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Why is pruning harder in an expectimax tree?

  • A.Chance nodes have far more successors than choice nodes
  • B.The utilities at the leaves are no longer bounded
  • C.The opponent's moves cannot be predicted in advance
  • D.A chance node's value depends on all its children

Answer: D

An average cannot be bounded from one child alone unless the range of leaf values is known, so the alpha beta argument does not apply directly. Bounding the utilities does permit a limited form of pruning. Successor counts, unbounded utilities and unpredictability are not the obstacle. An algorithmic technique that depends on a maximum or minimum being determined by a single child fails as soon as the backup rule becomes an average, which is a clean example of a technique's assumptions mattering.

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