending on the second weights of the nodes in a right subtree of which the first leaf is located (Equation 3, each of the left and right subtree are used in calculating the weighted sum).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Kitanov to include
the Gaussian process, depending on a sum of a first Gaussian process which is weighted with a first weight function, is determined with a second Gaussian process;
first Gaussian process is configured to map the first variable onto a first prediction for the second variable, and the second Gaussian process is configured to map the first variable onto a second prediction for the second variable,
sub-domains of a domain and/or a value range of the Gaussian process are determined depending on a numerical representation of a binary tree with leaves and nodesi,
a first leaf of the leaves is assigned to the first Gaussian process,
the nodes are each assigned a vector representing one of the sub-domain
the nodes are each assigned a first weight that depends on the first variable and the vector assigned to the respective node, and the first weight function is determined depending on the first weights of the nodes in a left subtree of which the first leaf is located, and/or each of the nodes is assigned a second weight, depending on the first variable and the vector assigned to the node; and
the first weight function is determined depending on the second weights of the nodes in a right subtree of which the first leaf is located.
In order to provide fast computation without sacrificing accuracy (see §1 of Shen, “This approximation can sometimes be made orders of magnitude faster than the direct computation, without sacrificing much in terms of accuracy”).
Regarding claim 2, Kitanov as modified teaches all of the limitations of claim 1, wherein
The second Gaussian process is weighted with a second weight function, wherein the second Gaussian process is assigned a second leaf of the leaves that is different from the first leaf (see Figure 1 and Equation 3, where the second process can be for the other of the two red rectangles), wherein the second weight function is determined depending on the second weights of the nodes in the right subtree of which the second leaf is located (Equation 3, the second weight function is dependent on the weights in its respective subtree, see Figure 1).
Regarding claim 4, Kitanov as modified teaches all of the limitations of claim 1, wherein:
for each node, a first value is assigned to a pair of the first weight function and the first weight assigned to the node, when the first weight function is located in the left subtree of the node, and the first weight function is determined depending on a computing operation with the first weight and the first value (Equation 3, pi).
Regarding claim 5, Kitanov as modified teaches all of the limitations of claim 1, wherein:
for each node, a second value is assigned to a pair of the first weight function and the second weight assigned to the node, when the first weight function is located in the left subtree of the node, and the first weight function is determined depending on a computing operation with the first weight and the second value (Equation 3, pi).
Regarding claim 10, Kitanov as modified teaches all of the limitations of claim 1, wherein
the first variable is a target variable for an actuator of the technical system or a target variable for an actuator of the technical system is determined depending on the first variable, wherein the technical system is a computer controlled machine including a robot (“The present invention provides an application of a topological approach to Belief Space Planning (BSP) to solving multi-robot active Simultaneous Localization and Mapping (SLAM) problems.”)
Regarding claims 14 and 19, Kitanov as modified according to claim 1 along with a processor (see ¶104 of Kitanov) to run the method of Kitanov as modified according to claim 1 discloses the features of claims 14 and 19.
Regarding claim 21, Kitanov as modified according to claim 10 discloses the features of claim 21.
Allowable Subject Matter
Claims 3 and 6-9 are objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
The prior art does not anticipate or render obvious the determination of the second weight depending on the first weight of the node (claim 3) and does not anticipate or render obvious the specifics of the Gaussian processes of claims 6 and 7.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Seide (US5857169) discusses tree structures utilizing probability densities.
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/SCHYLER S SANKS/Primary Examiner, Art Unit 2129
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