There is an intricate relationship between search and knowledge in the evaluation function. Deeper search favors less near-term tactical factors and more subtle long-horizon positional motifs in the evaluation. There is also a trade-off between efficacy of encoded knowledge and computational complexity: computing detailed knowledge may take so much time that performance decreases, so approximations to exact knowledge are often better. Because the evaluation function depends on the nominal depth of search as well as the extensions and reductions employed in the search, there is no generic or stand-alone formulation for an evaluation function. An evaluation function which works well in one application will usually need to be substantially re-tuned or re-trained to work effectively in another application.
There is an intricate relationship between search and knowledge in the evaluation function. Deeper search favors less near-term tactical factors and more subtle long-horizon positional motifs in the evaluation. There is also a trade-off between efficacy of encoded knowledge and computational complexity: computing detailed knowledge may take so much time that performance decreases, so approximations to exact knowledge are often better Because the evaluation function depends on the nominal. depth of search as well as the extensions and reductions employed in the search, there is no generic or stand-alone formulation for an evaluation function. An evaluation function which works well in one application will usually need to be substantially re-tuned or re-trained to work effectively in another application.