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ENH: Add action_values to DiscreteDP; add util.index_dict (#940)

* DOC: Correct the state_values docstring in MarkovChain

The attribute does not default to integers 0 through n-1; it is None
when unset, in which case the states are represented by their indices
(as the Attributes entry and the simulate docstring already state).

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* ENH: Refine DiscreteDP state_values; record in DPSolveResult

Refine the state_values support added in #832:

* Correct the docstring: the attribute is None when unset (in which
  case the states are represented by their indices), and the values
  may be 2-dimensional (row per state).
* Record state_values in DPSolveResult.
* Reorganize the tests into a class covering both formulations,
  2-dimensional values, the solution pipeline, and carry-over by
  to_sa_pair_form/to_product_form.

Cf. #248

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

* ENH: Add action_values to DiscreteDP

Add an action_values keyword argument to DiscreteDP, symmetric to
state_values. The values play no role in the solution algorithms.
DPSolveResult records action_values, and gains a sigma_values property
returning the optimal policy decoded to action values, i.e.,
action_values[sigma] (sigma itself if action_values is None).

The semantics follow the "universal action set" approach (approach 2
of QuantEcon/QuantEcon.jl#94 (comment); cf.
QuantEcon/QuantEcon.jl#402): action_values labels a common action set
A with A(s) a subset of A for each state s. In the state-action pairs
formulation, its length defines the number of actions and may exceed
a_indices.max() + 1, so a universal action set strictly containing the
union of the feasible sets is representable in both formulations.
to_sa_pair_form/to_product_form carry action_values unchanged, with
to_product_form restoring the full number of columns, so actions
feasible at no state survive the round trip.

Cf. #248

Co-Authored-By: Claude ... (continued)

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