Welcome to AI Agents Development! An AI Agent is a software entity that can perceive its environment through sensors and take actions using actuators to achieve specific goals. Think of it like a robot that can see, think, and act in the world around it.
AI Agents can be classified into five main types based on their complexity. Simple reflex agents react only to current inputs. Model-based agents maintain internal state. Goal-based agents plan to achieve objectives. Utility-based agents optimize performance. Learning agents improve through experience. Each type builds upon the previous, adding more sophisticated capabilities.
Agent environments have key properties that affect design decisions. Observable environments let agents see the full state, while partially observable ones hide information. Deterministic environments have predictable outcomes, unlike stochastic ones. Sequential environments require planning, while episodic ones don't. Static environments stay unchanged, but dynamic ones evolve. Discrete environments have finite states, continuous ones are infinite. Understanding these helps choose the right agent architecture.