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 .
Examiner Comment
The Office Action correspondence software provided by UPSTO does not permit Examiners to include documents exceeding 25 KB in the file wrapper. The front pages of the CN113825689 reference relied upon in the rejection below are included in the file wrapper with this Office Action.
The Examiner used Google Patents to access the document and recommends to the Applicant use of Google Patents to access the document (which exceeds 300 pages). Typing the document number in the search bar of Google Patents will yield the translated reference upon which the Examiner relied.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are:
Target agent determination unit in claims and disclosed in the specification at least at Par. [0009, 0011, 0012, 0018, 0042, 0052-0054, 0060-0064, 0088-0096].
Target action determination unit in claims and disclosed in the specification at least at Par. [0009-0011, 0013-0018, 0042, 0052-0058, 0063-0084, 0092-0096].
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 and 2 are rejected under 35 U.S.C. 103 as being unpatentable over CN 113825689.
Regarding claim 1, CN 113825689 discloses an action poisoning attack system for an autonomous driving model trained based on an action of each agent determining a movement of each of the agents driving virtually in a virtual space, the action poisoning attack system comprising (At least where CN 113825689 discloses Examples 413-422, 425-434, 480-485, 491-496 and their related explanations; description of Fig. 54):
a target agent determination unit (At least the system by which antagonistic data is introduced to the vehicle’s machine learning model and/or hacked) configured to determine a target agent that is an attack target intended to perform virtual driving by manipulated action information instead of action information output by the autonomous driving model among a plurality of agents (At least the manipulated control data/classification data in an environment where multiple Avs are located), based on position information of the agents in the virtual space; and
a target action determination unit configured to interfere with training of the autonomous driving model by generating target action information by manipulating the action information output (At least CN 113825689 discusses Fig. 54 and generation of a simulated attack data set that uses antagonistic data to interfere with the machine learning model or semi-autonomous/autonomous vehicles) by the autonomous driving model for the target agent and causing the target agent to perform a target action that is an action by the target action information, wherein the autonomous driving model is a machine learning model trained through a machine learning method based on the actions of the agents while determining the action information of each agent based on positions and actions of the other agents in the virtual space (At least where CN 113825689 disclose sharing of positioning reports, recommendation sharing, and communication V2V sharing of behavioral models between neighboring vehicles to provide determined probabilities as inputs to the vehicle’s own machine).
However, in the expressly discussed example in Fig. 54 where CN 113825689 discusses antagonistic data being introduced to a ML model, causing of the target agent to perform a target action does not appear to be discussed.
Nevertheless, in another portion of the disclosure, CN 113825689 discusses a machine learning model receiving manipulated classification data to alter a machine learning model’s behavior which results in the vehicle misidentifying a stop sign as a higher speed limit as well as a hacker manipulating control data and sending an erroneous command to the accelerator, thus causing the target agent to perform a target action based on the desired attack.
Thus, it would have been obvious to a PHOSITA at the time of effective filing to have recognized that the manipulated dataset described in Fig. 54 of CN 113825689 could leverage the manipulated image classification data as a targeted attack as disclosed in the other portions of CN 113825689 which teaches causing of a manipulated control action for the obvious purpose of providing a tangible accelerator, braking, or actuator outcome to gain control of the vehicle for hacking/safety testing purposes.
Regarding claim 2, the primary reference, CN 113825689 discloses that the autonomous driving model is configured to generate an action vector including a steering component related to steering of each of the agents and an acceleration component related to acceleration/ deceleration of each of the agents as the action information for each of the agents, and the target action determination unit is configured to generate a target action vector including a manipulation steering component and a manipulation acceleration component by changing at least one of the steering component and the acceleration component of the action vector output by the autonomous driving model (At least where CN 113825689 discloses the control events at the machine learning model include braking, acceleration, and steering wherein the control event is determined to be faulty or non-faulty during fault/intrusion detection; discussion of Fig. 46-48b; Fig. 54; use of classification models including support vector machines).
Allowable Subject Matter
Claims 10 and 11 are allowed.
Claims 3-9 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.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Brodie Follman whose telephone number is (571)270-1169. The examiner can normally be reached 8am-4:30pm EST M-F.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Erin Piateski can be reached at (571)270-7429. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/BRODIE J FOLLMAN/Primary Patent Examiner, Art Unit 3669
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