Three Pillars of SMAI

The SMAI course teaches three pillars that together prepare you for symbolic AI:

• Mathematical infrastructure — sets, relations, functions, induction, structures
• Talking about objects — MathTalk, ProofTalk, definitions, lemmas, theorems
• Programming with symbolic representations — SML, datatypes, pattern matching

On top of these sits complexity analysis, which tells us which problems are
tractable and which are not.

The course title — Symbolic Methods for AI — refers to the methods, not just
the goals. The aim is to give you a thinking toolbox you can apply anywhere:
in research, in building tools, in evaluating systems.