Solution

Expert systems are designed to mimic the decision-making ability of a human expert by using a set of rules (often called knowledge bases) to analyze information. These rules are based on domain-specific knowledge, enabling the system to provide advice, solve problems, or make decisions in specialized fields such as medical diagnosis or financial planning. Random decision-making : Expert systems do not make decisions randomly; they are rule-based. Ability to learn from mistakes : This is more characteristic of machine learning, not expert systems. Real-time feedback processing : While some systems may have real-time capabilities, this is not the defining feature of expert systems. Natural language understanding : This is more related to natural language processing (NLP) and is not the main characteristic of expert systems.