IA ideas library

Graph theory and network IA ideas (AI HL and beyond)

Graph theory turns routes, timetables and connections into mathematics. AI HL includes adjacency matrices, minimum spanning trees, the Chinese postman problem and travelling-salesman bounds; Markov chains and transition matrices sit next to them.

These ideas use networks you can draw yourself — your school, your bus routes, your delivery round — so the IA is personal by construction.

Next step: shortlist ideas with the free IA topic explorer, which filters starting points by course, interest and how easy the data is to get. For feedback on your own draft, the IA package (€39 once) gives you 5 AI feedback credits and every annotated exemplar in full.

How networks & graphs explorations reach the top bands

Personal engagement (C)

Map a network you actually use (your school, your town's transport, your friends) and collect the distances or connections yourself.

Reflection (D)

Reflect on what the graph leaves out (one-way systems, time of day, capacity) and whether the algorithm's answer would work in practice.

Use of mathematics (E)

SL: Graph theory is in AI HL. At SL, keep to distance tables and simple optimisation, or explain any algorithm you use carefully as new mathematics.

HL: Correct use of HL algorithms (Kruskal/Prim, Chinese postman, nearest neighbour and deleted-vertex bounds, adjacency matrices, Markov steady states), with each step explained and the result interpreted.

An HL version

Compare two algorithms or bounds, work with the adjacency or transition matrix directly, or prove why an algorithm gives an optimal (or bounded) answer.

Networks, graphs & algorithms ideas (9)

Also relevant (12)

Frequently asked questions

Is graph theory only for AI HL students?

It is only examined in AI HL, but anyone can use it if they explain it clearly. A small, carefully explained network is better than a huge one you cannot justify.

What software helps with graph theory?

A spreadsheet for matrices, GeoGebra for drawing, or a few lines of Python. Show one iteration of an algorithm by hand, then use technology for the rest.

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Related types of IA: Matrices, transformations & Markov chains

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