TITLE: Galois theory for polynomials in several variables
QUESTION [27 upvotes]: I feel a bit ashamed to ask the following question here. 

What is (actually, is there) Galois
  theory for polynomials in
  $n$-variables for $n\geq2$?

I am preparing a large audience talk on Lie theory, and decided to start talking about symmetries and take Galois theory as a "baby" example. I know that Lie groups are somehow to differential equations what discrete groups are to algebraic equations. But I nevertheless would expect Lie (or algebraic) groups to appear naturally as higher dimensional analogs of Galois groups. 
Namely, the Galois group $G_P$ of a polynomial $P(x)$ in one variable can be defined as the symmetry group of the equation $P(x)=0$ (very shortly, the subgroup of permutations of the solutions/roots that preserves any algebraic equation satisfied by them). 
Then one of the great results of Galois theory is that $P(x)=0$ is solvable by radicals if and only if the group $G_P$ is solvable (meaning that its derived series reaches $\{1\}$). 
I was wondering what is the analog of the story in higher dimension (i.e. for equations of the form $P(x_1,\dots,x_n)=0$. I would naively expect algebraic group to show up... 

I googled the main key words and found this presentation: on the last slide it is written that 

the task at hand is to develop a
  Galois theory of polynomials in two
  variables

This convinced me to anyway ask the question

EDIT: the first "idea" I had
I first thought about the following strategy. Consider $P(x,y)=0$ as an polynomial equation in one variable $x$ with coefficients in the field $k(y)$ of rational functions in $y$, and consider its Galois group. But then we could do the opposite...what would happen?

REPLY [9 votes]: (This should really be a comment I think, but I'm not highly rated enough to leave one, so please bear with me)
A Galois Theoretic condition for a polynomial in two variables to be solvable by radicals is found in the following paper: http://arxiv.org/abs/math/0305226. It seems to indicate that something similar can be done for higher variables. Perhaps I'll ask Jochen next time I see him about this.