Agent Zero utilizes a multi-intelligence body architecture with a tree hierarchy to support automatic task decomposition and distributed execution. When the main intelligent body receives a complex command, it creates a network of sub-intelligent bodies based on the following logic:
- Task decomposition: break down the goal into atomic-level subtasks (e.g., "data analysis report" into data collection, cleansing, visualization, etc.)
- Contextual inheritance: sub-intelligents automatically acquire environment variables and intermediate results from parent tasks
- Parallel execution: supports up to 5 intelligences running at the same time, coordinating resources through the semaphore mechanism
The technical implementation maintains independence for each instance of the intelligences:
- Memory space is isolated but data can be shared explicitly
- Dedicated log channel to mark task sources
- Resource quota management system
Typical examples include the simultaneous execution of port scanning and service identification in network security assessments or the parallel processing of multiple data sources for data analysis. the Web interface provides a complete visual monitoring of the task tree.
This answer comes from the articleAgent Zero: An Open Source AI Intelligent Body Framework for Flexible Creation and Execution of TasksThe
