  A discounted-sum automaton (NDA) is a nondeterministic finite automaton with
edge weights, valuing a run by the discounted sum of visited edge weights. More
precisely, the weight in the i-th position of the run is divided by
$\lambda^i$, where the discount factor $\lambda$ is a fixed rational number
greater than 1. The value of a word is the minimal value of the automaton runs
on it. Discounted summation is a common and useful measuring scheme, especially
for infinite sequences, reflecting the assumption that earlier weights are more
important than later weights. Unfortunately, determinization of NDAs, which is
often essential in formal verification, is, in general, not possible. We
provide positive news, showing that every NDA with an integral discount factor
is determinizable. We complete the picture by proving that the integers
characterize exactly the discount factors that guarantee determinizability: for
every nonintegral rational discount factor $\lambda$, there is a
nondeterminizable $\lambda$-NDA. We also prove that the class of NDAs with
integral discount factors enjoys closure under the algebraic operations min,
max, addition, and subtraction, which is not the case for general NDAs nor for
deterministic NDAs. For general NDAs, we look into approximate determinization,
which is always possible as the influence of a word's suffix decays. We show
that the naive approach, of unfolding the automaton computations up to a
sufficient level, is doubly exponential in the discount factor. We provide an
alternative construction for approximate determinization, which is singly
exponential in the discount factor, in the precision, and in the number of
states. We also prove matching lower bounds, showing that the exponential
dependency on each of these three parameters cannot be avoided. All our results
hold equally for automata over finite words and for automata over infinite
words.
