To generate the Sierpinski triangle illustrated below, there are at least $3$ approaches:
- The Deterministic IFS Algorithm: Determine the affine transformations $T_1,T_2,T_3$ that characterize the fractal, and given an initial compact $P_0$, iteratively compute $$ P_n= \bigcup_{i=1}^3T_i(P_{n-1}) $$
- The Random IFS Algorithm: Determine the affine transformations $T_1,T_2,T_3$ that characterize the fractal, and given an initial compact $P_0$, iteratively compute $$ P_n= T_i(P_{n-1}), $$ where $i\in \{1,2,3\}$ is randomly chosen at each step.
- The Chaos Game: Given a starting point on the edge of the largest triangle of the fractal, iteratively move half-way between the current point and a corner of the triangle.
It makes sense to me why the first two approaches generate the same set: roughly speaking, the random IFS algorithm applies the same sequence of transformations as the deterministic one, but in a different order. What I don't understand is why the Chaos game produces the same result, without using any information from the transformations $T_1,T_2,T_3$, hence my question:
My question:
Why does the Chaos Game on a triangle generate the Sierpinski triangle? Given that the Random IFS algorithm is a generalization of the Chaos game, how can we relate the two methods ?