# US 2025/0094902 A1 · Systems and methods for processing tasks delegated to a task facilitation service > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2025/0094902 A1 - Document ID: US20250094902A1 - Status: Published application - Kind: A1 - Application number: 18/897,026 - Filed: 2024-09-26 - Published: 2025-03-20 - Earliest claimed: 2021-09-07 - Assignees: Yohana LLC - Applicants: Yohana LLC - Inventors: Yoky Matsuoka; Gwendolyn W. van der Linden; Nitin Viswanathan; Malia Beaulieu; Lingyun Liu; Sean Paterson; Benjamin Deming - Web page: https://patentgrep.com/patent/US20250094902A1 ## CPC - G06Q 10/06316: {Sequencing of tasks or work} - G06F 40/216: using statistical methods - G06F 40/30: Semantic analysis - G06N 3/08: Learning methods - G06N 20/00: Machine learning - G06Q 10/06311: {Scheduling, planning or task assignment for a person or group} - G06Q 10/063114: {Status monitoring or status determination for a person or group} - G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) - G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS ## 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. ## Claims ### Claim 1 (canceled) ### Claim 2 A computer-implemented method comprising: generating task data based on information corresponding to one or more family members associated with a user, wherein the task data identifies a task to be delegated by the user; generating a feature vector corresponding to the task data; applying one or more parameter prediction models to the feature vector to generate task parameters associated with the task; determining a communication policy for the task, wherein the communication policy inhibits transmission of communication data to a computing device associated with the user, and wherein the communication policy is determined based on the task parameters; detecting a communication session with the computing device; inhibiting the transmission of one or more messages associated with the communication session; receiving feedback generated by the user after completion of the task; and updating the one or more parameter prediction models based on the feedback, wherein updating the one or more parameter prediction models increases a likelihood of future tasks to be delegated by the user. ### Claim 3 (depends on 2) The computer-implemented method of claim 2, wherein the information includes composition of the one or more family members associated with the user and one or more events associated with the one or more family members. ### Claim 4 (depends on 2) The computer-implemented method of claim 2, wherein the information includes one or more locations associated with the one or more family members. ### Claim 5 (depends on 2) The computer-implemented method of claim 2, wherein the task parameters identify a task type associated with the task, and wherein the communication policy is determined based on the task type. ### Claim 6 (depends on 2) The computer-implemented method of claim 2, wherein the task parameters identify an amount of resources for completing the task, and wherein the communication policy is determined based on the amount of resources. ### Claim 7 (depends on 2) The computer-implemented method of claim 2, wherein the one or more parameter prediction models includes an artificial neural network. ### Claim 8 (depends on 2) The computer-implemented method of claim 2, further comprising: receiving a revocation indicator of the task; updating the task data based on the revocation indicator, wherein the updated task data indicates that the task is being removed from delegation; and determining another communication policy after updating the task data. ### Claim 9 A system comprising: one or more processors; and a non-transitory computer-readable medium storing instructions that when executed by the one or more processors, cause the one or more processors to perform operations including: generating task data based on information corresponding to one or more family members associated with a user, wherein the task data identifies a task to be delegated by the user; generating a feature vector corresponding to the task data; applying one or more parameter prediction models to the feature vector to generate task parameters associated with the task; determining a communication policy for the task, wherein the communication policy inhibits transmission of communication data to a computing device associated with the user, and wherein the communication policy is determined based on the task parameters; detecting a communication session with the computing device; inhibiting the transmission of one or more messages associated with the communication session; receiving feedback generated by the user after completion of the task; and updating the one or more parameter prediction models based on the feedback, wherein updating the one or more parameter prediction models increases a likelihood of future tasks to be delegated by the user. ### Claim 10 (depends on 9) The system of claim 9, wherein the information includes composition of the one or more family members associated with the user and one or more events associated with the one or more family members. ### Claim 11 (depends on 9) The system of claim 9, wherein the information includes one or more locations associated with the one or more family members. ### Claim 12 (depends on 9) The system of claim 9, wherein the task parameters identify a task type associated with the task, and wherein the communication policy is determined based on the task type. ### Claim 13 (depends on 9) The system of claim 9, wherein the task parameters identify an amount of resources for completing the task, and wherein the communication policy is determined based on the amount of resources. ### Claim 14 (depends on 9) The system of claim 9, wherein the one or more parameter prediction models includes an artificial neural network. ### Claim 15 (depends on 9) The system of claim 9, wherein the instructions further cause the one or more processors to perform operations comprising: receiving a revocation indicator of the task; updating the task data based on the revocation indicator, wherein the updated task data indicates that the task is being removed from delegation; and determining another communication policy after updating the task data. ### Claim 16 A non-transitory computer-readable medium storing instructions that when executed by one or more processors, cause the one or more processors to perform operations including: generating task data based on information corresponding to one or more family members associated with a user, wherein the task data identifies a task to be delegated by the user; generating a feature vector corresponding to the task data; applying one or more parameter prediction models to the feature vector to generate task parameters associated with the task; determining a communication policy for the task, wherein the communication policy inhibits transmission of communication data to a computing device associated with the user, and wherein the communication policy is determined based on the task parameters; detecting a communication session with the computing device; inhibiting the transmission of one or more messages associated with the communication session; receiving feedback generated by the user after completion of the task; and updating the one or more parameter prediction models based on the feedback, wherein updating the one or more parameter prediction models increases a likelihood of future tasks to be delegated by the user. ### Claim 17 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the information includes composition of the one or more family members associated with the user and one or more events associated with the one or more family members. ### Claim 18 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the information includes one or more locations associated with the one or more family members. ### Claim 19 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the task parameters identify a task type associated with the task, and wherein the communication policy is determined based on the task type. ### Claim 20 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the task parameters identify an amount of resources for completing the task, and wherein the communication policy is determined based on the amount of resources. ### Claim 21 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the one or more parameter prediction models includes an artificial neural network. ### Claim 22 (depends on 16) The non-transitory computer-readable medium of claim 16, wherein the instructions further cause the one or more processors to perform operations comprising: receiving a revocation indicator of the task; updating the task data based on the revocation indicator, wherein the updated task data indicates that the task is being removed from delegation; and determining another communication policy after updating the task data.