SPOT Configuration

A configuration (CONF) file, which stores information about SPOT specific settings, has to be set up. For example, the number of (1+1)-ES algorithm runs, i.e., the available budget, can be specified via auto.loop.nevals. SPOT implements a sequential approach, i.e., the available budget is not used in one step. Evaluations of the algorithm on a subset of this budget, the so-called initial design, is used to generate a coarse grained meta model $F$. This meta model is used to determine promising algorithm design points which will be evaluated next. Results from these additional (1+1)-ES runs are used to refine the meta model $F$. The size of the initial design can be specified via init.design.size. To generate the meta model, we use random forest (Breiman, 2001). This can be specified via seq.predictionModel.func = "spotPredictRandomForest".

Random forest was chosen, because it is a robust method which can handle categorical and numerical variables.