Logic Programming (326.121, 326.122)

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Logic programming sits at the intersection of mathematics, computer science, and artificial intelligence. It shows how abstract mathematical logic can drive real computation, turning formulas into executable programs. Logic programming encourages declarative thinking, emphasizing what a solution should be rather than how to compute it: a perspective that can influence many different areas, ranging from database design to AI reasoning systems. In modern AI, logic programming plays a key role in areas such as knowledge representation and reasoning, planning and problem solving, and neuro-symbolic integration, bridging the gap between symbolic logic and data-driven approaches. It is a tool that lets AI systems combine raw data with logical thinking, opening the door to explainable and trustworthy intelligence.

This course introduces the logical foundations and computational model of logic programming and provides training in practical programming skills, showing how declarative problem solving emerges from simple formal principles. Students will learn how logic programs are executed, how they can express complex computations, and how these ideas extend to modern paradigms that are based on constraint or probabilistic models.

Grading is based on programming assignments and in-class quizzes. No prior experience in logic programming or Prolog is required.

Winter Semester 2025.

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