Study Notes
Artificial Intelligence involves creating computer systems that can perform tasks requiring human-like intelligence. Examples include speech recognition, translation, facial recognition, and decision making.
- Artificial Intelligence — development of computer systems to perform tasks requiring human intelligence. Example: Speech recognition systems that understand and process human language.
- Expert System — a computer-based decision-making system using facts and heuristics to solve complex problems. Example: Medical diagnosis systems that suggest treatments based on symptoms.
- Machine Learning — training computers with data to make predictions without explicit programming. Example: Recommendation engines that suggest products based on user behavior.
- User Interface — part of an expert system that interacts with users and displays results. Example: A graphical interface where users input queries and receive answers.
- Inference Engine — the component of an expert system that applies rules to solve problems. Example: The logic processor in a diagnostic tool that evaluates symptoms.
- Knowledge Base — a repository of facts used by an expert system to solve problems. Example: A database of medical knowledge used by a diagnostic expert system.
Exam Tips
Key Definitions to Remember
- Artificial Intelligence: Development of systems performing tasks requiring human intelligence.
- Expert System: Decision-making system using facts and heuristics.
- Machine Learning: Training computers with data to make predictions.
Common Confusions
- AI vs ML: AI is broader, encompassing all intelligent systems; ML is a subset focused on learning from data.
- User Interface vs Inference Engine: UI interacts with users, while the inference engine processes data.
Typical Exam Questions
- What is an expert system? A computer-based decision-making system using facts and heuristics.
- How does machine learning differ from AI? ML is a subset of AI focused on learning from data to make predictions.
- What are the components of an expert system? User Interface, Inference Engine, and Knowledge Base.
What Examiners Usually Test
- Understanding of AI and its applications.
- Differences between AI, ML, and expert systems.
- Components and functions of expert systems.