Combinatorial diversity metrics for the analysis of policy processes
  We present several completely general diversity metrics to quantify the
problem-solving capacity of any public policy decision making process. This is
performed by modelling the policy process using a declarative process paradigm
in conjunction with constraints modelled by expressions in linear temporal
logic. We introduce a class of traces, called first-passage traces, to
represent the different executions of the declarative processes. Heuristics of
what properties a diversity measure of such processes ought to satisfy are used
to derive two different metrics for these processes in terms of the set of
first-passage traces. These metrics turn out to have formulations in terms of
the entropies of two different random variables on the set of traces of the
processes. In addition, we introduce a measure of `goodness' whereby a trace is
termed {\it good} if it satisfies some prescribed linear temporal logic
expression. This allows for comparisons of policy processes with respect to the
prescribed notion of `goodness'.
