Rule-based AI makes decisions by following the rules that have been programmed into it. When faced with a new situation, the AI will first try to find a rule that applies to that situation. If it finds a rule that applies, it will follow the instructions in the rule to make a decision. If it does not find a rule that applies, the AI will either try to find a more general rule that might apply, or it will generate a new rule that can be used to handle the situation.

#### What are the advantages and disadvantages of Rule-based AI?

Rule-based AI has a number of advantages over other types of AI. First, rule-based AI is relatively easy to understand and explain. This makes it a good choice for tasks where it is important to be able to trace the AI's reasoning process. Second, rule-based AI is often very fast and efficient. This makes it a good choice for tasks where speed is important. Third, rule-based AI can be very accurate in tasks where the rules are well-defined.

However, rule-based AI also has a number of disadvantages. First, rule-based AI can be inflexible. This is because the rules that are programmed into the AI cannot be changed easily. Second, rule-based AI can be brittle. This is because the AI can make mistakes if the rules are not correct or if the situation does not match the rules that have been programmed into the AI. Third, rule-based AI can be difficult to scale to new tasks. This is because the AI needs to be reprogrammed for each new task.