Quote from MGJ:
Actually, people do. In the field of nonlinear optimization, the "Least Pth approximation" applies exactly this idea (raising deviations to the power P, summing, and taking the Pth root).
Note that in the limit as P approaches infinity, this calculation merely returns the largest of the individual deviations.
In other words, it is a continuous approximation of the (discontinuous) "MAX" function. Since the fastest optimization algorithms require the objective function to be continuous (with continuous 1st and 2nd derivatives too), the Least Pth Approximation is incredibly valuable; it lets you use the best optimizers on minimax problems. Do a google search for Least Pth Algorithm and/or Least Pth Approximation. It's good stuff.
Beautiful idea

I have some experience with nonlinear optimization, so it's easy for me to understand what you're talking about. Maybe I saw this least Pth idea many years ago, my memory fails me.
I'd like to hear more about "equiripple polynomials" but I fear we strayed too far off topic
