Final answer:
Rule-based expert systems cannot learn from experience as they follow predefined rules without learning from new data, unlike intelligent agents, neural networks, and case-based reasoning systems which are capable of learning.
Step-by-step explanation:
Among the artificial intelligence information systems listed, rule-based expert systems are typically not designed to learn from experience. These systems operate by following predefined rules and do not possess the ability to learn from new data without human intervention. In contrast, intelligent agents, neural networks, and case-based reasoning systems can all learn from new data or experiences to some extent. Intelligent agents adapt to new conditions and optimize their actions; neural networks learn and improve their performance through exposure to more data; and case-based reasoning systems learn by adding new cases to their databases.