AI Research
Uncertainty-Aware Resource Orchestration for Agentic AI Systems
How autonomous LLM workflows use tools, memory and resources as they work toward a task
Agentic artificial intelligence (AI) systems powered by large language models (LLMs) execute as autonomous multi-step pipelines that dynamically invoke tools, integrate observations into memory, and iterate until a task is resolved or a resource budget is exhausted.
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ArXiv CS.AI
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ArXiv CS.AI
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Agentic AI systems make decisions across multiple steps while using tools and memory, so resource use can change as a task unfolds. Orchestration that accounts for uncertainty could help manage execution within resource limits.
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