How to generate a finite set of points so that we can construct
all of the vectors in `V'` is the heart of the matter.
However, the first algorithm we discuss generally ignores trying to
find these points. The idea is to simply generate all the possible
vectors you could construct and was proposed by Monahan in 1982,
though also mentioned by Sondik in 1971. To construct a vector
requires selection an action and a vector in `V` for each
observation. Thus we must generate a large number of vectors. Many
of these are not useful, since they are completely dominated by other
vectors over the entire belief space. We can eliminate the useless
ones at the expense of some computing time, but regardless, just
enumerating the vectors takes a long time even for some small
problems. As a side note, it is possible to construct a problem where
everyone of those vectors enumerated is useful over some portion of
belief space. Thus, in the worst case, the general problem of one
step of value iteration on a `POMDP` is very hard.

The figure below shows what the Monahan algorithm does for each
action. For each observation it selects a vector from `V` and
transforms the vectors and combines them to construct a potential
vector for `V'`.

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