Optimizing parameter learning using temporal differences

Temporal difference algorithms are useful when attempting to predict outcome based on some pattern, such as a vector of evaluation parameters applied to the leaf nodes of a state space search. As time progresses, the vector begins to converge towards an optimal state, in which program performance pe... View More