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 . In the event the determination of the status of the application as subject to 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.
Status of Claims
Claims 1-19 are currently pending and are being hereby examined herein.
Joint Inventors
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.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy of JP2023-195474 filed on 16 November 2023 was received on 2 December 2025.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 18 September 2024 has been considered by the examiner.
Claim Objections
The claims are objected to because of the following informalities:
Claims 2, 5-6, 11, 14-15: “a period” should be “[[a]] the period”.
Claim 10: “the period” should be “[[the]] a period”.
Appropriate corrections are required.
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.
Claims 2-6 and 11-15 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. See MPEP 2173.05(b)(III)(E): The addition of the word "type" to an otherwise definite expression (e.g., Friedel-Crafts catalyst) extends the scope of the expression so as to render it indefinite. Ex parte Copenhaver, 109 USPQ 118 (Bd. Pat. App. & Inter. 1955). For the purposes of applying prior art for compact prosecution, the examiner has interpreted “the external stimulus of first type” to be “the external stimulus to be an external stimulus of a first classification [[type]]” (Claim 2 / Claim 11) and “the external stimulus of the first classification [[type]]” (Claim 4 / Claim 5 / Claim 13 / Claim 14). Furthermore, the examiner has interpreted “the external stimulus of second type” to be “the external stimulus to be an external stimulus of a second classification [[type]]” (Claim 6 / Claim 15). Appropriate corrections are required.
Claims 10-18 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor regards as the invention. “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 are not met” (see at least MPEP 2111.04II / Ex parte Schulhauser). One of ordinary skill would not know if the limitations including “in a case” are intended to be positively recited or contingent, so the scope of the claims are indefinite. For the purposes of applying prior art for compact prosecution, the examiner has assumed that all limitations are positively recited. Appropriate corrections are required.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 6-11, and 15-19 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Pub. No. 2022/0299999 (Hasegawa et al., hereinafter, Hasegawa) in view of U.S. Pub. No. 2002/0103576 (Takamura et al., hereinafter, Takamura).
Regarding Claim 1, Hasegawa discloses A robot to autonomously act (see at least [0002] and FIG. 1), comprising:
a sensor to detect an external stimulus (see at least [0043]-[0045] and FIG. 2: touch sensor 211, acceleration sensor 212, microphone 213, illuminance sensor 214); and
at least one processor (see at least [0039] and FIG. 8), wherein
the at least one processor
causes, in a case where an action trigger that is predetermined is satisfied, the robot to execute an action selected, from a selection candidate list corresponding to the action trigger, at a selection probability dependent on a growth level, the growth level representing a degree of pseudo-growth of the robot (see at least FIG. 12).
Hasegawa does not explicitly disclose changes, in a case where the sensor detects the external stimulus during a period from when the robot is caused to execute the action until an elapse of a predetermined time, the selection probability that the action is selected from the selection candidate list.
Takamura, in the same field of robot controls, and therefore analogous art, changes, in a case where the sensor detects the external stimulus during a period from when the robot is caused to execute the action until an elapse of a predetermined time, the selection probability that the action is selected from the selection candidate list (see at least [0275]-[0300]: “The behavior determining mechanism unit 102 first determines the next behavior using a behavior and motion model corresponding to each behavior pattern on such occasions as when state recognition information S10 is given from the state recognition mechanism unit 30, or when a given period of time has elapsed since the last behavior appeared”; “Meantime, the state recognition mechanism unit 30 recognizes events `stroked` or `patted` based on the pressure detection signal S1C (FIG. 2) given from the touch sensor 18, the result of which is conveyed to the learning control mechanism unit 104.”; “At this time the learning control mechanism unit 104 knows the present and past behaviors of the pet robot 100 based on the behavior determining information S14 given from the behavior determining mechanism 102. Then, given the recognition result from the state recognition mechanism unit 30 that the pet robot 100 has been `stroked` while embodying behaviors, the learning control mechanism unit 104 conveys this result to the behavior determining mechanism 102.”; “Controlled as described in the foregoing, with an action `stroked` exerted the transition probability corresponding to that action increases, thereby making it easier for the pet robot 100 to embody that action, and with an action `patted` exerted the transition probability corresponding to that action decreases, thereby making it harder for the pet robot 100 to embody that action. In this way it is possible to have the pet robot 100 transform its behaviors as if it could behave like a real animal as a result of learning the disciplines by the keeper.”; “Thus, based on this notification the behavior determining mechanism 102 increases by the predetermined value the transition probability corresponding to the behavior or motion then outputted, which is on the state transition table 50”; “a learning function capable of interchanging several sets of control parameters prepared for an event `walking` for example so that the parameters applied to a `poor way of walking` may be changed to those of a `better way of walking` by the influence from the user, such as `stroke` or `pat`, and vice versa”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teachings of Hasegawa with those of Takamura in order “to have the pet robot 100 transform its behaviors as if it could behave like a real animal as a result of learning the disciplines by the keeper” (see at least Takamura [0282]).
Regarding Claim 2, the Hasegawa and Takamura combination teaches the limitations of Claim 1. Furthermore, Takamura further teaches (with the same motivation to combine as Claim 1) wherein the at least one processor increases, in a case where the sensor detects the external stimulus of first type during a period from when the robot is caused to execute the action until the elapse of the predetermined time, the selection probability that the action is selected from the selection candidate list within a range less than or equal to a predetermined upper limit (see at least [0275]-[0300]: the total sum of probabilities is 100%, so that is the predetermined upper limit; “Controlled as described in the foregoing, with an action `stroked` exerted the transition probability corresponding to that action increases, thereby making it easier for the pet robot 100 to embody that action”; the first classification is ‘stroked’).
Regarding Claim 6, the Hasegawa and Takamura combination teaches the limitations of Claim 1. Furthermore, Takamura further teaches (with the same motivation to combine as Claim 1) wherein in a case where the sensor detects the external stimulus of second type during a period from when the robot is caused to execute the action until the elapse of the predetermined time, the at least one processor decreases the selection probability that the action is selected from the selection candidate list and increases a selection probability of at least one action other than the action executed by the robot is selected from the selection candidate list within a range less than or equal to the predetermined upper limit (see at least [0275]-[0300]: the total sum of probabilities is 100%, so that is the predetermined upper limit; “with an action `patted` exerted the transition probability corresponding to that action decreases, thereby making it harder for the pet robot 100 to embody that action”; the second classification is ‘patted’).
Regarding Claim 7, the Hasegawa and Takamura combination teaches the limitations of Claim 1. Furthermore, Hasegawa further discloses wherein the at least one processor sets a personality parameter expressing a pseudo-personality of the robot, and sets the growth level based on the personality parameter (see at least [0082] and FIG. 11: “For example, as illustrated in FIG. 11…the character value (active) is 8…a growth value is 8, which is the maximum value among the four character values).
Regarding Claim 8, the Hasegawa and Takamura combination teaches the limitations of Claim 7. Furthermore, Hasegawa further discloses wherein the personality parameter includes personality values that express degrees of mutually different personalities, and the at least one processor sets the growth level to a maximum value among the personality values (see at least [0082] and FIG. 11: “For example, as illustrated in FIG. 11, it is assumed a case where the character value (happy) is 3, the character value (active) is 8, the character value (shy) is 5, and the character value (wanted) is 4 as the current character values of the robot 200 and the microphone 213 has detected a loud sound. In this case, a growth value is 8, which is the maximum value among the four character values, and the movement trigger is “hearing a loud sound”. Then, in the growth table 123 illustrated in FIG. 12, in the case of referring to an item with the movement trigger “hearing a loud sound” and the growth value of 8, it can be seen that the movement selection probabilities are set to be 20% for a “basic movement 2-0”, 20% for a “basic movement 2-1”, 40% for a “basic movement 2-2”, and 20% for a “character movement 2-0”.”).
Regarding Claim 9, the Hasegawa and Takamura combination teaches the limitations of Claim 7. Furthermore, Hasegawa further discloses wherein the at least one processor changes, in accordance with the external stimulus detected by the sensor, an emotion parameter expressing a pseudo-emotion of the robot, and sets the personality parameter based on the emotion parameter (see at least [0093]-[0109], [0119], and FIG. 15: “For example, in a case where the head 204 is stroked, the simulated emotion of the robot 200 is “feeling secured”, and thus, DXP of the emotion change data 122 is added to the X value of the emotion data 121. On the contrary, in a case where the head 204 is hit, the simulated emotion of the robot 200 is “feeling anxious”, so that DXM of the emotion change data 122 is subtracted from the X value of the emotion data 121. In step S103, the processing unit 110 acquires a plurality of external stimuli of types different from each other by the plurality of sensors included in the sensor unit 210. Thus, the emotion change data 122 is acquired according to each of the plurality of external stimuli, and the emotion data 121 is set according to the acquired emotion change data 122.”; “For example, if only the head 204 is stroked many times, only DXP of the emotion change data 122 increases, and the other emotion change data 122 does not change, so that the robot 200 has a character that easily feels secured. If only the head 204 is hit many times, only DXM of the emotion change data 122 increases, and the other emotion change data 122 does not change, so that the robot 200 has a character that easily feels anxious. In this manner, the processing unit 110 learns to make pieces of the emotion change data 122 different from each other according to each of the external stimuli. In the embodiment, the character value is calculated from the emotion change data 122, and the maximum value of the character value is set as the growth value. Thus, it is possible to obtain an effect of the simulated growth of the robot 200 based on how the user interacts with the robot 200.”).
Regarding Claim 10, Hasegawa discloses A robot control method for controlling a robot that autonomously acts (see at least [0002] and FIG. 1). For the other limitations, Claim 10 is substantially similar to Claim 1, and accordingly rejected for the same reasons as Claim 1.
Regarding Claim 11, Claim 11 is substantially similar to Claim 2, and accordingly rejected for the same reasons as Claim 2.
Regarding Claim 15, Claim 15 is substantially similar to Claim 6, and accordingly rejected for the same reasons as Claim 6.
Regarding Claim 16, Claim 16 is substantially similar to Claim 7, and accordingly rejected for the same reasons as Claim 7.
Regarding Claim 17, Claim 17 is substantially similar to Claim 8, and accordingly rejected for the same reasons as Claim 8.
Regarding Claim 18, Claim 18 is substantially similar to Claim 9, and accordingly rejected for the same reasons as Claim 9.
Regarding Claim 19, Hasegawa discloses A non-transitory computer-readable recording medium storing a program, the program causing a computer of a robot that autonomously acts to execute processing (see at least [0002] and FIG. 1). For the other limitations, Claim 19 is substantially similar to Claim 1, and accordingly rejected for the same reasons as Claim 1.
Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Hasegawa in view of Takamura in further view of U.S. Pub. No. 2019/0160683 (hereinafter, Hayashi).
Regarding Claim 3, the Hasegawa and Takamura combination teaches the limitations of Claim 2. Furthermore, Hasegawa further discloses wherein for each action in the selection candidate list, an initial value of the selection probability is set in accordance with the growth level (see at least FIG. 12). The Hasegawa and Takamura combination does not explicitly teach the predetermined upper limit is defined based on the initial value that is set for the action executed by the robot in a case where the growth level is lower than a current growth level.
Hayashi, in the same field of robot controls, and therefore analogous art, teaches the predetermined upper limit is defined based on the initial value that is set for the action executed by the robot in a case where the growth level is lower than a current growth level (see at least [0186]: “The special motion selection probability may decrease in accordance with the age (number of years elapsed since manufacture) of the robot. The older the robot, the more difficult it is to execute a special motion, because of which “aging” of the robot can be expressed.”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the teachings of Hasegawa and Takamura with Hayashi to make it more difficult to execute a special motion as the robot ages (see at least Hayashi [0186]).
Regarding Claim 12, Claim 12 is substantially similar to Claim 3, and accordingly rejected for the same reasons as Claim 3.
Claims 5 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Hasegawa in view of Takamura in further view of U.S. Pub. No. 2023/0281495 (Dan et al., hereinafter, Dan).
Regarding Claim 5, the Hasegawa and Takamura combination teaches the limitations of Claim 2. Furthermore, Takamura further teaches wherein in a case where the sensor detects the external stimulus of first type during a period from when the robot is caused to execute the action until the elapse of the predetermined time, the at least one processor increases the selection probability that the action is selected from the selection candidate list and decreases selection probabilities that actions other than the action executed by the robot are selected from the selection candidate list (see at least [0286]: “If the notification is given from the learning control mechanism unit 104 that the pet robot 100 has been `stroked` while embodying a behavior, the behavior determining mechanism 102 increases by as much value as specified by the learning speed table 105 the transition probability corresponding to the then outputted behavior or motion on the state transition table 50”; “decreases the values of the other transition probabilities on the same line in response to the former”).
The Hasegawa and Takamura combination does not explicitly teach each of the actions is assigned with a priority used when the selection probability is decreased, and a decrease value of the selection probabilities that the actions are respectively selected is determined based on priorities respectively assigned to the actions.
Dan, solving the same problem of updating selection probabilities, and therefore analogous art, teaches each of the actions is assigned with a priority used when the selection probability is decreased, and a decrease value of the selection probabilities that the actions are respectively selected is determined based on priorities respectively assigned to the actions (see at least [0022], [0024], and [0029]-[0031]: “In a situation where a node stochastically selects one action from a plurality of candidate actions, the information processing apparatus 10 of the first embodiment searches for an equilibrium solution for a probability distribution of the plurality of actions”; “The probability distribution information 13 indicates the current selection probabilities respectively for a plurality of actions that are selectable by the node. The node is a decision-making entity that selects an action, and may be called a player. The node may correspond to an apparatus such as a computer. An individual action may be called a strategy or a pure strategy, and a set of actions with a probability distribution may be called a mixed strategy. The node is assumed to randomly select any one action from the probability distribution information 13 with selection probabilities. For example, a first action has a selection probability of 40%, a second action has a selection probability of 40%, and a third action has a selection probability of 20%.”, “The regret minimization dynamics takes the difference between the maximum evaluation value of the plurality of actions and the evaluation value of an action as a regret of the action, and decreases the selection probabilities of actions with high regrets.”; “as an updated selection probability for an action, the processing unit 12 may calculate a weighted average of the selection probability before update and a new selection probability calculated based on a converted evaluation value, instead of using the new selection probability as it is. A weight for the new selection probability may be called a learning rate. For example, the processing unit 12 calculates 60% from the evaluation value 16a of the first action, and updates its selection probability from 40% to 50%. In addition, the processing unit 12 calculates 40% from the evaluation value 16b of the second action, and keeps its selection probability at 40%. In addition, the processing unit 12 calculates 0% from the evaluation value 16c of the third action, and updates its selection probability from 20% to 10%.”).
It would have been obvious, before the effective filing date of the invention, with a reasonable expectation of success, to one having ordinary skill in the art, to combine the Hasegawa and Takamura combination with the teachings of Dan with the motivation of substituting a specific way of “increasing the selection probabilities of actions with evaluation values greater than the average evaluation value and decreasing the selection probabilities of actions with evaluation values less than the average evaluation value” (see at least Dan [0004]) into the generically taught way of decreasing values of non-favored actions of Takamura.
Regarding Claim 14, Claim 14 is substantially similar to Claim 5, and accordingly rejected for the same reasons as Claim 5.
Subject Matter without Prior Art Rejections
No rejections under 35 U.S.C. 102 and 35 U.S.C. 103 are being made for Claims 4 and 13. The prior art does not disclose, teach, suggest, nor render obvious (when assumed to be positively recited) upon the sensor detecting the external stimulus of first type during the period from when the robot is caused to execute the action until the elapse of the predetermined time,
in a case where a selection probability set for the action at a current growth level is less than or equal to a selection probability set for the action at a growth level lower than the current growth level, increases, with the predetermined upper limit, the selection probability that the action is selected from the selection candidate list, the predetermined upper limit being a value of the selection probability set for the action at the growth level lower than the current growth level, and
in a case where the selection probability set for the action at the current growth level is greater than the selection probability set for the action at the growth level lower than the current growth level, does not increase the selection probability that the action is selected from the selection candidate list in combination with the limitations of Claims 1 and 2 / Claims 10 and 11. Specifically, the closest prior art, which is a combination of Hasegawa, Takamura, and Hayashi does not disclose, teach, suggest, nor render obvious in a case where the selection probability set for the action at the current growth level is greater than the selection probability set for the action at the growth level lower than the current growth level, does not increase the selection probability that the action is selected from the selection candidate list. There is no additional reference that could be added to disclose, teach, suggest, nor render obvious this limitation, in combination with the other limitations, without impermissible hindsight.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALEXANDRA ROBYN MORFORD whose telephone number is (571)272-6109. The examiner can normally be reached Monday - Friday 8:00 AM - 4:00 PM ET.
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/A.R.M./Examiner, Art Unit 3658
/JASON HOLLOWAY/Primary Examiner, Art Unit 3658