Distributed AI Activity Control With Task Reachability Analysis
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Solution Overview
Problem
Existing systems lack dynamic, distributed control and communication technologies for efficiently managing interrelated activities with varying system attributes, leading to inefficiencies in task execution.
Innovation Solution
A dynamic directed activity network system that includes a directed activity control program, task execution agents, controllers, and communication networks, utilizing optimization tools like graph theory and artificial intelligence to dynamically update and optimize task execution based on agent attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed control and communication technologies are implemented, then efficiency and flexibility of task execution is enhanced, but device complexity increases
Solution Approach 1:
The system divides the activity control function into multiple distributed activity controllers that operate independently across different locations. Each controller manages specific tasks locally while communicating with others through standardized interfaces, enabling parallel processing and reducing central bottlenecks without requiring a completely complex centralized architecture
Solution Approach 2:
The patent implements universal communication protocols and standardized data formats that allow different types of devices and controllers to interoperate through common interfaces. This multi-functionality enables the system to handle diverse tasks across distributed locations using the same communication framework, reducing the need for specialized complex connections for each device type
2Reliability
If dynamic strategy adjustment is implemented to accommodate unforeseen events, then reliability of task completion is improved, but loss of time in decision-making increases
Solution Approach 1:
The system pre-establishes communication channels and data exchange protocols between distributed controllers before tasks begin. Standardized interfaces and predetermined coordination rules are configured in advance, allowing controllers to quickly adapt to unforeseen events using pre-prepared communication pathways without time-consuming setup during critical decision moments
Solution Approach 2:
The patent implements continuous feedback mechanisms where distributed controllers exchange status information and task progress data in real-time through standardized protocols. This feedback loop enables automatic detection of unforeseen events and triggers pre-programmed response strategies, reducing the need for lengthy manual decision-making processes while maintaining high reliability
Data Source
AI summary
A dynamic, distributed directed activity network comprising a directed activity control program specifying tasks to be executed including required individual task inputs and outputs, the required order of task execution, permitted parallelism in task execution, task adjacency to subsequent tasks, and reachability from each task to other tasks; a plurality of task execution agents, individual of said agents having a set of dynamically changing agent attributes and capable of executing different required tasks; a plurality of task execution controllers, each controller associated with one or more of the task execution agents with access to dynamically changing agent attributes; a directed activity controller for communicating with said task execution controllers for directing execution of said activity control program; and, a communications network supporting communication between said directed activity controller and task execution controllers for directing execution of said directed activity control program using selected task execution agents.