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 .
Response to Argument
Applicant’s arguments in the Remarks, filed on 5/28/26 have been fully considered but they are not persuasive.
In the Remarks, Applicant argues that:
Morris fails to teach at least applying the first message to the first agent module in the plurality of agent modules to receive the corresponding output for each respective agent module in the first subset of the plurality of agent modules, in which the first agent module is trained on training data to route the respective message to the second subset of the plurality of agent modules different from the first agent module, and using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify the subset of the plurality of actions.
In response to point (i), according to Applicant,
“Morris is entirely silent about using multiple feeder agents, one of which is trained to route to other feeder agents by considering a best output of such feeder agents and performing a process in accordance with the appropriate feeder agent. Accordingly, Morris does not teach or suggest the claimed feature applying the first message to the first agent module in the plurality of agent modules to receive the corresponding output for each respective agent module in the first subset of the plurality of agent modules, in which the first agent module is trained on training data to route the respective message to the second subset of the plurality of agent modules different from the first agent module, and using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify the subset of the plurality of actions.” (Remarks at 14)
Examiner respectfully disagree. In response to applicant's argument that the references fail to show certain features of the invention, it is noted that the features upon which applicant relies (i.e., using multiple feeder agents, one of which is trained to route to other feeder agents by considering a best output of such feeder agents and performing a process in accordance with the appropriate feeder agent) are not recited in the rejected claim(s). Although the claims are interpreted in light of the specification, limitations from the specification are not read into the claims. See In re Van Geuns, 988 F.2d 1181, 26 USPQ2d 1057 (Fed. Cir. 1993).
As stated in the Non-Final office action mailed on 4/3/26, Morris teaches the recited limitations of applying the first message to a first agent in the plurality of agents to receive a corresponding output for each respective agent in a first subset of the plurality of agents ([120][121][122], e.g., applying the user message to module/functionality 604 to receive a corresponding output for each agent/functionality/module), wherein the first agent is trained to route a respective message to a second subset of the plurality of agents ([121][122], e.g., the functionality/module 604 is trained to forward a respective message to a subset of agents associated with different topic or automated response agents), using the corresponding output for each respective agent in the first subset of the plurality of agents to identify a subset of the plurality of actions ([115][118], fig. 6, e.g., using outputs of the modules/agents to identify actions). The recited “first agent module” (or first agent) is mapped to the functionality/module 604, not the feeder agents in the Morris reference. Morris teaches the functionality/module 604, which comprises module 404, can use a model that is trained by training data ([75]; fig. 6) Morris teaches that the functionality/module 604 is trained to forward a respective message to a subset of agents associated with different topic or automated response agents ([121][122]). Morris further teaches using outputs of the modules/agents to identify actions ([115][118], fig. 6)
Double Patenting
Instant Application
1. A system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions for: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic, wherein the automated content logic is configured, at least in part, to facilitate electronic communication between with the user and a plurality of agent modules associated with the automated content logic; B) applying the first message to a first agent module in the plurality of agent modules to receive a corresponding output for each respective agent module in a first subset of the plurality of agent modules,
wherein the first agent module is trained on training data to route a respective message to a second subset of the plurality of agent modules, each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions, each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function, and the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module;
C) using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify a subset of the plurality of actions; and D) performing a process in accordance with the first subset of the plurality of actions to generate a second message to engage with the corresponding session.
30. A method comprising: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic, wherein the automated content logic is configured, at least in part, to facilitate electronic communication between with the user and a plurality of agent modules associated with the automated content logic; B) applying the first message to a first agent module in the plurality of agent modules to receive a corresponding output for each respective agent module in a first subset of the plurality of agent modules,
wherein the first agent module is trained to route a respective message to a second subset of the plurality of agent modules, each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions, each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function, and the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module;
C) using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify a subset of the plurality of actions; and
D) performing a process in accordance with the first subset of the plurality of actions to generate a second message to engage with the corresponding session.
2. The system of claim 1, wherein the receiving A) comprises detecting a first protocol, in a plurality of protocols, associated with the corresponding session, and the using C) comprises identifying the subset of the plurality of actions in accordance with the first protocol.
4. The system of claim 1, wherein the automated content logic comprises a first set of content logic associated with one or more learned routings associated with the plurality of agent modules.
5. The system of claim 1, wherein the automated content logic comprises a second set of content logic associated with one or more contexts of a respective message received during a respective session.
9. The system of claim 1, wherein each respective agent in the subset of the plurality of agent modules is configured to independently identify a classification in a plurality of classifications associated with a corresponding action in the plurality of actions.
14. The system of claim 1, wherein each respective agent module in the second subset of the plurality of agent modules is independently associated with one or more corresponding functions and a corresponding plurality of parameters applied to the one or more corresponding functions.
20. The system of claim 1, wherein the applying B) comprises generating a first plurality of tokens associated with the first message, and performing D) comprises generating a second plurality of tokens different from the first plurality of tokens.
21. The system of claim 1, wherein the applying B) comprises applying (i) the first message and (ii) a first data set associated with a content of the corresponding session to the first agent module.
22. The system of claim 1, wherein the applying B) comprises applying (i) the first message and (ii) a second data set to the first agent module, wherein the second data set comprises one or more prior conversations associated with the user and/or one or more attributes associated with a corresponding user profile of the user.
23. The system of claim 1, wherein the using C) comprises identifying the subset of the plurality of actions through a weighted vote among the corresponding output for each respective agent module in the subset of the plurality of agent modules.
24. The system of claim 1, wherein the using C) comprises identifying the subset of the plurality of actions through a proximity of actions among the corresponding output for each respective agent module in the subset of the plurality of agent modules.
29. A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores instructions, which when executed by a computer system, cause the computer system to perform a method of: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic, wherein the automated content logic is configured, at least in part, to facilitate electronic communication between with the user and a plurality of agent modules associated with the automated content logic;
B) applying the first message to a first agent module in the plurality of agent modules to receive a corresponding output for each respective agent module in a first subset of the plurality of agent modules,
wherein the first agent module is trained on training data to route a respective message to a second subset of the plurality of agent modules, each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions, each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function, and the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module;
C) using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify a subset of the plurality of actions; and
D) performing a process in accordance with the first subset of the plurality of actions to generate a second message to engage with the corresponding session.
Patent 12563002
29. A server system, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions for: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic configured, at least in part, to facilitate electronic communication between with the user and a plurality of agents associated with the automated content logic;
B) applying the first message as an input to a first set of agents, in the plurality of agents, to receive a corresponding output for each respective agent in the first set of agents, wherein each corresponding output identifies an action, in a plurality of actions, performed, at least in part, by the automated content logic, wherein the plurality of actions is defined in a registered set of actions, each action in the registered set of actions comprising a typed schema specifying a plurality of parameters, one or more authentication types, and one or more return types;
C) using the corresponding output for each respective agent in the first set of agents to identify a first action in the plurality of actions; and
D) performing a process in accordance with the first action to generate a second message to engage with the corresponding session.
1. A method comprising: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic configured, at least in part, to facilitate electronic communication between with the user and a plurality of agents associated with the automated content logic;
B) applying the first message as an input to a first set of agents, in the plurality of agents, to receive a corresponding output for each respective agent in the first set of agents, wherein each corresponding output identifies an action, in a plurality of actions, performed, at least in part, by the automated content logic, wherein the plurality of actions is defined in a registered set of actions, each action in the registered set of actions comprising a typed schema specifying a plurality of parameters, one or more authentication types, and one or more return types;
C) using the corresponding output for each respective agent in the first set of agents to identify a first action in the plurality of actions; and
D) performing a process in accordance with the first action to generate a second message to engage with the corresponding session.
2. The method of claim 1, wherein the receiving A) comprises detecting a first protocol, in a plurality of protocols, associated with the corresponding session, and selecting the first set of agents from the plurality of agents in accordance with the first protocol.
4. The method of claim 1, wherein the method further comprises, prior to the applying B), selecting the first set of agents from the plurality of agents in accordance with a plurality of rules of the automated content logic comprising a first set of rules associated with one or more learned routings of two or more agents in the plurality of agents; or
a second set of rules in the plurality of rules, associated with one or more contexts of a respective message received during a respective session.
6. The method of claim 1, wherein each respective agent in the first set of agents is configured to independently identify a classification in a plurality of classifications associated with the action.
11. The method of claim 1, wherein each respective agent in the plurality of agents is independently associated with one or more corresponding functions and a corresponding plurality of parameters applied to the one or more corresponding functions.
13. The method of claim 1, wherein the applying B) comprises generating a first plurality of tokens associated with the first message, and the action is generating a second plurality of tokens different from the first plurality of tokens.
15. The method of claim 1, wherein the applying B) comprises applying (i) the first message and (ii) a first data set associated with a content of the corresponding session as the input to each agent in the first set of agents.
16. The method of claim 1, wherein the applying B) comprises applying (i) the first message and (ii) a second data set as the input to each agent in the first set of agents, wherein the second data set comprises one or more prior conversations associated with the user and/or one or more attributes associated with a corresponding user profile of the user.
20. The method of claim 1, wherein the using C) comprises identifying the first action through a majority vote among the corresponding output for each respective agent in the first set of agents, a weighted vote among the corresponding output for each respective agent in the first set of agents, or a proximity of actions among the corresponding output for each respective agent in the first set of agents.
28. A non-transitory computer readable storage medium, wherein the non-transitory computer readable storage medium stores instructions, which when executed by a computer system, cause the computer system to perform a method of: A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic configured, at least in part, to facilitate electronic communication between with the user and a plurality of agents associated with the automated content logic;
B) applying the first message as an input to a first set of agents, in the plurality of agents, to receive a corresponding output for each respective agent in the first set of agents, wherein each corresponding output identifies an action, in a plurality of actions, performed, at least in part, by the automated content logic, wherein the plurality of actions is defined in a registered set of actions, each action in the registered set of actions comprising a typed schema specifying a plurality of parameters, one or more authentication types, and one or more return types;
C) using the corresponding output for each respective agent in the first set of agents to identify a first action in the plurality of actions; and
D) performing a process in accordance with the first action to generate a second message to engage with the corresponding session.
Claim 1 is non-provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 29 of U.S. Patent 12563002 in view of Morris et al, U.S. Patent Application Publication 2011/0252011. Claim 29 of U.S. Patent 12563002 does not claim wherein the first agent module is trained on training data to route a respective message to a second subset of the plurality of agent modules, each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions, each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function, and the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module; and first subset of the plurality of actions. Morris teaches
wherein the first agent module is trained on training data to route a respective message to a second subset of the plurality of agent modules ([75][121][122], e.g., the functionality/module 604 is trained to forward a respective message to a subset of agents associated with different topic or automated response agents; functionality/module 604, which comprise module 404, can use a model that is trained by training data), each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions ([115][118], e.g., each subset of agents/automated response agents is trained to perform an action), each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function ([114][115][118][155], e.g., agent responding to a question/message; message feeder agents routing messages to contacts or automated response functionality or invoking an automated response functionality), and the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module ([115][122], fig. 6, e.g., functionalities/modules of fig. 6, message-feeder agents of different topics, automated response agents different from the functionality/module 604); and D) performing a process in accordance with the first subset of the plurality of actions to generate a second message to engage with the corresponding session ([115][129], e.g., generating message in accordance with the actions of the modules/agents). It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include Morris’s teaching because by doing so it would allow a user message to be routed and processed by more than one agents, thus allowing a plurality of agents to collectively process the user message to generate a response.
Except for the identified elements above, claim 29 of 12563002 contains every elements of claim 1 in the instant application and thus anticipate the claim of the instant application. Claim 1 of the instant application therefore are not patently distinct from the earlier claim and as such is unpatentable over non-provisional obvious-type double patenting.
Claim 30 is non-provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 1 of U.S. Patent 12563002 in view of Morris for the same reason as set forth in claim 1 above.
Claim 29 is non-provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claim 28 of U.S. Patent 12563002 in view of Morris for the same reason as set forth in claim 1 above.
Claims 2 and 4-5 are non-provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 2 and 4 of U.S. Patent 12563002 in view of Morris. Except for the identified elements above in claim 1, claim 2 and 4 of 12563002 contains every elements of claim 2 and 4-5 in the instant application and thus anticipate the claim of the instant application. Claim 2, 4-5 of the instant application therefore are not patently distinct from the earlier claim and as such is unpatentable over non-provisional obvious-type double patenting.
Claims 9, 14 and 20-24 are non-provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 6, 11, 13, 15-16 and 20 of U.S. Patent 12563002 in view of Morris. Except for the identified elements above in claim 1, claims 6, 11, 13, 15-16 and 20 of 12563002 contains every elements of claim 9, 14 and 20-24 in the instant application and thus anticipate the claim of the instant application. Claim 9, 14 and 20-24 of the instant application therefore are not patently distinct from the earlier claim and as such is unpatentable over non-provisional obvious-type double patenting.
Objection
Claims are objected to because of the following typographical error: Claim 30, the claim recites duplicate of step A) (i.e., please delete one of the duplicate step A)); Claim 33, “the first agent” should be “the first agent module”
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-7, 9-22 and 26-30 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Morris et al, U.S. Patent Application Publication 2011/0252011 (hereinafter Morris).
As per claim 1, Morris teaches the invention as claimed comprising:
one or more processors [210];
memory [210]; and
one or more programs, wherein the one or more programs are stored in the memory and are configured to be executed by the one or more processors, the one or more programs including instructions for [210]:
A) receiving, in electronic form, a first message from a user to engage with a corresponding session of an automated content logic, wherein the automated content logic is configured, at least in part, to facilitate electronic communication between with the user and a plurality of agent modules associated with the automated content logic([118][122][123], e.g., receiving a user message to engage with a session of the system, wherein the system is to facilitate communication between a user and agents/functionalities/modules of the system);
B) applying the first message to a first agent module in the plurality of agent modules to receive a corresponding output for each respective agent module in a first subset of the plurality of agent modules, ([120][121][122], e.g., applying the user message to module/functionality 604 to receive a corresponding output for each agent/functionality/module), wherein
the first agent module is trained on training data to route a respective message to a second subset of the plurality of agent modules([75][121][122], e.g., the functionality/module 604 is trained to forward a respective message to a subset of agents associated with different topic or automated response agents; functionality/module 604, which comprise module 404, can use a model that is trained by training data),
each respective agent module in the second subset of the plurality of agent modules is trained to perform a corresponding action in a plurality of actions ([115][118], e.g., each subset of agents/automated response agents is trained to perform an action),
each respective action in the plurality of actions is an operation performed, at least in part, by a corresponding agent module comprising responding to a message, routing to a different agent module, or invoking an application function ([114][115][118][155], e.g., agent responding to a question/message; message feeder agents routing messages to contacts or automated response functionality or invoking an automated response functionality), and
the first subset of the plurality of agent modules comprises at least two agent modules different from the first agent module([115][122], fig. 6, e.g., functionalities/modules of fig. 6, message-feeder agents of different topics, automated response agents different from the functionality/module 604);
C) using the corresponding output for each respective agent module in the first subset of the plurality of agent modules to identify a subset of the plurality of actions ([115][118], fig. 6, e.g., using outputs of the modules/agents to identify actions); and
D) performing a process in accordance with the first subset of the plurality of actions to generate a second message to engage with the corresponding session ([115][129], e.g., generating message in accordance with the actions of the modules/agents).
As per claim 2, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the receiving A) comprises detecting a first protocol, in a plurality of protocols, associated with the corresponding session ([122], e.g., detecting a first protocol (e.g., geographic)), and the using C) comprises identifying the subset of the plurality of actions in accordance with the first protocol ([122]).
As per claim 3, Morris teaches the invention as claimed in claim 2 above. Morris further teach wherein the plurality of protocols comprises
(i) one or more security protocols,
(ii) one or more encryption protocols,
(iii) one or more privacy protocols,
(iv) one or more access right protocols,
(v) one or more communication protocols,
(vi) one or more display protocols,
(vii) one or more transaction protocols,
(viii) one or more session protocols,
(ix) one or more data protocols,
(x) one or more regional protocols,
(xi) one or more geographic protocols,
(xii) one or more resource protocols,
(xiii) one or more pooled resource protocols,
(xiv) one or more classification protocols,
(xv) one or more context protocols, or
(xvi) a combination thereof ([122]).
As per claim 4, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the automated content logic comprises a first set of content logic associated with one or more learned routings associated with the plurality of agent modules ([122][127][132]).
As per claim 5, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the automated content logic comprises a second set of content logic associated with one or more contexts of a respective message received during a respective session ([138]).
As per claim 6, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the automated content logic is based, at least in part, on a corresponding functional flow logic (fig. 4), and
prior to the applying B), the automated content logic updates the corresponding functional flow in accordance with a customized dependency defined by an administrator ([149], e.g., prior to applying the first agent to route a respective message, user defined social network resource/resources that will receive the message).
As per claim 7, Morris teaches the invention as claimed in claim 6 above. Morris further teach wherein the administrator is a second agent module in the plurality of agent modules or an administrator user ([147]-[149]).
As per claim 9, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein each respective agent module in the subset of the plurality of agent modules is configured to independently identify a classification in a plurality of classifications associated with a corresponding action in the plurality of actions ([121][122][132]).
As per claim 10, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein each respective agent module in the subset of the plurality of agent modules is a trained classifier ([132]).
As per claim 11, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein each respective agent module in the subset of the plurality of agent modules comprises a corresponding logic defining a decision tree, a random forest, a Bayesian network, a support vector machine, a neural network, a logistic regression, a nearest neighbor clustering, a pattern recognition, a node graph, an imposed heuristic, or a classification recognition ([132]).
As per claim 12, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein each respective agent module in the plurality of agent modules is a component module of a decision tree agent module, a random forest agent module, a Bayesian network agent module, a support vector machine agent module, a neural network agent module, a logistic regression agent module, a nearest neighbor clustering agent module, a pattern recognition agent module, a node graph agent module, an imposed heuristic agent module, or a classification recognition agent module ([132]).
As per claim 13, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the plurality of agent modules comprise
a second agent module configured to identify a respective action in the plurality of actions based on one or more demographic parameters,
a third agent module configured to identify the respective action in the plurality of actions based on one or more geographic parameters,
a fourth agent module configured to identify the respective action in the plurality of actions based on one or more historical parameters,
a fifth agent module configured to identify the respective action in the plurality of actions based on one or more pattern-based parameters,
a sixth agent module trained to identify the respective action in the plurality of actions based on one or more personalized parameters uniquely associated with the user,
or a combination thereof ([137]).
As per claim 14, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein each respective agent module in the second subset of the plurality of agent modules is independently associated with one or more corresponding functions and a corresponding plurality of parameters applied to the one or more corresponding functions ([122][115][118]).
As per claim 15, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein an agent module in the second subset of the plurality of agent modules comprises a first logic configured to generate a first output using the first message ([122]; 120, fig. 4), and
a second logic configured generate the corresponding output using the first output ([122]; 120, fig. 4).
As per claim 16, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the first agent module is configured as a root agent module and each respective agent module in the second subset of the plurality of agent modules is configured as a child agent module associated with the first agent module ([122]).
As per claim 17, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the automated content logic comprises a hierarchical tree comprising a depth of n (614, fig. 6), n is an integer greater than or equal to two (614, fig. 6; [126]), the first agent module is configured as a root agent module at a first depth, of the hierarchical tree, of n is one (614, fig. 6; [126], e.g., module 604 uses the hierarchical tree 614, fig. 6 for the routing of message feeder agents (i.e., module 604 fig. 6 as root agent and route the message to message feeder agents as child agents)), and each respective agent module in the subset of the plurality of agent modules is associated with the first agent module and configured as a child agent module at least a second depth, of the hierarchical tree, of n is two or more (614, fig. 6; [126]).
As per claim 18, Morris teaches the invention as claimed in claim 17 above. Morris further teach wherein n is at least four (614, fig. 6).
As per claim 19, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the plurality of agent modules comprises six agent modules (modules of figs. 4 and 6, message feeder agents [121][122], automated response agents [115]).
As per claim 20, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the applying B) comprises generating a first plurality of tokens associated with the first message ([122][137][141]), and the performing D) comprises generating a second plurality of tokens different from the first plurality of tokens ([122][137][141]).
As per claim 21, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the applying B) comprises applying (i) the first message and (ii) a first data set associated with a content of the corresponding session to the first agent module [126].
As per claim 22, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the applying B) comprises applying (i) the first message and (ii) a second data set to the first agent module, wherein the second data set comprises one or more prior conversations associated with the user and/or one or more attributes associated with a corresponding user profile of the user [137].
As per claim 26, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the using C) comprises
(i) obtaining, via a communication network, a third data set from a remote device in accordance with an application programing interface token associated with the remote device,
(ii) communicating, via the communication network, a fourth data set to the remote device in accordance with the application programing interface token associated with the remote device,
(iii) identifying a second subset of the plurality of agent modules different from the subset of the plurality of agent modules for the performing D),
(iv) identifying a first parameter in a plurality of parameters associated with the first message,
(v) generating a text string for the second message,
(vi) displaying the second message,
(vii) executing one or more instructions,
(viii) evaluating a first graphical image,
(ix) providing a second graphical image,
(x) joining a human user different from the user to the corresponding session,
(xi) a future best action by the automated content logic, or
(xii) a combination thereof ([138][140][141][142]).
As per claim 27, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the performing D) comprises applying (i) the first message and (ii) a third data set associated with a content of the corresponding session as an input to the first agent to receive as output the second message ([154][137]-[142][155]).
As per claim 28, Morris teaches the invention as claimed in claim 1 above. Morris further teach wherein the performing D) comprises causing (i) the second message and (ii) one or more labels associated with the second message to display at a remote device associated with the user ([165][141]fig. 9, e.g., Giovanni’s Italian cuisine).
As per claims 29 and 30, they are rejected for the same reason as set forth in claim 1 above.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis 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.
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.
Claim 23 is rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Li et al, U.S. Patent Application Publication 2006/0287848 (hereinafter Li).
As per claim 23, Morris teaches the invention as claimed in claim 1 above. Although Morris teaches wherein the using C) comprises identifying the subset of the plurality of actions among the corresponding output for each respective agent module in the subset of the plurality of agent modules ([137]), however, Morris is silent in regards to through a weighted vote. Li teaches wherein the using C) comprises identifying the subset of the plurality of actions through a weighted vote among the corresponding output for each respective agent module in the subset of the plurality of agent modules ([27][45]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Li’s teaching with Morris’s system in order to improve the accuracy of statistical classifiers/agents in Morris’s system [25].
Claim 24 is rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Fuzinski et al, EP 1227419 (hereinafter Fuzinski).
As per claim 24, Morris teaches the invention as claimed in claim 1 above. Although Morris teaches wherein the using C) comprises identifying the subset of the plurality of actions among the corresponding output for each respective agent module in the subset of the plurality of agent modules ([137]), however, Morris is silent in regards to through a proximity of actions. Fuzinski teaches wherein the using C) comprises identifying the subset of the plurality of actions through a proximity of actions among the corresponding output for a respective agent module ([45], e.g., identifying subset of actions through context nodes that are closer to the root of the tree like data structure among the corresponding output for an agent).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Fuzinski’s teaching with Morris’s system in order to improve the communication of automated response agents in Morris’s system by providing a technique/tools used in connection with simulating communication behavior of Morris’s agents.
Claim 25 is rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Lee-Goldman et al, U.S. Patent 10,102,273 (hereinafter Lee-Goldman).
As per claim 25, Morris teaches the invention as claimed in claim 1 above. Morris is silent in regards generating the second message in accordance with a determination a first value associated with the first message exceeds a second value associated with the second message. Lee-Goldman teaches wherein the subset of the plurality of actions comprises a first action and a second action different from the first action (col. 22, lines 45-64, e.g., append the author name in the beginning, middle or end of the suggested keyword query), and the performing D) comprises generating the second message in accordance with a determination a first value associated with the first message exceeds a second value associated with the second message (col. 22, lines 45-64, e.g., performing generating a suggest keyword query (a second message) in accordance with a determination a fixed number of extracted keywords associated with the post is more than (i.e., exceed) the number of keywords in the suggested keyword query).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Lee-Goldman’s teaching with Morris’s system in order to improve the process of determining topics associated with a user message in Morris’s system, thus allowing a plurality of agents to collectively process the user message to generate a response.
Claims 31 and 32 are rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Pujare et al, WO 2014/197482 (hereinafter Pujare).
As per claim 31, Morris teaches the invention as claimed in claim 1 above. Morris is silent in regards to the automated content logic is associated with a typed schema governing a plurality of parameters and one or more authentication types. Pujare teaches wherein the automated content logic is associated with a typed schema governing a plurality of parameters and one or more authentication types [46].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Pujare’s teaching with Morris’s system in order to allow bots in Morris’s system to authenticate inputs, thus improving the security of Morris’s system.
As per claim 32, Morris teaches the invention as claimed in claim 1 above. Morris is silent in regards to the automated content logic is associated with a typed schema governing a plurality of parameters and one or more return types. Pujare teaches wherein the automated content logic is associated with a typed schema governing a plurality of parameters and one or more return types [46].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Pujare’s teaching with Morris’s system in order to allow bots in Morris’s system to authenticate inputs, thus improving the security of Morris’s system.
Claim 33 is rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Kolluru et al, GB 2517212 (hereinafter Kolluru).
As per claim 33, Morris teaches the invention as claimed in claim 1 above. Although Morris teaches wherein the first agent is trained on the training data [75], however, Morris is silent in regards to controlling, modifying, tailoring, adjusting, or a combination a coefficient, a weight, a hyperparameter, or a combination thereof that defines the behavior, learning, performance, or a combination thereof of the automated content logic. Kolluru teaches wherein the first agent is trained on the training data by controlling, modifying, tailoring, adjusting, or a combination a coefficient, a weight, a hyperparameter, or a combination thereof that defines the behavior, learning, performance, or a combination thereof of the automated content logic (pg. 11, lines 12-21; pg. 15, line 5-pg. 16, line 24).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Kolluru’s teaching with Morris’s system in order to allow training/optimizing of the first agent in Morris’s system to improve the performance of first agent in Morris’s system.
Claims 34 and 35 are rejected under 35 U.S.C. 103 as being unpatentable over Morris in view of Guy Frederick Bowerman, U.S. Patent Application Publication 2009/0100160 (hereinafter Bowerman).
As per claim 34, Morris teaches the invention as claimed in claim 1 above. Morris is silent in regards to scoped capability credential. Bowerman teaches wherein the automated content logic is associated with a scoped capability credential [20][30].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Bowerman’s teaching with Morris’s system in order to allow access control of the automated content logic in Morris’s system, thus improving the security of Morris’s system.
As per claim 35, Morris and Bowerman teach the invention substantially as claimed in claim 34 above. Bowerman further teach wherein the scoped capability credential defines at least one of:
i) a set of topics a respective agent module is authorized to address;
ii) access to a set of functions; or
iii) a set of data sources the respective agent module is authorized to access ([20][30], e.g., credential that only allow access to one or more data servers).
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set
forth in 37 CFR 1.136(a). A shortened statutory period for reply to this final action is set to expire
THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any extension fee pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/PHILIP C LEE/Primary Examiner, Art Unit 2454
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