Agentic AI architectures excel at maintaining a dynamic internal state and exploiting contextual information, allowing autonomous systems to interpret complex environments more effectively. By integrating multiple modules that specialize in perception, reasoning, and memory, such architectures enable agents to make decisions that better align with their objectives and environmental nuances.
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