Office Action Predictor
Last updated: April 15, 2026
Application No. 18/097,594

DIFFERENTIABLE LEARNING OF SCALABLE MULTI-AGENT NAVIGATION POLICIES

Non-Final OA §112
Filed
Jan 17, 2023
Examiner
SCHNEE, HAL W
Art Unit
2129
Tech Center
2100 — Computer Architecture & Software
Assignee
Tencent America LLC
OA Round
1 (Non-Final)
84%
Grant Probability
Favorable
1-2
OA Rounds
2y 9m
To Grant
99%
With Interview

Examiner Intelligence

Grants 84% — above average
84%
Career Allow Rate
503 granted / 595 resolved
+29.5% vs TC avg
Strong +22% interview lift
Without
With
+22.1%
Interview Lift
resolved cases with interview
Typical timeline
2y 9m
Avg Prosecution
16 currently pending
Career history
611
Total Applications
across all art units

Statute-Specific Performance

§101
9.7%
-30.3% vs TC avg
§103
40.8%
+0.8% vs TC avg
§102
17.4%
-22.6% vs TC avg
§112
26.3%
-13.7% vs TC avg
Black line = Tech Center average estimate • Based on career data from 595 resolved cases

Office Action

§112
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 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 1-20 are 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 Claim 1, it recites “iteratively taking, by the device until a condition is satisfied, next configuration as the initial configuration and feeding the next configuration into the neural network to begin next iteration, the next configuration comprising the next positions of the multiple objects” (last 3 lines). The terms “next configuration” and “next iteration” lack an article such as “a,” so it is unclear what configuration and iteration are being referenced. The lack on an article also makes the terms “the next configuration” and “the next iteration” indefinite because their antecedent basis is unclear. Regarding Claim 7, it recites “generating next position” (line 11). This term is indefinite because it lacks an article such as “a.” The present claim also recites “the current total energy-function in next iteration.” Here too, the term “next iteration” lacks an article such as “a” or “the,” so it is unclear which iteration is being referenced. Regarding Claims 10 and 19, they recite limitations substantially similar to those of claim 1, so they are indefinite for the same reasons. Regarding Claim 16, it recites limitations substantially similar to those of claim 7, so it is indefinite for the same reasons. Allowable Subject Matter Claims 1-20 would be allowable if rewritten or amended to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action. None of the prior art of record teaches all of the limitations of independent claims 1, 10, and 19. Dally et al. (U.S. 2020/0249674, cited by the applicant in the IDS filed 11 April 2024) uses a neural network to plan the path of an autonomous vehicle, but does not input target positions of multiple objects into the neural network and does not construct a kernel-based divergence-free velocity field. Chen et al. (U.S. 2024/0013406) predicts trajectories of multiple objects, but does not include target positions of the multiple objects. Lai et al. (U.S. 2025/0128419) teaches using a graph neural network to control multiple robots using current states and multiple target destinations, but it does not construct a kernel-based divergence-free velocity field and does not interpolate the kernel-based divergence-free velocity field to extract predicted velocities. Li, Qingbiao, et al. (“Graph neural networks for decentralized multi-robot path planning,” 2020 IEEE/RSJ international conference on intelligent robots and systems (IROS). IEEE, 2020) performs path planning for multiple robots by inputting a current state and a goal position of each robot into a separate convolutional neural network, but it too does not construct a kernel-based divergence-free velocity field and does not interpolate the kernel-based divergence-free velocity field to extract predicted velocities. Conclusion Any inquiry concerning this communication or earlier communications from the examiner should be directed to HAL W SCHNEE whose telephone number is (571) 270-1918. The examiner can normally be reached M-F 7:30 a.m. - 6:00 p.m. Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Michael Huntley can be reached at 303-297-4307. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300. Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000. /HAL SCHNEE/Primary Examiner, Art Unit 2129
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Prosecution Timeline

Jan 17, 2023
Application Filed
Dec 01, 2025
Non-Final Rejection — §112
Mar 27, 2026
Response Filed

Precedent Cases

Applications granted by this same examiner with similar technology

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Study what changed to get past this examiner. Based on 5 most recent grants.

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Prosecution Projections

1-2
Expected OA Rounds
84%
Grant Probability
99%
With Interview (+22.1%)
2y 9m
Median Time to Grant
Low
PTA Risk
Based on 595 resolved cases by this examiner. Grant probability derived from career allow rate.

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