Fine-Grained Decision-Theoretic Search Control
  Decision-theoretic control of search has previously used as its basic unit.
of computation the generation and evaluation of a complete set of successors.
Although this simplifies analysis, it results in some lost opportunities for
pruning and satisficing. This paper therefore extends the analysis of the value
of computation to cover individual successor evaluations. The analytic
techniques used may prove useful for control of reasoning in more general
settings. A formula is developed for the expected value of a node, k of whose n
successors have been evaluated. This formula is used to estimate the value of
expanding further successors, using a general formula for the value of a
computation in game-playing developed in earlier work. We exhibit an improved
version of the MGSS* algorithm, giving empirical results for the game of
Othello.
