Estimate Treemower score with Gaussian Process Regression

[yoos]

Currently, the score is simply a sum of the scores of all traversed cells. We should instead implement a Ordinary Kriging evaluator in DecisionTree::CalcScore().

[drews256]

We could process the data in Matlab. As long as the data output is something that I can use or I can make it into something that I can use then I should be able to do that. I'll play around with it tonight.

[yoos]

Sounds good. We currently export the generated path to a logfile in the output directory. Between the original costmap and the score depreciator in DecisionTree::DepreciateScore(), I think you'll have the information you need.

[drews256]

Also there is a difference between "simple" kriging and ordinary kriging. I don't know if you meant "simple" kriging as in a simple evaluator that uses kriging or a "simple kriging" in the sense that we're using the simple kriging technique. I think ordinary kriging is more applicable.

[yoos]

Oh, I saw a mention of Simple Kringing in your paper, thus my assumption. Ordinary kringing it is.

[drews256]

It sounds like you're on board with this anyways so I will be working towards that goal.

[drews256]

"Even so, they are useful in different frameworks: Kriging is made for estimation of a single realization of a random field, while regression models are based on multiple observations of a multivariate data set." -Per Wikipedia. Maybe we should just call it Gaussian Process Regression

[yoos]

We're going to be mathing on multiple multivariable mathing maths.

[drews256]

Yes, m'ing on quadruple m's is really the way to do it.

[yoos]

Mmm-mm. Can't wait.