I am currently trying to apply some results from Choquet theory - i.e., the generalisation of results by Minkowski and Krein-Milman for representing points in a compact, convex set C by probability measures over its extreme points, ext C = { x ∈ C : C - { x } is convex }.

My main problem is with explicitly describing the set of extreme points for a particular convex set, namely the set C of concave functions over the k-simplex that vanish at the vertices of the simplex and have sup-norm at most 1. I've convinced myself that this set of functions in compact and convex and so the Choquet's theorem applies. However, apart from the case of the 1-simplex I am struggling to say anything about what the extreme functions might be.

In the case of the 1-simplex, the functions in ext C are "tents" with height 1, that is, functions f that are zero on the boundaries and rise linearly to a single point x where f(x)=1. I suspect that in the case of the 2-simplex the extreme functions are also piece-wise linear concave functions with height 1. I have considered a number of candidates (the functions formed by the taking the minimum of 3 affine functions, each zero on a different vertex) but am having trouble showing that the candidates are actually extreme.

Does anyone know of any techniques for identifying extreme points of convex sets? 

Pointers to applications of Choquet's theorem that explicitly construct ext C and the probability measure for a given point in C would also be much appreciated. My reading in this area has only got me as far as Phelps' monograph "Lectures on Choquet Theory" and a survey article by Nina Roy titled "Extreme Points of Convex Sets in Infinite Dimensional Spaces".