A blackboard-based LLM multi-agent system with controller-selected agents achieves competitive benchmark accuracy at lower token cost than several static and dynamically optimized baselines.
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Exploring Advanced LLM Multi-Agent Systems Based on Blackboard Architecture
A blackboard-based LLM multi-agent system with controller-selected agents achieves competitive benchmark accuracy at lower token cost than several static and dynamically optimized baselines.