Question

When comparing expert systems to machine learning, what is the major difference, and when is one preferred over the other? Explain your answer in 3-5 sentences.(4 points)

Answer 1

The major difference between expert systems and machine learning lies in their approach to knowledge acquisition and problem solving. Expert systems rely on predefined rules and knowledge encoded by human experts, making them suitable for well-defined problems with clear logic and reasoning, such as medical diagnosis or legal advice. In contrast, machine learning utilizes algorithms to learn from data, making it better suited for tasks with complex patterns and large datasets, such as image recognition or natural language processing. One is preferred over the other based on the problem at hand; expert systems excel in domains where rules are established and transparent, while machine learning is favored when dealing with vast amounts of unstructured data where patterns are not easily articulable.