Asa H has a number of parameters which are not easy to set. Th2 is a threshold value which is used to determine if two patterns are so similar that they can be considered to be the same pattern. L is a learning rate which determines how big a step is taken during extrapolation. Th3 is a threshold that determines if a vector component is small enough to neglect.......
There are a half dozen to a dozen such parameters in Asa H and it is difficult to decide on their values.
One way to tune these parameters is the following:
The set of parameters can be treated as a vector and Asa H can be run for a period of time in a typical environment while we record the Utility gains during the run. A second set of parameters can be employed in Asa H while it is run in the same (or very similar) environment and the Utility gain is again recorded.
Using these two vectors and utilities (or a larger set) we can then extrapolate using the Asa H extrapolation algorithm in order to improve the vector (i.e. adjust the threshold/parameter values) in an effort to improve the utility gains. This procedure can be repeated to gradually tune the parameters.