Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
MAS Orchestration
MAS-Orchestra Process Flow
MAS-Orchestra formulates multi-agent system orchestration as a function-calling reinforcement learning problem, enabling holistic system design and efficient sub-agent coordination. This framework generates the entire Multi-Agent System (MAS) at once, rather than incrementally, allowing for global reasoning over system structure.
MAS-Orchestra Execution Flow
User Query
→
Holistic Orchestration (RL)
→
Sub-agent Instantiation (Callable Functions)
→
Sub-agent Execution
→
Results Aggregation
→
Final Answer
This holistic approach, trained via reinforcement learning, enables MAS-Orchestra to dynamically adapt to task structures, optimizing sub-agent utilization and achieving superior performance and efficiency.
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