CTNF 18/232,206 CTNF 93128 07-03-aia AIA 15-10-aia The present application, filed on or after 16 March 2013, is being examined under the first inventor to file provisions of the AIA. DETAILED ACTION This office action is in response to Applicant’s submission filed on 9 August 2023. THIS ACTION IS NON-FINAL . The restriction requirement is removed and all claims are reviewed. 12-151 AIA 26-51 12-51 Status of Claims Claims 1-20 are pending. Claim 1-20 are rejected under 35 U.S.C. 101 for being directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. There is no art rejection for claims 1-20. Claim Rejections - 35 USC § 101 07-04-01 AIA 07-04 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. Judicial Exception Claims 1-20 of the claimed invention are directed to a judicial exception, an abstract idea, without significantly more. Regarding claims 1-7, (Independent Claims) With regards to claim 1, Step 1: The claim recites a process, which falls into one of the statutory categories. Step 2A – Prong 1: the claim, in part, recites “ accessing a representation space associated with the command, where similar subjects and commands in the representation space are clustered together; … updating the representation space based on at least one of the first dataset, the second dataset, and the third dataset; generating … a goal representation based on the representation space; … generating a first series of steps and a second series of steps based on the goal representation and the current environment; annotating … the sensor data based on performance of the first series of steps to generate an annotated senor data; and updating …the second series of steps based on the annotated sensor data ” (mental processes and/or math concepts), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the language about generic computer elements, “accessing”, “updating”, “generating”, “annotating”, in the limitation citied above encompasses generating / updating goal oriented task plan based on request and environment data, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Step 2A – Prong 2: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of: (a) “ A computer-implemented method for a machine-learning network … ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receiving, by a device, a command from a user related to a subject …”, “ receiving a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receiving, from a plurality of sensors, a sensor data of a current environment …” , which is extra-solution activity of pre-solution data gathering (see MPEP 2106.05(g)). Accordingly. the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites the additional elements of: (a) “ A computer-implemented method for a machine-learning network … ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receiving, by a device, a command from a user related to a subject …”, “ receiving a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receiving, from a plurality of sensors, a sensor data of a current environment …”, which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)). The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory"). The claim is not patent eligible. (Dependent claims) Claims 2-7 are dependent on claim 1 and include all the limitations of claim 1. Therefore, claims 2-7 recite the same abstract ideas. With regards to claim 2 , the claim recites further limitation of “wherein updating the representation space includes the steps of: analyzing the first dataset and the second dataset in view of the goal representation to determine an inter-task score for at least one subject represented in the representation space that is associated with the subject of the command; and regularizing a position of the at least one subject in the goal representation based on inter-task score ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 3 , the claim recites further limitation of “wherein updating the representation space includes the steps of: analyzing the third dataset in view of the goal representation to determine an intra-task score for at least one subject represented in the representation space that is not associated with the subject of the command; and regularizing a position of the at least one subject in the goal representation based on intra-task score ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 4 , the claim recites further limitation of “wherein the first dataset comprises goal related sensor data organized as a tuple, wherein each sensor data is positively associated with the command, wherein each tuple comprises a subject related sensor data, an instruction related sensor data, and an audio related sensor data; wherein the second dataset comprises goal related sensor data organized as a tuple, wherein one of the sensor data is negatively associated with the command; and wherein the third dataset comprises goal related sensor data organized as a tuple, wherein the sensor data is either negatively or positively associated with the command ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 5 , the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 6 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 7 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. Regarding claims 8-14, (Independent Claims) With regards to claim 8, Step 1: The claim recites a machine, which falls into one of the statutory categories. Step 2A – Prong 1: the claim, in part, recites “ access a representation space associated with the command, where similar subjects and commands in the representation space are clustered together; … update the representation space based on at least one of the first dataset, the second dataset, and the third dataset; generate … a goal representation based on the representation space; … generating a first series of steps and a second series of steps based on the goal representation and the current environment; annotate … the sensor data based on performance of the first series of steps to generate an annotated senor data; and update …the second series of steps based on the annotated sensor data ” (mental processes and/or math concepts), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the language about generic computer elements, “accessing”, “updating”, “generating”, “annotating”, in the limitation citied above encompasses generating / updating goal oriented task plan based on request and environment data, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Step 2A – Prong 2: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of: (a) “ A system for a machine-learning network comprising: one or more processors configured to … ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receive, by a device, a command from a user related to a subject …”, “ receive a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receive, from a plurality of sensors, a sensor data of a current environment …” , which is extra-solution activity of pre-solution data gathering (see MPEP 2106.05(g)). Accordingly. the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites the additional elements of: (a) “ A system for a machine-learning network comprising: one or more processors configured to … ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receive, by a device, a command from a user related to a subject …”, “ receive a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receive, from a plurality of sensors, a sensor data of a current environment …”, which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)). The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory"). The claim is not patent eligible. (Dependent claims) Claims 9-14 are dependent on claim 8 and include all the limitations of claim 8. Therefore, claims 9-14 recite the same abstract ideas. With regards to claim 9 , the claim recites further limitation of “wherein updating the representation space includes the steps of: analyzing the first dataset and the second dataset in view of the goal representation to determine an inter-task score for at least one subject represented in the representation space that is associated with the subject of the command; and regularizing a position of the at least one subject in the goal representation based on inter-task score ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 10 , the claim recites further limitation of “wherein updating the representation space includes the steps of: analyzing the third dataset in view of the goal representation to determine an intra-task score for at least one subject represented in the representation space that is not associated with the subject of the command; and regularizing a position of the at least one subject in the goal representation based on intra-task score ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 11 , the claim recites further limitation of “wherein the first dataset comprises goal related sensor data organized as a tuple, wherein each sensor data is positively associated with the command, wherein each tuple comprises a subject related sensor data, an instruction related sensor data, and an audio related sensor data; wherein the second dataset comprises goal related sensor data organized as a tuple, wherein one of the sensor data is negatively associated with the command; and wherein the third dataset comprises goal related sensor data organized as a tuple, wherein the sensor data is either negatively or positively associated with the command ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 12 , the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 13 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 14 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. Regarding claims 15-20, (Independent Claims) With regards to claim 15, Step 1: The claim recites a machine, which falls into one of the statutory categories. Step 2A – Prong 1: the claim, in part, recites “ access a representation space associated with the command, where similar subjects and commands in the representation space are clustered together; … update the representation space based on at least one of the first dataset, the second dataset, and the third dataset; generate … a goal representation based on the representation space; … generating a first series of steps and a second series of steps based on the goal representation and the current environment; annotate … the sensor data based on performance of the first series of steps to generate an annotated senor data; and update …the second series of steps based on the annotated sensor data ” (mental processes and/or math concepts), as drafted, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting generic computer elements, nothing in the claim element precludes the step from practically being performed in the mind. For example, but for the language about generic computer elements, “accessing”, “updating”, “generating”, “annotating”, in the limitation citied above encompasses generating / updating goal oriented task plan based on request and environment data, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. Step 2A – Prong 2: This judicial exception is not integrated into a practical application. In particular, the claim recites the additional elements of: (a) “ A machine-learning network for a machine-learning network comprising: one or more processors configured to … ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receive, by a device, a command from a user related to a subject …”, “ receive a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receive, from a plurality of sensors, a sensor data of a current environment …” , which is extra-solution activity of pre-solution data gathering (see MPEP 2106.05(g)). Accordingly. the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. Step 2B Analysis: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites the additional elements of: (a) “ A machine-learning network for a machine-learning network comprising: one or more processors configured to… ”, “ by a goal description machine learning model …”, “ by a progress description machine learning model …“, “ by a policy machine learning mode … “, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)); (b) “… receive, by a device, a command from a user related to a subject …”, “ receive a first dataset related to the command, a second dataset related to the subject, and a third dataset which includes subjects related to the command …”, “ receive, from a plurality of sensors, a sensor data of a current environment …”, which is extra-solution activity of pre-solution data gathering (see MPEP.2106.05(g)). The courts have found limitations directed to obtaining information electronically, recited at a high level of generality, to be well-understood, routine, and conventional (see MPEP 2106.05(d)(II), “receiving or transmitting data over a network”, "electronic record keeping," and "storing and retrieving information in memory"). The claim is not patent eligible. (Dependent claims) Claims 16-20 are dependent on claim 8 and include all the limitations of claim 8. Therefore, claims 9-14 recite the same abstract ideas. With regards to claim 16 , the claim recites further limitation of “wherein updating the representation space includes the steps of: analyzing the first dataset and the second dataset in view of the goal representation to determine an inter-task score for at least one subject represented in the representation space that is associated with the subject of the command; and regularizing a position of the at least one subject in the goal representation based on inter-task score ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 17 , the claim recites further limitation of “wherein the first dataset comprises goal related sensor data organized as a tuple, wherein each sensor data is positively associated with the command, wherein each tuple comprises a subject related sensor data, an instruction related sensor data, and an audio related sensor data; wherein the second dataset comprises goal related sensor data organized as a tuple, wherein one of the sensor data is negatively associated with the command; and wherein the third dataset comprises goal related sensor data organized as a tuple, wherein the sensor data is either negatively or positively associated with the command ”, which is further details on generating / updating goal oriented task plan, which is based on observation, evaluation, judgement, and/or opinion, that could be performed by human using paper / pen / calculator. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Except citing generic computer elements to implement the abstract idea, there is no additional element showing integration into a practical application or adding something significantly more to the abstract idea. The claim is not patent eligible. With regards to claim 18 , the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein the policy machine learning model is further trained based on the annotated sensor data ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 19 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model is frozen ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. With regards to claim 20 , the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2A, prong two, the additional elements individually or in combination do not integrate the judicial exception into a practical application. The claim is directed to an abstract idea. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above, the claim recites additional element of “… wherein training of the goal description machine learning model, progress description machine learning model, and the policy machine learning model are trained at a server, and operate locally at the device ”, which is mere instructions to implement an abstract idea using generic computing device, or merely uses a computer as a tool to perform an abstract idea (see MPEP 2106.05(f)). Accordingly, at Step 2B the additional elements individually or in combination do not amount to significantly more than the judicial exception. The claim is not patent eligible. Allowable Subject Matter Claims 1-20 include allowable subject matter since when reading the claims in light of the specification, as per, MPEP §2111.01 or Toro Co. v. White Consolidated Industries Inc., 199F.3d 1295, 1301, 53 USPQ2d 1065, 1069, 1069 (Fed.Cir. 1999), none of the references of record alone or in combination disclose or suggest the combination of limitations specified in claims 1-20. In interpreting the claims, in light of the specification filed on 9 August 2023, the Examiner finds the claimed invention to be patentably distinct from the prior arts of record. Regarding the amended independent claims, the primary reason for the allowance is the inclusion of the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions . None of the cited prior art references, singly or in combination, fully teaches all limitations of independent claims 1, 8 and 15. Regarding the dependent claims, which include all the limitations of the independent claims, are also allowed. The followings are references close to the invention claimed: Antonello et al., US-PGPUB NO.20250108832A1 [hereafter Antonello] teaches motion plan generation for mobile robots. However Antonello does not teach the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions. Grossman et al., US-PGPUB NO.20180121470A1 [hereafter Grossman] teaches object annotation using ML models. However Grossman does not teach the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions. Lancaster et al., US-PGPUB NO.10311442B1 [hereafter Lancaster] teaches automatically generating task plan using ML models. However Lancaster does not teach the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions. Xiao et al., “Motion planning and control for mobile robot navigation using machine learning: a survey”, Autonomous robots (2022) 46: 569-597, 2022 [hereafter Xiao] teaches robot planning and navigation using ML models. However Xiao does not teach the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions. Chaplot et al., “Object goal navigation using goal-oriented semantic exploration”, 24 th conference on neural information processing (NeurIPS 2020), Vancouver, Canada, 2020 [hereafter Chaplot] teaches goal navigation using ML models. However Chaplot does not teach the specific claimed process / structure of generating semantic representation of environment with clustering, creating goal representation based on environmental representation, followed by dual series of steps for planning, annotating with sensor inputs, then updating the plan for actions. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to TSU-CHANG LEE whose telephone number is 571-272-3567. The fax number is 571-273-3567. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Omar Fernandez Rivas, can be reached 571-272-2589. Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /TSU-CHANG LEE/ Primary Examiner, Art Unit 2128 Application/Control Number: 18/232,206 Page 2 Art Unit: 2128 Application/Control Number: 18/232,206 Page 3 Art Unit: 2128 Application/Control Number: 18/232,206 Page 4 Art Unit: 2128 Application/Control Number: 18/232,206 Page 5 Art Unit: 2128 Application/Control Number: 18/232,206 Page 6 Art Unit: 2128 Application/Control Number: 18/232,206 Page 7 Art Unit: 2128 Application/Control Number: 18/232,206 Page 8 Art Unit: 2128 Application/Control Number: 18/232,206 Page 9 Art Unit: 2128 Application/Control Number: 18/232,206 Page 10 Art Unit: 2128 Application/Control Number: 18/232,206 Page 11 Art Unit: 2128 Application/Control Number: 18/232,206 Page 12 Art Unit: 2128 Application/Control Number: 18/232,206 Page 13 Art Unit: 2128 Application/Control Number: 18/232,206 Page 14 Art Unit: 2128 Application/Control Number: 18/232,206 Page 15 Art Unit: 2128 Application/Control Number: 18/232,206 Page 16 Art Unit: 2128 Application/Control Number: 18/232,206 Page 17 Art Unit: 2128 Application/Control Number: 18/232,206 Page 18 Art Unit: 2128 Application/Control Number: 18/232,206 Page 19 Art Unit: 2128 Application/Control Number: 18/232,206 Page 20 Art Unit: 2128 Application/Control Number: 18/232,206 Page 21 Art Unit: 2128 Application/Control Number: 18/232,206 Page 22 Art Unit: 2128 Application/Control Number: 18/232,206 Page 23 Art Unit: 2128 Application/Control Number: 18/232,206 Page 24 Art Unit: 2128 Application/Control Number: 18/232,206 Page 25 Art Unit: 2128 Application/Control Number: 18/232,206 Page 26 Art Unit: 2128
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