Iterations

[rafaqz]

Some models with macro scale feedbacks need to iterate over each timestep multiple times to hone in on macro variables like market demand. This could be done with an Iterate{G}(f, rule/s) wrapper where f is a function of the grid/s G and the current rule object, returning an updated rule and true/false. When it returns true, the iteration is used as the simulation frame for that timestep, otherwise it is repeated after, another function that returns the rule with updated parameters.

See https://link.springer.com/content/pdf/10.1007/s00267-002-2630-x.pdf for an example of this approach.