Abstract: Systems and methods for generating and providing experience recommendations to members of a task facilitation service are provided. A task recommendation system can identify a set of experience recommendations within a geographic region. These experience recommendations are ordered based on a member profile. The ordered experience recommendations are provided such that one or more experience recommendations can be selected for presentation to the member. When the member selects an experience recommendation, tasks corresponding to the experience recommendation are generated and performance of these tasks is monitored. The member profile is updated based on the performance of these tasks, the selected experience recommendation, and feedback corresponding to performance of these tasks.

Abstract: Systems and methods for proposal acceptance in a task determination system are provided. The task determination system receives in real-time a set of messages through a communications session associated with a task. The set of messages are processed in real-time to identify a response to a set of proposals for completion of the task. Based on the response, the task determination system generates one or more proposal tasks performable to complete the task. The task determination system performs one or more actions according to the one or more proposal tasks to complete the task. The task determination system updates the member profile in real-time based on these actions, the task, and the response to the set of proposals.

Abstract: Disclosed embodiments provide a framework to identify and recommend tasks that can be performed for the benefit of a member. Through this framework, a member is assigned with a representative that, over time, learns about the member's preferences and behavior, which can be used to recommend tasks that can be performed to reduce the member's cognitive load. Further, as the representative develops a relationship with the member over time, the representative can also curate experiences for the member and assist the member in achieving personal goals and ambitions.

Abstract: Systems and methods for identifying and recommending tasks that may be performed in order to achieve member goals are provided. A system processes messages in real-time as these messages are exchanged to identify a goal and a timeframe from achieving the goal. Based on the goal and the corresponding timeframe, the system identifies task groupings corresponding to different methods for achieving the goal. The task groupings are ordered according to the likelihood of the member selecting a task grouping. When a member selects a task grouping, the system can monitor in real-time the performance of tasks of the task grouping to determine whether the goal is being achieved. If any tasks are not being performed successfully, the system can automatically adjust the remaining tasks, select new tasks, and/or adjust the timeframe for achieving the goal in order to provide the member with an opportunity to achieve the goal.

Abstract: Systems and methods for delegating tasks for a task facilitation service include receiving a delegation indicator for a task and determining a communication policy for the task in response to receiving the delegation indicator. The communication policy generally inhibits communication between the task facilitation service and a member of the service. Generation of proposals for completing delegated tasks and prediction of missing task data are also facilitated by aspects of the task facilitation service.

Abstract: Automated message tagging in a chat forward task facilitation communication system is described. One implementation involves receiving a set of messages between a member and a representative as the set of messages are being exchanged, processing the set of messages to identify one or more task flags associated with the set of messages, where the one or more task flags correspond to a set of tasks performable by the representative on behalf of the member, and tracking a chat flow within a chat interface, wherein the set of messages are exchanged within the chat interface. The chat flow is processed using a tagging algorithm to automatically assign at least one of the one or more task flags to messages of the set of messages, and message history is generated including the set of messages and corresponding task flag assignments with associated tasks of the set of tasks.

Abstract: Message filtering and management systems in a chat forward task facilitation communication system are described. One implementation involves receiving one or more pre-filtering inputs from a member, where the inputs include task associations to identify message types to hide or display from a real-time chat interface based on the task associations. A set of messages are processed in real-time using a filtering algorithm to associate one or more tasks with messages of the set of messages, where the one or more tasks correspond to a set of tasks performable by the representative on behalf of the member. A first message is displayed based on the one or more pre-filtering inputs and a first task association with the first message, and a second message is hidden or not displayed based on the one or more pre-filtering inputs and a second task association with the second message.

Abstract: Automated message tagging in a chat forward task facilitation communication system is described. One implementation involves receiving a set of messages between a member and a representative as the set of messages are being exchanged, processing the set of messages to identify one or more task flags associated with the set of messages, where the one or more task flags correspond to a set of tasks performable by the representative on behalf of the member, and tracking a chat flow within a chat interface, wherein the set of messages are exchanged within the chat interface. The chat flow is processed using a tagging algorithm to automatically assign at least one of the one or more task flags to messages of the set of messages, and message history is generated including the set of messages and corresponding task flag assignments with associated tasks of the set of tasks.

Abstract: Message filtering and management systems in a chat forward task facilitation communication system are described. One implementation involves receiving one or more pre-filtering inputs from a member, where the inputs include task associations to identify message types to hide or display from a real-time chat interface based on the task associations. A set of messages are processed in real-time using a filtering algorithm to associate one or more tasks with messages of the set of messages, where the one or more tasks correspond to a set of tasks performable by the representative on behalf of the member. A first message is displayed based on the one or more pre-filtering inputs and a first task association with the first message, and a second message is hidden or not displayed based on the one or more pre-filtering inputs and a second task association with the second message.

Abstract: Systems and methods for generating and curating projects and tasks based on messages exchanged between members and assigned representatives are provided. A system receives, in real-time, a set of messages between a member and a representative as the set of messages are being exchanged. The system, based on these messages, automatically identifies a task that can be performed for the benefit of the member. The system can further identify additional information required for defining the task based on the member's preferences. The system can dynamically generate prompts for this additional information, which are provided to the member to obtain the additional information. The task is updated based on the additional information and is performed according to the parameters of the task and the additional information.

Abstract: Task reminder surfacing in a communication system is described. One implementation involves receiving a set of messages associated with a member device and a representative device, processing the set of messages to generate task data including one or more task recommendations associated with the set of messages, wherein the one or more task recommendations correspond to a set of tasks performable on behalf of the member, and tracking a real-time chat flow within a chat interface. The real-time chat flow is processed in real-time as messages of the set of messages are received using a scheduling algorithm to select a position or timing for one or more reminders associated with the one or more task recommendations, the reminders are automatically inserted within the chat flow using the position or timing for the one or more reminders, and the one or more reminders are presented within the chat flow.

Abstract: Systems and methods are presented herein for implementing dynamic interfaces in task-facilitation services. The task-facilitation service may receive authorization to execute a proposal that corresponds to an implementation of a task. The proposal may include an identification of third-party service providers that are configured to execute a task. The task-facilitation service may identify a first interface configured to translate commands of a task-facilitation service into native commands of the third-party service providers. The task-facilitation service may transmit a first communication including the commands to the third-party service providers. In response, the task-facilitation service may receive a first request for a set of resources. The task-facilitation service may define a resource-allocation mapping configured to identify the set of resources and distribute the set of resources to the third-party service providers. The task-facilitation service may then execute the resource-allocation mapping.

Abstract: Systems and methods for delegating tasks for a task facilitation service include receiving a delegation indicator for a task and determining a communication policy for the task in response to receiving the delegation indicator. The communication policy generally inhibits communication between the task facilitation service and a member of the service. Generation of proposals for completing delegated tasks and prediction of missing task data are also facilitated by aspects of the task facilitation service.

Abstract: Systems and methods are presented herein for implementing reinforcement learning in a task-facilitation service. The task-facilitation service may receive a request to delegate an execution of a task. The request can may include a user identifier that corresponds to the task. The task-facilitation service may generate a proposal using a machine-learning process. The proposal may include an implementation of the task and facilitate execution of the task by one or more third-party service providers. The task-facilitation service may facilitate the execution of the task by the one or more third-party service providers according to the proposal. In response to receiving an execution status of the task, the task-facilitation service may train the machine-learning process using the proposal and the execution status to improve subsequent proposals generated by the machine-learning process.

Abstract: Message filtering and management systems in a chat forward task facilitation communication system are described. One implementation involves receiving one or more pre-filtering inputs from a member, where the inputs include task associations to identify message types to hide or display from a real-time chat interface based on the task associations. A set of messages are processed in real-time using a filtering algorithm to associate one or more tasks with messages of the set of messages, where the one or more tasks correspond to a set of tasks performable by the representative on behalf of the member. A first message is displayed based on the one or more pre-filtering inputs and a first task association with the first message, and a second message is hidden or not displayed based on the one or more pre-filtering inputs and a second task association with the second message.

Abstract: Systems and methods are presented herein for generating user models based on user interaction with a task-facilitation service. The task-facilitation service can transmit a set of queries that when received at a computing device cause the computing device to generate a set of responses to the set of queries. The task-facilitation service may receive the set of responses to the set of queries. The set of responses can include an identification of one or more information sources associated a user of the computing device. The task-facilitation service may generate a feature vector that includes a subset of features extracted from the set of responses. The task-facilitation service may then generate a user model using the feature vector. The user model may be usable to define one or more tasks for execution by a remote service.

Abstract: Systems and methods for automatically throttling active tasks based on the cognitive load of members and assigned representatives are provided. A system receives, in real-time, a set of messages between a member and a representative as the set of messages are being exchanged. The system, based on these messages, automatically detects an indication of a change in the member's cognitive load and identifies the cognitive load based on the tasks being performed for the member, the presentation of these tasks, and the set of messages. If the member's cognitive load exceeds a threshold, the system dynamically selects one or more active tasks for migration to a suspended state. The remaining active tasks are performed for the benefit of the member.

Abstract: Automated message tagging in a chat forward task facilitation communication system is described. One implementation involves receiving a set of messages between a member and a representative as the set of messages are being exchanged, processing the set of messages to identify one or more task flags associated with the set of messages, where the one or more task flags correspond to a set of tasks performable by the representative on behalf of the member, and tracking a chat flow within a chat interface, wherein the set of messages are exchanged within the chat interface. The chat flow is processed using a tagging algorithm to automatically assign at least one of the one or more task flags to messages of the set of messages, and message history is generated including the set of messages and corresponding task flag assignments with associated tasks of the set of tasks.

Abstract: Systems and methods are presented herein for generating representative models and assigning members of a task-facilitation service to representatives based on corresponding representative models. The task-facilitation service can transmit a set of queries that when received cause a computing device to generate a set of responses. The task-facilitation service may generate a feature vector that corresponds to the set of responses. The feature vector may be used to generate a representative model that corresponds to a user of the computing device. The representative model may be usable to establish communications one or more members of the task-facilitation service. The task-facilitation service may determine a correspondence between the representative model and one or more user models that correspond to the one or more members. The task-facilitation service may receive a selection of a particular user model and facilitate a communication to a client device associated with the particular user model.

Abstract: Task generation from chat flow data in a task facilitation system is described. One implementation involves receiving in real-time a set of messages between a member and a representative as the set of messages are being exchanged, processing the set of messages to identify one or more task recommendations associated with the set of messages, wherein the one or more task recommendations correspond to a set of tasks performable by the representative on behalf of the member, tracking a chat flow within a chat interface, wherein the set of messages are exchanged within the chat interface, processing the chat flow using a machine learning network to automatically assign at least one of the one or more task recommendations to messages of the set of messages, and generating a message history for the one or more task recommendations by associating the messages with associated tasks of the set of tasks.