The rule of a simple reflex agent is based on condition-action pairs, often expressed as "If condition, then action." This means the agent perceives the current state of the environment through its sensors and immediately performs an action according to predefined rules without considering any history or past percepts. The agent's decision-making relies solely on the current percept and a set of fixed condition-action rules. Key points about the simple reflex agent rule:

• The agent uses if-then rules to map environmental conditions directly to actions.
• It acts only on the current percept , ignoring any past perceptual history.
• The agent's behavior is reactive and immediate , similar to a reflex in humans.
• It is designed for fully observable environments where the current percept contains all necessary information for decision-making.
• It cannot learn or adapt because it does not store or use past information.

For example, a simple reflex agent controlling a thermostat might follow this rule:
If the temperature is above a threshold, then turn on the air conditioning; otherwise, turn it off. This approach makes simple reflex agents efficient and easy to implement but limits them to environments where the rules are sufficient and the environment is predictable. They struggle in dynamic or partially observable environments that require memory or learning