Unverified50% confidenceFactExact time
In the LLM context, each agent in a multi-agent system is typically a model instance with a specific role, tool access permissions, and reasoning capabilities, and they can exchange information through shared context, message passing, or a blackboard architecture.
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50%
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Long-term
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10/21/2026
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Related Claims
UnverifiedIn LLM-based multi-agent systems, there are three main methods of inter-Agent communication: shared memory, message passing, and blackboard systems.76% similarUnverifiedAccess control should be based on the combined permissions of multiple identities, and policies must simultaneously account for all identities involved in the agent workflow (delegated and chained identities).68% similarUnverifiedCommon multi-agent system topologies include star topology (one orchestrator assigns tasks to multiple executors), chain topology (agents pass tasks sequentially), and mesh topology (agents can communicate freely with one another), with mesh topology's communication complexity growing at O(n²).68% similarUnverifiedA sub-agent is an independent execution unit spawned by the main agent, with its own conversation history and context window, and does not share the cache already established by the main session.67% similarUnverifiedThe risk model for an agent that can run continuously, invoke tools, and access external systems is completely different from that of a model that only answers questions.65% similar
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