Artificial intelligence is built through rational agents that perceive their environment and act to achieve goals.
Imagine a robot playing chess. It sees the board (perceives), thinks about which move to make (processes), and moves the piece (acts). This is the idea of a rational agent: a program that makes good decisions to win, just like a human player.
A rational agent does not have to be perfect. It makes the best choice based on what it knows. For example, a robot vacuum does not know where the dirt is in the house. It uses sensors to detect dust and decide which direction to go. Sometimes it misses a corner, but that is okay. Its goal is to clean as efficiently as possible, not to be perfect. That is practical rationality. The next step is to understand how the agent learns from mistakes.
Why it matters This book is the modern foundation of artificial intelligence, used in universities to learn how robots and virtual assistants work.