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Foundational techniques for autonomous agent design originate from classic AI approaches, including Probabilistic Graphical Models, Reinforcement Learning, and Multi-Agent Systems, which manage uncertainty, learn optimal behaviors in dynamic environments, and enable agents to interact and share information efficiently.

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