Extremal graph theory has several roots:applications in geometry, logic (Ramsey theory) and number theory, …
The first result in extremal graph theory is Mantel's theorem, which is Turán's theorem for K3, see below. Next Erdős and Szekeres (re)invented Ramsey's theorem (and later they realized that it was proved a little earlier by Ramsey). Turán wanted to replace the condition of Ramsey's theorem by conditions on the edge-number: Let Tn,p be the p-class Turán graph: n vertices are partitioned into p classes as uniformly as possible and two vertices are joined iff they belong to different classes.
Theorem 1 (Turán, 1940). Among all the graphs Gn not containing Kp+1 there is only one having maximum number of edges, namely, the Turán graph Tn,p.
Erdős should have "invented extremal graph theory in 1938," but he missed it. It was important, that Turán, proving his theorem also asked several related questions.
This leads, among others, to the Erdős-Gallai theorem: Given a family L of (forbidden) graphs, denote by ex(n,L) the maximum number of edges a graph Gn on n vertices can have without containing subgraphs from L.
Theorem 2 (Erdős-Gallai). If Pk is a path of k vertices, ex(n,Pk)=n(k-2)/2+O(1).
Later Turán conjectured that √n is the Ramsey number: all the graphs on n vertices contain either a complete graph of ⌊√n⌋ vertices or an empty graph of this many vertices. Erdős pointed out that the right order of magnitude is not √n but c log n. This is how the random graph method emerged.
Questions from topology led to the Erdős-Stone theorem (1946) and to its important very special case, with much better estimates:
Theorem 3 (Kővári-T. Sós-Turán).
ex(n,K(a,b))≤ca,bn2-(1/a).
Some lower bounds were obtained
The famous Erdős-Turán problem on arithmetic progressions in dense sequences of integers led to a complicated version of the Szemerédi regularity lemma. Later (1976) some investigations on the quantitative Erdős-Stone theorem resulted in the modern form of the regularity lemma, one of the most powerful methods in asymptotic graph theory. This had many applications, among others, for quasi-random graphs.
The regularity lemma asserts that all graphs can be approximated - in some sense - by a generalized random graph:
Definition 4 (Generalized random graph). Given an r×r matrix A=(pij) where pij are probabilities, for x1,…,xr we define the corresponding generalized random graph by fixing r groups of vertices, C1,…,Cr and joining each vertex of Ci to each (other) vertex of Cj with probability pij, independently.
Definition 5 (Regularity condition). Given a graph Gn and two disjoint vertex sets X⊆V, Y⊆V, we shall call the pair (X,Y) ε-regular, if for every X*⊂X and Y*⊂Y satisfying |X*|>ε|X| and |Y*|>ε|Y|,
|d(X*,Y*)-d(X,Y)|<ε.
Theorem 6 (Regularity Lemma 1976). For every ε>0 and ν0 there exists a ν(ε,ν0) such that for every Gn, V(Gn) can be partitioned into ν sets U0, U1,…,Uν, for some ν0<ν<ν(ε,ν0), so that |Ui|=m or Ui=m+1≈n/ν for every i>0, and for all but at most ε(ν2) pairs (i,j) (Ui,Uj) is ε-regular. (U0 is discarded.)
In the last lectures we shall sketch proofs of some recent results, among others, the sharp version of Luczak's theorem on the Bondy-Erdős conjecture:
Theorem 7 (Kohayakawa-Simonovits-Skokan). If Cn is an odd cycle of n vertices and R(Cn,Cn,Cn) denotes the three-color Ramsey function, then for n>n0 R(Cn,Cn,Cn)=4n-3.
We shall also sketch the proofs of several further results and recent progress on the Erdős-Sós conjecture on trees.