  We examine normal form solutions of decision trees under typical choice
functions induced by lower previsions. For large trees, finding such solutions
is hard as very many strategies must be considered. In an earlier paper, we
extended backward induction to arbitrary choice functions, yielding far more
efficient solutions, and we identified simple necessary and sufficient
conditions for this to work. In this paper, we show that backward induction
works for maximality and E-admissibility, but not for interval dominance and
Gamma-maximin. We also show that, in some situations, a computationally cheap
approximation of a choice function can be used, even if the approximation
violates the conditions for backward induction; for instance, interval
dominance with backward induction will yield at least all maximal normal form
solutions.
