AI Agent Architecture The diagram below illustrates the core architecture of AI agents. Step 1: Perception The agent processes inputs from its environment through multiple channels. It handles language through NLP, visual data through computer vision, and contextual information to build situational awareness. Modern systems incorporate audio processing, sensor data, and state tracking to maintain a complete picture of their surroundings. Step 2: Reasoning At its core, the agent uses logical inference systems paired with knowledge bases to understand and interpret information. This combines symbolic reasoning, neural processing, and Bayesian approaches to handle uncertainty. The reasoning engine applies deductive and inductive processes to form conclusions and even supports creative thinking for novel solutions. Step 3: Planning Strategic decision-making happens through goal setting, strategy formulation, and path optimization. The agent breaks complex objectives into manageable...