Constructive Function Approximation
The problem of automatically constructing features for use in a learned evaluation function is visited. Issues of feature overlap, independence, and coverage are addressed. Three algorithms are applied to two tasks, measuring the error in the approximated function as learning proceeds. The issues are discussed in the context of their apparent effects on the function approximation process.