a.4.7.4.3 logic programming
State the facts and let the machine deduce the rest. Explore logic programming, where formal rules and inference engines drive classic Artificial Intelligence.
Imagine being a detective. Instead of explaining exactly how to solve a crime step-by-step, you simply lay out all the clues (facts) and the laws of physics (rules), and let the detective's brain figure out the rest. That is Logic Programming. In languages like Prolog, you declare what is true about a specific problem domain. An underlying 'inference engine' then does the heavy lifting - using complex algorithms like backtracking to automatically deduce answers to your questions. It is a foundational pillar of Artificial Intelligence, perfect for building expert systems and solving complex constraint puzzles like school timetabling or Sudoku.
🧐 Sorry, I looked and there is nothing to see.
This section outlines the progressive curriculum mapping for Logic Programming, tracing the pedagogical journey from foundational deductive reasoning in early years to advanced constraint-satisfaction modeling in Artificial Intelligence at the extension level. It explicitly shifts the focus from writing sequential commands to defining absolute truths and relationships. By mandating the use of formal inference engines and backtracking analysis, this strand ensures students understand the "what not how" principle, preparing them to architect complex expert systems where the computer infers new knowledge from established facts.
Last modified: March 20th, 2026
