DETAILED ACTION
Acknowledgement
This final office action is in response to the amendment filed on 10/15/2025.
Status of Claims
Claims 4, 7, 20, 23, 36, and 39 have been cancelled.
Claims 1, 5, 8-10, 17, 21, 24-26, 33, 37, and 40-42 have been amended.
Claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are now pending.
Response to Arguments
The 35 U.S.C. 101 “signal per se” rejection of claims 17-32 is withdrawn in light of amendments.
Applicant's arguments filed on 10/15/2025 regarding the 35 U.S.C. 101 and 103 rejections of the pending claims have been fully considered. The Applicant argues the following.
As per the 101 rejection, the Applicant argues that independent claims 1, 17, and 33 as amended recite a practical application of the alleged abstract idea. The improvement is in allowing non-human distributed actors to autonomously interact with other distributed actors to obtain skills needed to resolve an unfulfilled need by replicating actions of the other distributed actors to teach the non-human distributed actor to perform the needed skill.
The Examiner respectfully disagrees. The Examiner submits that in order for the claims to reflect a practical application, the additional elements recited in the claims must reflect an improvement in the functioning of a computer or an improvement in technology or a technical field. The improvement argued by the Applicant is neither. Allowing non-human distributed actors to interact and learn from other distributed actors by replicating actions of other distributed actors can be considered abstract and a standard method of learning. An improvement in technology cannot be acknowledged without the details of what technological components are involved in the process and an explanation of how these components are technologically improved beyond their normal function. Therefore, the 35 U.S.C. 101 rejection is maintained.
As per the 103 rejection, the Applicant argues that Horvitz and Charisius fail to teach, disclose, or suggest the limitations in amended claims 1, 17, and 33.
The Examiner finds the Applicant’s arguments persuasive. Therefore, the previous 103 rejection has been withdrawn. However, upon further search and consideration, a new ground of 103 rejection is made for claims 1, 17, and 33. See details below.
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 .
Information Disclosure Statement
The information disclosure statements (IDSs) submitted on 06/16/2025, 09/15/2025, 12/02/2025, and 03/02/2026 are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are rejected under 35 U.S.C. 101 because the claimed invention, “Distributed Actor-Based Information System & Method”, is directed to an abstract idea, specifically Mental Processes and Certain Methods of Organizing Human Activity, without significantly more. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements individually or in combination provide mere instructions to implement the abstract idea on a computer.
Step 1: Claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are directed to a statutory category, namely a process (claims 1-3, 5-6, and 8-16), a manufacture (claims 17-19, 21-22, and 24-32), and a machine (claims 33-35, 37-38, and 40-48).
Step 2A (1): Claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are directed to an abstract idea of Mental Processes and Certain Methods of Organizing Human Activity, based on the following claim limitations: “monitoring an environment to detect the existence of an unfulfilled need by processing a request from a non-human distributed actor; identifying one or more needed skills that can collaboratively address the unfulfilled need, thus defining one or more needed skills; comparing the one or more needed skills to one or more available skills offered by one or more distributed actors to identify one or more missing skills required to address the unfulfilled need; generating one or more new skills to address the one or more missing skills required to address the unfulfilled need by: …communicating with a target distributed actor to resolve the unfulfilled need without direct human intervention; and processing one or more interactions of the target distributed actor during the replication of the browsing session to generate the one or more new skills to address the one or more missing skills (claims 1, 17, and 33); defining the one or more available skills offered by one or more distributed actors (claims 2, 18, and 34); wherein defining the one or more available skills offered by one or more distributed actors includes: reviewing exposed skill information about the one or more distributed actors (claims 3, 19, and 35); wherein detecting the existence of a request includes receiving a request from a human distributed actor (claims 5, 21, and 37); notifying one or more distributed actors who previously could have utilized the one or more new skills of the current availability of the one or more new skills (claims 8, 24, and 40); wherein the one or more new skills include one or more machine-generated skills (claims 9, 25, and 41); wherein the one or more new skills include one or more human-generated skills (claims 10, 26, and 42); addressing at least a first portion of the unfulfilled need with the one or more new skills (claims 11, 27, and 43); addressing at least a second portion of the unfulfilled need with one or more of the available skills offered by one or more distributed actors (claims 12, 28, and 44); wherein addressing at least a first portion of the unfulfilled need with the one or more new skills includes: generating at least a first response portion with the one or more new skills (claims 13, 29, and 45); forming a bespoke response to the unfulfilled need based, at least in part, upon the at least a first response portion from the one or more new skills (claims 14, 30, and 46); providing the bespoke response to a party associated with the unfulfilled need (claims 15, 31, and 47); and effectuating, in whole or in part, the bespoke response (claims 16, 32, and 48).
The independent claims describe a process of monitoring an environment to detect the existence of an unfulfilled need and/or a request, identifying skills needed to address the need/request, comparing needed skills to available skills offered by distributed actors to identify missing skills to address the need, and generating one or more new skill to address the one or more missing skills required. This process can practically be performed in the human mind via observation, evaluation, and with pen and paper. Dependent claims further describe defining the one or more available skills, detecting the existence of a request, the one or more distributed actors, the one or more new skills, and addressing the need/request with the one or more new and/or available skills offered by one or more distributed actors. Managing skills of distributed actors, receiving requests from human actors, and addressing the need/requests with skills associated with distributed actors or human actors reflect certain methods of organizing human activity as facilitating the fulfillment of needs/request with skills of distributed actors is managing personal behavior and the interaction between a person that has an unfulfilled need/request and a computer that is fulfilling the need/request. Therefore, these limitations, under the broadest reasonable interpretation, fall within the abstract groupings of Mental Processes and Certain Methods of Organizing Human Activity. Mental Processes includes concepts performed in the human mind such as observations, evaluations, judgments, and opinions and include claims directed to collecting information, analyzing it, and displaying certain results of the collection and analysis even if they are claimed as being performed on a computer. Certain Methods of Organizing Human Activity includes managing personal behavior or relationships or interactions between people including social activities, teaching, and following rules or instructions. Certain Methods of Organizing Human Activity can encompass the activity of a single person (e.g. a person following a set of instructions), activity that involve multiple people (e.g. a commercial interaction), and certain activity between a person and a computer (e.g. a method of anonymous loan shopping). Therefore, claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are directed to an abstract idea and are not patent eligible.
Step 2A (2): This judicial exception is not integrated into a practical application. In particular, claims 1, 6, 9, 17, 22, 25, 33, 38, and 41 recite additional elements of “a computer-implemented method, executed on a computing device (claim 1); performing a replication of a browsing session associated with the non-human distributed actor to the target distributed actor (claims 1, 17, and 33) wherein the group of distributed actors include one or more of: a software platform; a software application; a virtual machine; and a web-based service (claims 5, 21, and 37); machine-generated skills (claims 9, 25, and 41); a computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations (claim 17); and a computing system including a processor and memory configured to perform operations (claim 33)”. These additional elements do not integrate the abstract idea into a practical application because the claims do not recite (a) an improvement to another technology or technical field and (b) an improvement to the functioning of the computer itself and (c) implementing the abstract idea with or by use of a particular machine, (d) effecting a particular transformation or reduction of an article, or (e) applying the judicial exception in some other meaningful way beyond generally linking the use of an abstract idea to a particular technological environment. These additional elements evaluated individually and in combination are viewed as computing devices that are used to perform that abstract idea stated in Step 2A(1). Limitations that recite mere instructions to implement an abstract idea on a computer or merely uses a computer as a tool to perform an abstract idea are not indicative of integration into a practical application (see MPEP 2106.05(f)). Therefore, claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 do not include individual or a combination of additional elements that integrate the judicial exception into a practical application and thus are not patent eligible.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Claims 1, 6, 9, 17, 22, 25, 33, 38, and 41 recite additional elements of “a computer-implemented method, executed on a computing device (claim 1); performing a replication of a browsing session associated with the non-human distributed actor to the target distributed actor (claims 1, 17, and 33) wherein the group of distributed actors include one or more of: a software platform; a software application; a virtual machine; and a web-based service (claims 5, 21, and 37); machine-generated skills (claims 9, 25, and 41); a computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations (claim 17); and a computing system including a processor and memory configured to perform operations (claim 33)”. These additional elements evaluated individually and in combination are viewed as mere instructions to apply or implement the abstract idea on a computer. Applying an abstract idea on a computer does not integrate a judicial exception into a practical application or provide an inventive concept (see MPEP 2106.05(f)). Therefore, claims 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 do not include individual or a combination of additional elements that are sufficient to amount to significantly more than the judicial exception and thus are not patent eligible.
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 1-3, 5-6, 8-19, 21-22, 24-35, 37-38, and 40-48 are rejected under 35 U.S.C. 103 as being unpatentable over Horvitz et al. (US 2014/0278634 A1) in view of Charisius et al. (US 2002/0107914 A1) and in further view of Litty et al. (US 11,979,383 B1).
As per claims 1, 17, and 33 (Currently Amended), Horvitz teaches a computer-implemented method, executed on a computing device, comprising (Horvitz e.g. FIG. 4 is a flow diagram summarizing some example steps that may be taken by a geospatial crowdsourcing service or the like when a task is received, which may be in real time, or based upon a scheduled task [0057]. The techniques described herein can be applied to any device. Accordingly, the below general purpose remote computer described below in FIG. 5 is but one example of a computing device [0062]. A method implemented at least in part on at least one processor, comprising (claim 1).); A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising (Horvitz e.g. Computer 510 typically includes a variety of computer readable media and can be any available media that can be accessed by computer 510 (Fig. 5 and [0066]. One or more computer-readable media having computer-executable instructions, which when executed on at least one processor perform step (claim 19).); A computing system including a processor and memory configured to perform operations comprising (Horvitz e.g. With reference to FIG. 5, an example remote device for implementing one or more embodiments includes a general purpose computing device in the form of a computer 510 [0065]. A system comprising, one or more processors, a memory communicatively coupled to the processor, and a spatiotemporal crowdsourcing configured to execute on the one or more processors from memory,.. (claim 13).):
Horvitz teaches monitoring an environment to detect the existence of an unfulfilled need… (Horvitz e.g. FIG. 1 shows a task being received at a planning component 112, in which the task includes any number of criteria. Example criteria include a task deadline, a maximum cost, any reputation requirements, any acquaintance requirements and so on. Other criteria may specify a number of workers, skill sets required for the workers, non-human assets needed, and so forth. Basically any task requirement that may be matched against known data regarding actors' preferences and abilities to perform that task may be used as part of the task criteria [0024]. The planning component 112 (or another component of the service 102) may receive task completion state information, to ensure that tasks are completed by the deadline, with any re-planning as needed (e.g., an extra worker is needed) [0027]. State data also may be accessed, to determine the current state of an actor [0058]. Re-planning may be performed as state information comes in, e.g., the task is behind schedule and the task owner is willing to increase the budget to hire another worker, a confirmed worker did not show up, a piece of equipment broke down, and so forth. Tracking continues until the task is complete, as evaluated at step 416 [0060].)
Horvitz teaches identifying one or more needed skills that can collaboratively address the unfulfilled need, thus defining one or more needed skills; and (Horvitz e.g. FIG. 1 shows a task being received at a planning component 112, in which the task includes any number of criteria. Example criteria include a task deadline, a maximum cost, any reputation requirements, any acquaintance requirements and so on. Other criteria may specify a number of workers, skill sets required for the workers, non-human assets needed, and so forth. Basically any task requirement that may be matched against known data regarding actors' preferences and abilities to perform that task may be used as part of the task criteria [0024]. When a task needs to be performed, a subset of one or more actors is summoned by the planning component 112, which in the example of FIG. 1. In general, the planning component 112 uses the task criteria matching module 114 to work with the preference and ability component 106 to match the criteria associated with the task with an actor set (e.g., one or more users and/or any other actor or actors) [0025].)
Horvitz teaches comparing the one or more needed skills to one or more available skills offered by one or more distributed actors (Horvitz e.g. FIG. 1 is a block diagram showing example components of an example spatiotemporal crowdsourcing implementation, in the form of a service 102 [0018]. In general, users 104 register as actors (members) in the spatiotemporal crowdsourcing service via a network (e.g., Internet) interface, shown as coupling to a user task preference and ability component 106 [0018]. The preference and qualification information is stored in an actor data store 108, and may include a list of capabilities, competencies and/or experience (e.g., a math tutor for algebra to calculus, five years teaching), price/rate (including overtime), preferences (e.g., evenings OK but not weekends, will work within thirty minutes of a general location), assets e.g., (have a bike or car), calendar data, schedule data and/or possibly other pertinent information. This information may be updated in real time as it changes, either with explicit instructions from the user and/or automatically through sensing and inference [0019]. The planning component 112 operates in conjunction with the other components 106, 114 and 116 to coordinate the summoning of the equipment and personnel to a specified location at a desired time, based upon who is available, when and where, and their pricing, along with any other criteria such as experience, reputation and so forth [0027]. One or more actors are matched to task-related criteria and summoned to accomplish a task, which may be divided into a set of coordinated tasks (subtasks) [0061].)
Horvitz does not explicitly teach, however, Charisius teaches the following:
Charisius teaches…by processing a request from a non-human distributed actor; (Charisius e.g. FIG. 1 depicts a data processing system 100 suitable for practicing methods and systems consistent with the present invention [0074]. Memory 110 in computer 102a includes a Client Interface 134 to a Web-based “Distributed Authoring and Versioning” (WebDAV) server 140 in memory 112 [0076]. The WebDAV server 140 in memory 112 of computer 104 operates as a virtual file system for computers 102a, 102n, and 106 on the network 108 [0078]. Two separate enterprise affiliates using their respective Client Interfaces 134 on their respective computers 102a and 102n may independently request and view the same workflow or plan stored on WebDAV Storage 142 [0079]. The messages or requests directed to the WebDAV server 140 from the Client Interface 134 are initially sent to the WebDAV proxy 146. The WebDAV proxy 146 passes these messages and requests to the Management Modules 148 [0082]. The types of messages or requests serviced by the Management Modules 148 include activating a project plan, notifying various enterprise affiliates assigned to each task of the plan, and managing the execution of the plan to the enterprise affiliates [0082].)
Charisius teaches…to identify one or more missing skills required to address the unfulfilled need, (Charisius e.g. Charisius teaches methods and systems for optimizing resource allocation and resource profiles used in resource allocation based on data mined from plans created from a workflow [0006]. The method comprises the step of generating a plan to perform an instance of the process. The generated plan has tasks performed by resources. Each resource has capabilities that are considered when generating the plan to ensure that, for each task, a suitable one of the resources is selected to perform the task [0013]. FIG. 1 depicts a data processing system 100 suitable for practicing methods and systems consistent with the present invention [0074]. The Client Interface 134 allows any enterprise affiliate to create, delete, move, and copy workflows, project plans, and associated roles/resource lists on WebDAV server 140 [0079]. The enterprise affiliates may be employees, managers, administrators, suppliers, customers, or other users within the enterprise who may need to create, view, or receive information regarding an activated project plan in accordance with methods and systems consistent with the present invention [0075]. The Resource Manager Module 206 further allows an enterprise affiliate to create, modify, and store the resource profiles (e.g., the person, equipment, or systems, such as a development facility) that may be assigned to a task of a plan created from a workflow (Fig. 2 and [0093]). The Resource/Role Management Module 220 reviews requests from an enterprise affiliate to assign a resource to a plan (e.g., to assign a user to a task of the plan) [0105]. The Client Interface 134 may also receive other resource information (not shown) for other types of resources (e.g., equipment, facilities, computer systems, or other known entities) that may be assigned to any task of a plan [0162]. Resource information 5404 may also include one or more skill identifiers that indicate one or more capabilities that a task of a plan may require for the task to be completed. Skill identifiers may include any foreseeable skill for the named resource, including a user, equipment, facilities, computer systems, or other known entities that may be assigned to any task of a plan [0163]. When performing the resource allocation process, the Client Interface examines whether a resource has one or more skills that indicate one or more capabilities that a task of a plan may require for the task to be completed [0180]. To perform the resource allocation process, the Client Interface accesses a profile for the role to identify the skill and the corresponding skill strength for the role (i.e., capabilities that a task of a plan may require) and accesses a resource profile for the resource to identify if the resource has the same skill and the same or greater skill strength (i.e., same or greater capabilities than the task of the plan requires) [0180]. After identifying all skills associated with a role for each logged task where the resource was manually assigned, the Client Interface determines if the resource is missing a skill (Step 6758). To determine if the resource is missing a skill, the Client Interface retrieves the profile for the resource and compares the skill set in the resource profile to the skills or skill identified for the role (Fig. 67D and [0216]).)
Charisius teaches generating one or more new skills to address the one or more missing skills required to address the unfulfilled need (Charisius e.g. When it is determined that the resource is missing a skill, the Client Interface generates a suggestion to improve the resource profile by adding the missing skill to the resource profile (Step 6760). For example, the Client Interface generates a suggestion to improve “MG' profile 7104 by adding the missing “Chicago plant receiving logistics’ Skill 7030 to “MG’ Skill Set 7116. [0217].):
Charisius teaches by autonomously communicating with a target distributed actor to resolve the unfulfilled need without direct human intervention; (Charisius e.g. After generating a suggestion to add a missing skill to the resource profile or after generating a suggestion to increase a skill strength in the resource profile, the Client Interface notifies the enterprise affiliate of the suggestion to improve the resource profile [0220]. After notifying the enterprise affiliate of the suggestion to improve the profile of the resource, the Client Interface determines if the suggested improvement is to be implemented [0221]. When it is determined that the suggested improvement is to be implemented, the Client Interface modifies the profile of the resource to reflect the suggested improvement (Step 6770). For example, when the suggested improvement is to add the missing skill to the resource profile, the Client Interface adds the missing “Chicago plant receiving logistics' skill 7030 to skill set 7116 in “MG” resource profile 7104 [0222]. Thus, when creating a subsequent plan from “AssemblyWorkflow” definition file 6800 and performing resource allocation processing for the plan, the Client Interface recognizes that improved “MG' resource profile 7104 has an improved skill set that matches “Gopher skill set 7018 and that has higher corresponding skill strengths than “MA” skill set 7114. Therefore, the Client Interface automatically assigns “MG” resource in lieu of “MA” resource to the “Gopher role of a new task created from “Get Parts” activity 6804 in FIG. 68 [0222].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include processing a request from non-human distributed actor, identifying one or more missing skills required to address the unfulfilled need, and generating one or more new skills to address the one or more missing skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
Horvitz nor Charisius explicitly teach, however Litty teaches the following:
Litty teaches performing a replication of a browsing session associated with the non-human distributed actor to the target distributed actor; and (Litty e.g. Transparent web browsing recording is disclosed (Abstract). FIG. 1 illustrates an embodiment of an environment in which surrogate browsing services ( also referred to herein as isolated browsing services) are provided (col. 3 lines 4-6). In the example shown, client device 102 (e.g., a laptop computer) is executing a client browser application 104 (col. 3 lines 6-8). Surrogate browsing system 106 provides protection to browsers such as browser 104 by obtaining and rendering content on behalf of users, and then transmitting a representation of that content on to the client browser (col. 3 lines 32-36). When system 106 is referred to herein as performing a task, such as transmitting or processing data, it is to be understood that a sub-component or multiple sub-components of system 106 (whether individually or in cooperation with third party components) may cooperate to perform that task (col. 3 lines 55-59). A browser plugin installed on client browser 104, and/or native functionality of client browser 104, as applicable, can be configured to cause Alice's request for site 110 to be directed through system 106 (col. 4 lines 11-14). FIG. 3 illustrates an embodiment of a surrogate browsing system. Surrogate browsing system 302 is one embodiment of surrogate browsing system 106 (col. 5 lines 21-22). In the example shown in FIG. 3, when Alice requests access to a page on site 110 (e.g., by clicking submit button 206), a virtual machine 304, in which a surrogate browser application 306 is executing, is made available to browser 104. An image of the page is sent by surrogate browsing system 302 to client 102 (308). In some embodiments, the image sent to Alice is transcoded so that, for example, an attacker cannot send malicious pixels to Alice. When Alice interacts with the image via her browser 104, her events, such as mouse clicks and keyboard presses, are observed and transmitted by the JavaScript executing on client 102 to virtual machine 304 (310). System 302 interprets the received events (e.g., by overlaying the position of the events on Alice's rendering of the page on top of the page as seen by system 302) and surrogate browser 306 takes the corresponding actions with respect to site 110, if applicable. For example, if Alice attempts to click a link on the page she is viewing, her click event is sent to system 302 and browser 306 replicates Alice's click on site 110. If Alice is randomly clicking in white space, in some embodiments, the event is not replicated to site 110. As browser 306's view of the page changes (e.g., a new page is displayed due to following a link), updated images are streamed to Alice's browser 104 (col. 5 lines 31-53). The surrogate browsing approach depicted in FIG. 3 will protect Alice's computer 102 against attacks, such as drive-by downloads and zero-day exploits, that may be present on site 110. Further, with respect to certain websites (e.g., ones with relatively simple layouts), Alice may be unable to distinguish between the experience of accessing the site directly with her browser, or accessing the site using surrogate browsing system 302 (col. 5 lines 54-61).)
Litty teaches processing one or more interactions of the target distributed actor during the replication of the browsing session to generate the one or more new skills to address the one or more missing skills. (Litty e.g. The surrogate browser renders requested pages and runs JavaScript code within the pages. It also contains an event simulator component 416 that applies user interaction events (e.g., 310) received from client 102 (col. 7 lines 23-26). In various circumstances, it would be desirable to have a record of what took place when a user interacted with a remote website. As one example, if a user falls victim to a phishing website, it would be desirable to know what information, if any, the user provided to the website (e.g., a username, both a username and password, etc.) and/or what information was transferred to the user (e.g., a screenshot of the rendered website). One approach to capturing browsing-related data is to record network trace data (e.g., packet traces captured at an Internet gateway) and then attempt to reconstruct, based on the captured network traffic, what occurred (col. 19 lines 54-65). Described herein are embodiments of an enterprise-scalable browser recording system that can capture users' web-page interactions across all types of browsers and all devices in the enterprise, and also capture resulting page state (e.g., screen shots, DOM/CSS tree, script state, and network requests/responses). The recording functionality described herein can be used for securely conducting transparent and reliable security forensics of very large user populations (col. 20 lines 7-15). FIG. 25 illustrates an embodiment of a process for recording web browsing information. In various embodiments, process 2500 is performed by system 702. (col. 24 lines 65-67). FIGS. 30B-30H illustrate various interfaces provided by an example browsing forensics viewer. Using the browsing forensics viewer, the administrator can see a page as it appeared to the end user throughout the browsing session, as well as see user activity events, such as entry of text into a field (col. 31 lines 9-15).)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz in view of Charisius’s task planning process to include generating one or more new skills…by performing a replication of a browsing session associated with the non-human distributed actor to the target distributed actor and processing one or more interactions of the target distributed actors during the replication of the browsing session to generate as taught by Litty in order to allow security teams to easily see what the user saw (e.g. screenshots) and inputted into the page (e.g. keystrokes) (col. 33 lines 5-7) and to secure computer interactions (e.g. with browsers and websites) (col. 1 lines 39-40).
As per claims 2, 18, and 34 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1 further comprising; the computer program product of claim 17 further comprising; and the computing system of claim 33 Horvitz teaches further comprising: defining the one or more available skills offered by one or more distributed actors. (Horvitz e.g. The spatiotemporal crowdsourcing service selects an actor set (e.g., one or more human workers and/or entities) for accomplishing the task, including having the task-related criteria and actor-related data used to determine inclusion in the actor set [0005]. The preference and qualification information is stored in an actor data store 108, and may include a list of capabilities, competencies and/or experience (e.g., a math tutor for algebra to calculus, five years teaching), price/rate (including overtime), preferences (e.g., evenings OK but not weekends, will work within thirty minutes of a general location), assets e.g., (have a bike or car), calendar data, schedule data and/or possibly other pertinent information. This information may be updated in real time as it changes, either with explicit instructions from the user and/or automatically through sensing and inference [0019]. The planning component 112 operates in conjunction with the other components 106, 114 and 116 to coordinate the summoning of the equipment and personnel to a specified location at a desired time, based upon who is available, when and where, and their pricing, along with any other criteria such as experience, reputation and so forth [0027]. One or more actors are matched to task-related criteria and summoned to accomplish a task, which may be divided into a set of coordinated tasks (subtasks) [0061].)
As per claims 3, 19, and 35 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 2, the computer program product of claim 18, and the computing system of claim 34, Horvitz teaches wherein defining the one or more available skills offered by one or more distributed actors includes: reviewing exposed skill information about the one or more distributed actors (Horvitz e.g. The spatiotemporal crowdsourcing service selects an actor set (e.g., one or more human workers and/or entities) for accomplishing the task, including having the task-related criteria and actor-related data used to determine inclusion in the actor set [0005]. Example criteria include a task deadline, a maximum cost, any reputation requirements, any acquaintance requirements and so on. Other criteria may specify a number of workers, skill sets required for the workers, non-human assets needed, and so forth. Basically any task requirement that may be matched against known data regarding actors' preferences and abilities to perform that task may be used as part of the task criteria [0024]. When a task needs to be performed, a subset of one or more actors is summoned by the planning component 112, which in the example of FIG. 1. In general, the planning component 112 uses the task criteria matching module 114 to work with the preference and ability component 106 to match the criteria associated with the task with an actor set (e.g., one or more users and/or any other actor or actors) [0025].)
As per claims 5, 21, and 37 (Currently Amended), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1, the computer program product of claim 17, and the computing system of claim 33, Horvitz teaches wherein detecting the existence of a request includes receiving a request from a human distributed actor (Horvitz e.g. FIG. 4 is a flow diagram summarizing some example steps that may be taken by a geospatial crowdsourcing service or the like when a task is received, which may be in real time, or based upon a scheduled task [0057]. Step 410 evaluates whether the needed distributed actors have confirmed and the summoning is done. Note that if the task criteria cannot be met, step 412 represents notifying the owner of the issue (i.e. human) [0059]. The actor set includes at least one human actor and at least one non-human actor (claim 14).).
As per claims 6, 22, and 38 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1, the computer program product of claim 17, and the computing system of claim 33, Horvitz teaches wherein the one or more distributed actors include one or more of: a software platform; a software application; a virtual machine; and a web-based service (Horvitz e.g. Users are one type of actor that may be summoned to accomplish a task. Although not explicitly shown in FIG. 1, other example types of actors that may have actor data stored in the data store108 include non-human participants, such as a sensor (e.g., as a security camera, traffic camera and/or microphone), an automobile equipped with communication capabilities, tagged equipment, and so forth. Such other non-human actors may be summoned as part of accomplishing a task, as described below [0020]. Via contemporary computer-aware connectedness, mobile actors also may provide current state information (e.g., via a mobile device application) such as including current GPS coordinates and velocity at a certain sampling rate, and possibly a destination. A non-human mobile actor may likewise provide such state information, e.g., via GPS coordinates and velocity, a nearby truck may be summoned to help accomplish a task, regardless of who is actually driving the truck [0021]. Embodiments can partly be implemented via an operating system, for use by a developer of services for a device or object, and/or included within application software that operates to perform one or more functional aspects of the various embodiments described herein [0063].).
As per claims 8, 24, and 40 (Currently Amended), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1 further comprising; the computer program product of claim 17; and the computing system of claim 33 further comprising: Horvitz does not explicitly teach, however, Charisius teaches notifying one or more distributed actors who previously could have utilized the one or more new skills of the current availability of the one or more new skills (Charisius e.g. After generating a suggestion to add a missing skill to the resource profile or after generating a suggestion to increase a skill strength in the resource profile, the Client Interface notifies the enterprise affiliate of the suggestion to improve the resource profile [0220]. After notifying the enterprise affiliate of the suggestion to improve the profile of the resource, the Client Interface determines if the suggested improvement is to be implemented [0221]. When it is determined that the suggested improvement is to be implemented, the Client Interface modifies the profile of the resource to reflect the suggested improvement (Step 6770). For example, when the suggested improvement is to add the missing skill to the resource profile, the Client Interface adds the missing “Chicago plant receiving logistics' skill 7030 to skill set 7116 in “MG” resource profile 7104 [0222]. Thus, when creating a subsequent plan from “AssemblyWorkflow” definition file 6800 and performing resource allocation processing for the plan, the Client Interface recognizes that improved “MG' resource profile 7104 has an improved skill set that matches “Gopher skill set 7018 and that has higher corresponding skill strengths than “MA” skill set 7114. Therefore, the Client Interface automatically assigns “MG” resource in lieu of “MA” resource to the “Gopher role of a new task created from “Get Parts” activity 6804 in FIG. 68 [0222].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include notifying one or more distributed actors who previously could have utilized the one or more new skills of the current availability of the one or more new skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 9, 25, and 41 (Currently Amended), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1, the computer program product of claim 17, and the computing system of claim 33 Horvitz does not explicitly teach, however, Charisius teaches wherein the one or more new skills include one or more machine-generated skills (Charisius e.g. The Resource Manager Module 206 further allows an enterprise affiliate to create, modify, and store the resource profiles (e.g., the person, equipment, or systems, such as a development facility) that may be assigned to a task of a plan created from a workflow [0093]. Resource information 5404 may also include one or more skill identifiers that indicate one or more capabilities that a task of a plan may require for the task to be completed. Skill identifiers may include any foreseeable skill for the named resource, including a user, equipment, facilities, computer systems, or other known entities that may be assigned to any task of a plan [0163]. For example, when the named resource is an enterprise affiliate, the skill identifiers that may be identified for the enterprise affiliate may include: “Java programming,” “architecture,” or “carpentry.” When the named resource is equipment, the skill identifiers may include “punch-press” or “Windows NT Operating System.” Resource information 5404 may also include a skill strength (not shown) for each skill identifier. The skill strength may be used by the tool to differentiate one resource from another resource when matching a resource to a role of a task in a plan [0163].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include one or more new skills include one or more machine-generated skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 10, 26, and 42 (Currently Amended), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1, the computer program product of claim 17, and the computing system of claim 33 Horvitz does not explicitly teach, however, Charisius teaches wherein the one or more new skills include one or more human-generated skills (Charisius e.g. The Resource Manager Module 206 further allows an enterprise affiliate to create, modify, and store the resource profiles (e.g., the person, equipment, or systems, such as a development facility) that may be assigned to a task of a plan created from a workflow [0093]. Resource information 5404 may also include one or more skill identifiers that indicate one or more capabilities that a task of a plan may require for the task to be completed. Skill identifiers may include any foreseeable skill for the named resource, including a user, equipment, facilities, computer systems, or other known entities that may be assigned to any task of a plan [0163]. For example, when the resource is a person, the Tool Server 144 may recognize that the person can play a given role (e.g., Analyst) in a specific activity in a workflow (e.g., Software Development Process) based on the skills or capabilities required by the role assigned to the activity to be performed [0093]. The Client Interface improves a profile associated with the replacement resource by adding a skill or increasing a strength of the skill in the profile, where the skill is also associated with the role of the mined task [0175].).
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include one or more new skills include one or more human-generated skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 11, 27, and 43 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 1 further comprising; the computer program product of claim 17 further comprising; and the computing system of claim 33 further comprising: Horvitz does not explicitly teach, however, Charisius teaches addressing at least a first portion of the unfulfilled need with the one or more new skills (Charisius e.g. When it is determined that the suggested improvement is to be implemented, the Client Interface modifies the profile of the resource to reflect the suggested improvement (Step 6770). Thus, when creating a subsequent plan from “AssemblyWorkflow” definition file 6800 and performing resource allocation processing for the plan, the Client Interface recognizes that improved “MG' resource profile 7104 has an improved skill set that matches “Gopher skill set 7018 and that has higher corresponding skill strengths than “MA” skill set 7114. Therefore, the Client Interface automatically assigns “MG” resource in lieu of “MA” resource to the “Gopher role of a new task created from “Get Parts” activity 6804 in FIG. 68 [0222].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include addressing at least a first portion of the unfulfilled need with the one or more new skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 12, 28, and 44 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 11 further comprising; the computer program product of claim 27 further comprising; and the computing system of claim 43 further comprising: Horvitz teaches addressing at least a second portion of the unfulfilled need with one or more of the available skills offered by one or more distributed actors (Horvitz e.g. One or more actors are matched to task-related criteria and summoned to accomplish a task, which may be divided into a set of coordinated tasks (subtasks) [0061]. Other criteria may specify a number of workers, skill sets required for the workers, non-human assets needed, and so forth. Basically any task requirement that may be matched against known data regarding actors' preferences and abilities to perform that task may be used as part of the task criteria [0024].).
As per claims 13, 29, and 45 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 11, the computer program product of claim 27, and the computing system of claim 43 wherein addressing at least a first portion of the unfulfilled need with the one or more new skills includes: Horvitz does not explicitly teach, however, Charisius teaches generating at least a first response portion with the one or more new skills. (Charisius e.g. After generating the plan, the tool receives modification information indicating that the capabilities of one of the resources has changed, and assigns the resources to the tasks to generate a new plan by using the received modification information (Abstract) and [0011]. Wherein the step of receiving modification information includes the step of assigning a new capability to the one resource that indicates the one resource is capable of performing an additional one of the tasks (claim 3). When it is determined that the suggested improvement is to be implemented, the Client Interface modifies the profile of the resource to reflect the suggested improvement (Step 6770) [0222]. The Client Interface also automatically assigns a resource to a role for each task based on a resource allocation process, such as matching a role having a skill and a corresponding skill strength to a resource having the same skill and the same or greater skill strength. Thus, when performing the resource allocation process, the Client Interface examines whether a resource has one or more skills that indicate one or more capabilities that a task of a plan may require for the task to be completed [0180]. Thus, when creating a subsequent plan from “AssemblyWorkflow” definition file 6800 and performing resource allocation processing for the plan, the Client Interface recognizes that improved “MG' resource profile 7104 has an improved skill set that matches “Gopher skill set 7018 and that has higher corresponding skill strengths than “MA” skill set 7114. Therefore, the Client Interface automatically assigns “MG” resource in lieu of “MA” resource to the “Gopher role of a new task created from “Get Parts” activity 6804 in FIG. 68 [0222].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include generating at least a first response portion with the one or more new skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 14, 30, and 46 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 13 further comprising; the computer program product of claim 29 further comprising; and the computing system of claim 45 further comprising: Horvitz does not explicitly teach, however, Charisius teaches forming a bespoke response to the unfulfilled need based, at least in part, upon the at least a first response portion from the one or more new skills (Charisius e.g. After generating the plan, the tool receives modification information indicating that the capabilities of one of the resources has changed, and assigns the resources to the tasks to generate a new plan by using the received modification information (Abstract) and [0011]. The tool 200 may automatically assign a resource to a role of a task in the plan based on the identified, capable resources for the role [0154]. The responsible resource 5012 of the task is the resource with the authority to notify the tool 200 when the task is complete. The owner(s) 5014 of the task, on the other hand, are notified when the task is started or completed [0155].)
The Examiner submits that before the effective filing date, it would have been obvious to one of ordinary skill in the art to modify Horvitz’s task planning process to include forming a bespoke response to the unfulfilled need based, at least in part, upon the at least a first response portion from the one or more new skills as taught by Charisius in order to improve resource allocation to a given plan (Abstract).
As per claims 15, 31, and 47 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 14 further comprising; the computer program product of claim 30 further comprising; and the computing system of claim 46 further comprising: providing the bespoke response to a party associated with the unfulfilled need (Horvitz e.g. The planning component 112 operates in conjunction with the other components 106, 114 and 116 to coordinate the summoning of the equipment and personnel to a specified location at a desired time, based upon who is available, when and where, and their pricing, along with any other criteria such as experience, reputation and so forth [0027]. Bidding or the like may be implemented, e.g., different actors and/or groups may bid on the task [0026]. One or more actors are matched to task-related criteria and summoned to accomplish a task, which may be divided into a set of coordinated tasks (subtasks) [0061]. Note that if the task criteria cannot be met, step 412 represents notifying the owner of the issue [0059].).
As per claims 16, 32, and 48 (Original), Horvitz in view of Charisius and Litty teach the computer-implemented method of claim 14 further comprising; the computer program product of claim 30 further comprising; and the computing system of claim 46 further comprising: effectuating, in whole or in part, the bespoke response (Horvitz e.g. When a task needs to be performed, a subset of one or more actors is summoned by the planning component 112, which in the example of FIG. 1 [0025]. One or more actors are matched to task-related criteria and summoned to accomplish a task, which may be divided into a set of coordinated tasks (subtasks) [0061]. Users are one type of actor that may be summoned to accomplish a task… Such other non-human actors may be summoned as part of accomplishing a task [0020]. For example, crowdphysics tasks may be performed using spatiotemporal crowdsourcing such as reducing traffic congestion. Given a sufficient percentage of participants' locations and velocities, a traffic flow model may be implemented, according to which participants may be notified ( e.g., audibly while driving) to get into a certain lane, drive at a certain speed, detour to avoid an accident scene and so forth. Participants may be separately notified of an optimal or advantageous departure time, (e.g., "Based upon traffic, the system recommends leaving no earlier than 5:15 pm") ([0029] and [0031]).).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 nonprovisional extension fee (37 CFR 1.17(a)) 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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/A.M./Examiner, Art Unit 3624
/Jerry O'Connor/Supervisory Patent Examiner,Group Art Unit 3624