DETAILED ACTION
This office action is in response to communication filed on 3 April 2025.
Claims 1 – 20 are presented for examination.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 – 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to the judicial exception of abstract ideas without significantly more. The independent claims recite receiving a user prompt related to an energy industry operation, analyzing the user prompt to interpret content, intent, and relevant context associated with the energy industry operation, generating a workflow based on an analysis of the user prompt, wherein the workflow defines a sequence of tasks, each task corresponding to a specialized function within the energy industry, communicating the workflow via a shared message pool, wherein each agent is configured to perform a specific role related to the user prompt, receiving responses to the workflow, wherein each response includes outputs from tasks, and compiling a response to the user prompt based on the received responses, wherein the response is tailored to address the user prompt within a context of the energy industry operation. This judicial exception is not integrated into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The eligibility analysis in support of these findings is provided below, in accordance section 2106 of the MPEP (hereinafter, MPEP 2106).
With respect to Step 1 of the eligibility inquiry (as explained in MPEP 2106), it is noted that the method, the computer readable medium, and the system are directed to an eligible categories of subject matter. Step 1 is satisfied.
With respect to Step 2A prong 1 of MPEP 2106, it is next noted that the claims recite an abstract idea by reciting concepts of workflow generation and task assignment with role configuration, as this is commercial interactions such as business relations or behaviors, which falls into the “certain methods of organizing human activity” group within the enumerated groupings of abstract ideas set forth in the MPEP 2106. The claimed invention also recites an abstract idea that falls within the mental processes grouping, as claims describe communicating, receiving, analyzing, and compiling responses. The limitations reciting the abstract idea in independent claims are receiving a user prompt related to an energy industry operation, analyzing the user prompt to interpret content, intent, and relevant context associated with the energy industry operation, generating a workflow based on an analysis of the user prompt, wherein the workflow defines a sequence of tasks, each task corresponding to a specialized function within the energy industry, communicating the workflow via a shared message pool, wherein each agent is configured to perform a specific role related to the user prompt, receiving responses to the workflow, wherein each response includes outputs from tasks, and compiling a response to the user prompt based on the received responses, wherein the response is tailored to address the user prompt within a context of the energy industry operation.
With respect to Step 2A Prong Two of the MPEP 2106, the judicial exception is not integrated into a practical application. The additional elements are directed to an artificial intelligence system, various agents, prompt interface, computer readable medium, processor, and computing system, to implement the abstract idea. However, these elements fail to integrate the abstract idea into a practical application because they are directed to the use of generic computing elements to perform the abstract idea, which is not sufficient to amount to a practical application (as noted in the MPEP 2106) and is tantamount to simply saying “apply it” using a general purpose computer, which merely serves to tie the abstract idea to a particular technological environment by using the computer as a tool to perform the abstract idea, which is not sufficient to amount to particular application.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
With respect to Step 2B of the eligibility inquiry, it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional limitations are directed to: an artificial intelligence system, various agents, prompt interface, computer readable medium, processor, and computing system. These elements have been considered, but merely serve to tie the invention to a particular operating environment, though at a very high level of generality and without imposing meaningful limitation on the scope of the claim. This does not amount to significantly more than the abstract idea, and it is not enough to transform an abstract idea into eligible subject matter. Such generic, high-level, and nominal involvement of a computer or computer-based elements for carrying out the invention merely serves to tie the abstract idea to a particular technological environment, which is not enough to render the claims patent-eligible, as noted at pg. 74624 of Federal Register/Vol. 79, No. 241, citing Alice, which in turn cites Mayo.
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Their collective functions merely provide conventional computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that the ordered combination amounts to significantly more than the abstract idea itself.
The dependent claims have been fully considered as well, however, similar to the finding for claims above, these claims are similarly directed to the abstract idea of concepts of further defining step assignment and publishing messages to a shared pool, without integrating it into a practical application and with, at most, a general purpose computer that serves to tie the idea to a particular technological environment, which does not add significantly more to the claims. The ordered combination of elements in the dependent claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide conventional computer implementation. Accordingly, the subject matter encompassed by the dependent claims fails to amount to significantly more than the abstract idea.
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 (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.
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 – 20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by U.S. P.G. Pub. 2021/0406774 (hereinafter, Browne).
Regarding claim 1, Browne teaches a method for coordinating tasks within an energy industry using a multi-agent artificial intelligence system, the method comprising:
receiving, by a coordination agent of a multi-agent artificial intelligent system, a user prompt related to an energy industry operation via a prompt interface (¶ 208, “The command-line interface can be configured to request information through a prompt for creating a new AI model such as a name for the new AI model.);
analyzing, by the coordination agent, the user prompt to interpret content, intent, and relevant context associated with the energy industry operation (¶ 235, “The AI engine can also determine when to train each concept, how much (or little) to train each concept based on its relevance, and, ultimately, produce a trained BRAIN.”);
generating, by the coordination agent, a workflow based on an analysis of the user prompt, wherein the workflow defines a sequence of tasks to be executed by a plurality of professional agents, each task corresponding to a specialized function within the energy industry (¶ 46, “From a Machine Learning perspective there are tools that have a graph representation (e.g., workflows) of a learning task which include trainable pieces and user defined nodes, which predefined models or user provided code.”);
communicating, by the coordination agent, the workflow to the plurality of professional agents via a shared message pool, wherein each professional agent is configured to perform a specific role related to the user prompt (¶ 194, “The architect module is coded and configured to take in the codified mental model and pedagogy and then propose a set of candidate low-level learning algorithms, topologies of a main task and concepts making up that main task, and configurations thereof the architect module believes will best be able to learn the concepts in the model.”);
receiving, by the coordination agent from the plurality of professional agents, responses to the workflow, wherein each response includes outputs from tasks executed by the plurality of professional agents (¶ 262, “1) the request and response cycle from all web browser based applications, 3) the request and response cycle from a dedicated on-line server, 4) the request and response cycle directly between a native application resident on a client device and the cloud-based remote access to another client computing system, and 5) combinations of these.”); and
compiling, by the coordination agent, a response to the user prompt based on the received responses from the plurality of professional agents, wherein the response is tailored to address the user prompt within a context of the energy industry operation (¶ 74, “For a hosted simulator, the project file contains the simulator declaration—that is currently not required for a local simulator. The project file may also contain i) Schema references for the predefined (keyword) schemas input, output, config, and state, and ii) custom schema declarations.”).
Regarding claim 2, Browne teaches the method of claim 1, wherein communicating, by the coordination agent, the workflow to the plurality of professional agents via the shared message pool comprises:
identifying a first professional agent to perform a first step in the workflow (¶ 118, “The concept node of the integrator concept can be trained via reinforcement learning to learn to choose from the two or more AI concepts in the levels stemming from the integrator node in the graph by choosing a particular concept that is considered most applicable based on a current state data.”);
generating a message intended for the first professional agent, wherein the message comprises an indication of the first professional agent as a recipient of the message and instructions for the first professional agent to perform a task associated with the first step in the workflow (¶ 118, “the AI engine may not choose a new concept at each time step but rather train a specific concept until it reaches a termination condition.”); and
publishing the message in the shared message pool (¶ 118, “The integrator may use concepts with a long-running termination condition: each concept can have pre-conditions for when it can be selected, and a run-until condition to meet before switching to another individual concept.”).
Regarding claim 3, Browne teaches the method of claim 2, wherein receiving, by the coordination agent from the plurality of professional agents, responses to the workflow comprises: receiving, from the first professional agent, a first output corresponding to the task; and analyzing, by the coordination agent, the first output to determine whether the first output satisfies the first step in the workflow (¶ 38, “A software process may be an instance of an executable file configured to perform a task in a finite amount of time (i.e., a job). Thus, each process is configured to operate for a finite amount of time to achieve its configured goal and then shut down until invoked again when needed in the future.”).
Regarding claim 4, Browne teaches the method of claim 3, further comprising: determining, by the coordination agent, that the first output does not satisfy the first step in the workflow; and responsive to the determining, generating, by the coordination agent, an updated message intended for the first professional agent, the updated message instructing the first professional agent to re-perform the task (¶ 243, “If the user decides further refinement of a BRAIN is needed, be it through additional training with existing data, additional training with new, supplemental data, or additional training with a modified version of the mental model or curricula used for training, the BRAIN-server is configured to support versioning of BRAINs so that the user can preserve (and possibly revert to) the current state of a BRAIN while refining the trained state of the BRAIN until a new, more satisfactory state is reached.”).
Regarding claim 5, Browne teaches the method of claim 3, further comprising: determining, by the coordination agent, that the first output does satisfy the first step in the workflow; and responsive to the determining: identifying a second professional agent to perform a second step in the workflow; generating a second message intended for the second professional agent, wherein the second message comprises a second indication of the second professional agent as a second recipient of the second message and second instructions for the second professional agent to perform a second task associated with the second step in the workflow; and publishing the second message in the shared message pool (¶ 33, “The architect module is also configured to create a second concept node derived from its description in a first scripted file, and to connect the second concept node into the graph of nodes in the resulting AI model.”).
Regarding claim 6, Browne teaches the method of claim 2, further comprising: generating, by the first professional agent, a first output by analyzing the instructions in the message (¶ 205, “The web-based interface can include a browser-based tool configured to access a web site for configuring and analyzing AI models stored in the AI engine. The web site can be used for sharing, collaborating, and learning. Some information that can be accessed from the web site is a visualization of a AI model's training progress.”).
Regarding claim 7, Browne teaches the method of claim 6, wherein generating, by the first professional agent, the first output by analyzing the instructions in the message comprises: determining a first analytical model for generating the first output; and responsive to the determining, calling the first analytical model to generate the first output by passing inputs to the first analytical model via one or more application programming interfaces (¶ 77, “Thus, the AI engine may use a first file, such as an Interface Definition Language file, to map the interface of the software container between an external entity of code and the corresponding API for the AI engine.”).
Regarding claims 8 and 15, the claims recite substantially similar limitations to claim 1. Therefore, claims 8 and 15 are similarly rejected for the reasons set forth above with respect to claim 1.
Regarding claims 9 and 16, the claims recite substantially similar limitations to claim 2. Therefore, claims 9 and 16 are similarly rejected for the reasons set forth above with respect to claim 2.
Regarding claims 10 and 17, the claims recite substantially similar limitations to claim 3. Therefore, claims 10 and 17 are similarly rejected for the reasons set forth above with respect to claim 3.
Regarding claims 11 and 18, the claims recite substantially similar limitations to claim 4. Therefore, claims 11 and 18 are similarly rejected for the reasons set forth above with respect to claim 4.
Regarding claims 12 and 19, the claims recite substantially similar limitations to claim 5. Therefore, claims 12 and 19 are similarly rejected for the reasons set forth above with respect to claim 5.
Regarding claim 13, the claim recites substantially similar limitations to claim 6. Therefore, claim 13 is similarly rejected for the reasons set forth above with respect to claim 6.
Regarding claim 14, the claim recites substantially similar limitations to claim 7. Therefore, claim 14 is similarly rejected for the reasons set forth above with respect to claim 7.
Regarding claim 20, the claim recites substantially similar limitations to claims 6 and 7, combined. Therefore, claim 20 is similarly rejected for the reasons set forth above with respect to claims 6 and 7, combined.
Conclusion
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/AMANDA GURSKI/Primary Examiner, Art Unit 3625
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