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Agent Architectures

Agent architectures define how an AI system perceives its environment, makes decisions, and performs actions. They range from simple reactive agents that respond directly to stimuli to complex deliberative agents that plan future actions based on internal models of the world. The choice of architecture dictates an agent's capabilities and how it interacts with its surroundings.

In plain terms

An agent architecture is like the blueprint for a robot's brain, outlining how it will think and act in the world.

Why it matters

Understanding agent architectures is crucial for building autonomous systems that can effectively operate in dynamic and unpredictable environments, from self-driving cars to intelligent assistants.

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