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A desideratum for future versions of HARK is a syntax for mathematical expressions in model definitions.
This syntax need not be the native Python syntax, though this is what is done in @llorracc 's "pre-alpha 2.0" code, which uses strings of Python and the very controversial eval function to parse them.
Dolo has its own Dolang syntax and interpreter, which is an attractive choice. I wonder if it can be extracted from the YAML context in which it is used.
In conversation with @alanlujan91 and @nicksawhney , Disciplined Convex Programming (DCP) has come up. This is a DSL for convex optimization problems developed by researchers at Stanford. It is implemented in several convex optimization packages, in different languages.
DCP has the advantage of being featureful with respect to convex optimization -- if it can be expressed in the language, then it guarantees that it can be solved by their optimization engine (in this case CVXPY).
The text was updated successfully, but these errors were encountered:
Yes, it's a reply. And an attempt to elaborate a bit on the discussion
about "magic" solvers.
In particular, to make the point that any general-purpose solution method's
first requirement is a general-purpose technology for describing the
problem with complete clarity. Even a "magic" solver could not solve
correctly a problem that was not defined completely.
The current approach to this issue that's favored is to use Sympy to parse strings into symbolic expressions, and then convert these into other forms as needed.
A desideratum for future versions of HARK is a syntax for mathematical expressions in model definitions.
This syntax need not be the native Python syntax, though this is what is done in @llorracc 's "pre-alpha 2.0" code, which uses strings of Python and the very controversial
eval
function to parse them.#1055
Dolo has its own Dolang syntax and interpreter, which is an attractive choice. I wonder if it can be extracted from the YAML context in which it is used.
In conversation with @alanlujan91 and @nicksawhney , Disciplined Convex Programming (DCP) has come up. This is a DSL for convex optimization problems developed by researchers at Stanford. It is implemented in several convex optimization packages, in different languages.
https://www.cvxpy.org/tutorial/dcp/index.html
DCP has the advantage of being featureful with respect to convex optimization -- if it can be expressed in the language, then it guarantees that it can be solved by their optimization engine (in this case CVXPY).
The text was updated successfully, but these errors were encountered: