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 .
Claims 1-10 and 17-26 are pending in this application. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/01/2025 has been entered.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-10 and 17-26 have been considered but are moot because the new ground of rejection does not rely on the combination of references applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Allowable Subject Matter
Claims 9 and 21 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.
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 1-6, 10, 17, and 22-26 are rejected under 35 U.S.C. 103 as being Unpatentable over Tan (US 2011/0277014) and in view of Ritter (US 2020/0034701) and in view of Kamvar (US 7,805,518).
Re Claim 1, Tan discloses a method comprising:
operating a distributed system including a first agent node and a plurality of agent nodes structured to communicate ([0021], peer-to-peer network communication nodes communicate with each other)
determining, with each agent node of the plurality of agent nodes, a plurality of iterations separated in time by a plurality of ticker periods ([0025], [0043], communications between the peer or evaluator nodes store a communication history and includes time stamps indicating a timer period during which the nodes have communicated) ;
determining, with the first agent node, a trust matrix including a plurality of trust factors, each trust factor corresponding to a weight applied to iterations of the plurality of iterations determined by one of the plurality of agent nodes ([0043]-[0044], [0058], authentication module calculates a global trust of a node. A trust degree matrix R is converted from local trust degree evaluated between the peer and/or evaluator nodes indicating a timer period during which the nodes have communicated);
determining, with the first agent node, a first iteration ([0054], value of corresponding duality variable between two nodes are implemented for the valuations of local trust given by node 1);
receiving, with the first agent node, a portion of the plurality of iterations determined by a portion of the plurality of agent nodes during a first ticker period beginning after the first iteration ([0053], the communication between nodes and a timestamp of the communication is used to store the local trust degree collection between time 1 and time2);
updating, with the first agent node, the trust matrix based on the portion of the plurality of iterations ([0045], the communication history of node j is updated based on the most recent interaction with node i. [0055]-[0057], the communication history represented by the alpha list and beta list where frequency of communication and timestamps are stored so the global trust can be calculated with the algorithm); and
determining, with the first agent node, a second iteration after the first ticker period based on the portion of the plurality of iterations and the updated trust matrix ([0057]-[0060], trust degree matrice is nXn where n is total number of nodes satisfying time requirement from time1 to time2 and at this time is calculated to global trust with the nodes.).
While Tan discloses iterations and the time between the iteration communications, Tan does not explicitly disclose the distributed al, however Ritter discloses a plurality of iterations of a distributed iterative algorithm separated in time by a plurality of ticker periods, wherein each ticker period comprises a predetermined time interval separating consecutive iterations ([0087], [0089], [0181], Each time (t) represents an iteration of the decision process for each given action. Every step in time or iteration for an action, the dynamic agent calculates the algorithm. A machine learning algorithm using a probability distribution where the distribution expresses the probability of a given number of values occurring in a fixed interval.); and
matrix in the distributed iterative algorithm ([0122], Q learning matrix ).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the teachings of Tan’s node evaluation with Ritter’s evaluation function by optimizing KPIs. One of ordinary skill in the art would have been motivated to incorporate the teachings with one another in order to allow the users to quickly and efficiently source a job in the nodes.
Tan and Ritter does not disclose, however Kamvar discloses where the nodes are structured to communicate asynchronously (col. 2, lines 5-15, peer-to-peer networks receives information from each other such as e-mail message (asynchronous communication).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the teachings of Tan and Ritter’s node communication with Kamvar’s node communication to utilize asynchronous communications such as emails. One of ordinary skill in the art would have been motivated to incorporate the teachings with one another in order to allow the users to communicate without an immediate response.
Re claim 2, Tan discloses further comprising determining, with the first agent node, a second plurality of iterations including the first iteration and the second iteration, ([0043], The communication history may span a predetermined time period, such as the last hour, 2 hours, 3 hours etc.). One of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Ritter discloses the plurality of iterations being separated in time by a second plurality of ticker period, wherein the second plurality of ticker periods are each equal in length of time ([0128], The neural network trained by the agents are performed at predetermined intervals such as after a specific number of training episodes or at a given time interval (once a day, week, etc.).
Re claim 3, Tan discloses wherein a portion of the ticker periods of the first plurality of ticker periods are a length in time different than the length of time of the ticker periods of the second plurality of ticker periods ([0043], The time period selection enables using evaluations that are not stale and assign an evaluation to another node by using a sliding bar, entering a number, or other types of user interfaces.) One of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Ritter discloses the plurality of iterations being separated in time by a second plurality of ticker period, wherein the second plurality of ticker periods are each equal in length of time ([0128], The neural network trained by the agents are performed at the direction of a user at or predetermined intervals such as after a specific number of training episodes or at a given time interval (once a day, week, etc.). The dynamic agent can increase the rate of leaning or increase (change the ticker periods)).
Re claim 4, Tan discloses wherein updating the trust matrix is based on the portion of the plurality of iterations received during the first ticker period includes decreasing any weight applied to iterations received from a remainder of the plurality of agents nodes that did not transmit an iteration to the first agent node during the ticker period ([0043], the communication history of node j is updated based on the most recent interaction with node i. [0056]-[0061], listed different equations used to calculate the global trust value with different time periods).
Re claim 5, one of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Kamvar discloses wherein updating the trust matrix based on the portion of the plurality of iterations received during the first ticker period includes increasing the weight applied to iterations determined by the first agent node in an amount equal to the amount any weights were decreased (col. 4, lines 61-67, normalizing local trust values ensure that all values will be between 0 and 1 and that a peer’s normalized rankings for other peers will sum to 1. Which means an increase in one peer will have to decrease in another in order for the values to have a sum of 1).
Re claim 6, Tan discloses determining a step size based on the portion of the plurality of iterations received during the first ticker period, wherein determining the second iteration after the first ticker period is based in part on the determined step size ([0043], The communication history may span a predetermined time period, such as the last hour, 2 hours, 3 hours etc.).
Re claim 23, one of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Ritter discloses repeatedly determining additional iterations until the plurality of agent nodes determine that the iterations have converged ([0232], the training set of scenario as part of training the machine-training algorithm continues until the output from the algorithm meets are certain threshold including comparing the differences between output values and expected values or when output values for similar inputs converge within a threshold variance).
Re claim 24, one of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Ritter discloses the first ticker period ([0087], [0089], Each time (t) represents an iteration of the decision process for each given action). In addition, Kamvar discloses computing a weighted combination of the portion of the plurality of iterations received, wherein the trust factors of the trust matrix are used as weights in the weighted combination (Claim 1, combining set of global and local trust values).
Re claim 26, one of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Ritter discloses wherein different agent nodes of the plurality of agent nodes determine corresponding iterations at different times such that the distributed iterative algorithm executes asynchronously ([0087], [0089], Each time (t) represents an iteration of the decision process for each given action [0128], The neural network trained by the agents are performed at the direction of a user at or predetermined intervals such as after a specific number of training episodes or at a given time interval (once a day, week, etc.). The dynamic agent can increase the rate of leaning or increase (change the ticker periods). Since Ritter only discloses the point in time the agent selects and performs the action does not disclose a certain time that iteration of the decision has to be processed by, it is treated as asynchronous iteration).
Re claims 10, 17, 22, 25 is similar to claims 1 and 4-6 therefore is rejected for the same reasons as claims 1 and 4-6 above.
Claims 7, 18 and 19 are rejected under 35 U.S.C. 103 as being Unpatentable over Tan and in view of Kamvar and in view of Hoffberg (US 2010/0317420).
Re Claims 7 and 18, Tan and Kamvar does not disclose, however Hoffberg discloses wherein the first iteration, the second iteration, and the plurality of iterations are determined by the plurality of agent nodes based on recursive least squares ([0465]-[0466], covariance R matrices (trust matrices) utilizes Kaman filter providing an efficient recursive solution of the least-squares method).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the teachings of Tan and Kamvar’s trust matrix with Hoffberg’s covariance R matrices in order to utilize a Kalman filter. One of ordinary skill in the art would have been motivated to incorporate the teachings with one another in order to allow the users to provide an efficient recursive solution using with the matrices.
Re claim 19, one of ordinary level of skill in the art would have been compelled to make the proposed modification to Tan for the same reasons identified in the rejection of claim 1. In addition, Kamvar discloses wherein updating the trust matrix based on the portion of the plurality of iterations received during the first ticker period includes increasing the weight applied to iterations determined by the first agent node in an amount equal to the amount any weights were decreased (col. 4, lines 61-67, normalizing local trust values ensure that all values will be between 0 and 1 and that a peer’s normalized rankings for other peers will sum to 1. Which means an increase in one peer will have to decrease in another in order for the values to have a sum of 1).
Claims 8 and 20 are rejected under 35 U.S.C. 103 as being Unpatentable over Tan and in view of Ritter and in view of Kamvar and in view of Feng (US 2015/0066402).
Re Claims 8 & 20, Tan and Kamvar does not disclose, however Fengg discloses wherein the first iteration, the second iteration, and the plurality of iterations are determined by the plurality of agent nodes based on recursive least squares ([0465]-[0466], covariance R matrices (trust matrices) utilizes Kaman filter providing an efficient recursive solution of the least-squares method).
It would have been obvious for one of ordinary skill in the art before the date the current invention was effectively filed to have modified the teachings of Tan, Ritter and Kamvar’s trust matrix with Feng’s covariance R matrices in order to have state estimation based on covariance (trust) matrices. One of ordinary skill in the art would have been motivated to incorporate the teachings with one another in order to allow the users to have first and second state estimates carried out at separate nodes for different problems such as state estimators for state vectors.
Conclusion
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/HO T SHIU/Examiner, Art Unit 2443
/CHRISTOPHER B ROBINSON/Primary Examiner, Art Unit 2443