This document contains a list of development issues and plans for the hypereconomy project.

Maintainer:  Sasha Chislenko <sasha@media.mit.edu>
Last updated:  06/02/98

 Eventually, these tasks should have names and dates against them.

Urgent tasks: Finish and run simple versions of static and variable models:

     - run and plot non-variable model with realistic (click rate around 5%) data

     - implement and test variable response model - put adaptive response biases
        everywhere in addition to static ones; test deaths and births; collect
            category data incrementally (needed for adaptive computation); change
        the mixing formulas to assure adaptation
     - death and birth of sites doesn't seem to work well.
     - debug variable model, run, plot, publish

Immediate tasks (clean up code)

     - need to separate response model from optimization code
     - look up occurrences of ?, "should", "eventually", "ugly" in all code,
       and handle the issues
     - check parameters read from file (rename into HyperE.param ?)
     - rename parameters into param.NUMXXX, etc.  (?)
     - use new calls instead of deprecated
     - separate code better into classes and routines
     - all statistics variables should go into classes
     - global constants should be accessible in all classes
     - be ready to divide the work among multiple developers


Development Plans for near future:

     - at the end of run, compute and print total values (prices) of remaining inventory
     - add perfect knowledge option
     - categories should look more like generic advisory agents / resource owners
       we can have in each category, the list of agents it covers, and in each agent,
       a list of categories.  After that we can have a graph-like agent hierarchy

Continuing issues:

     - test all elements carefully
     - speed up execution
     - more documentation, comments
     - report errors everywhere they may be detected
     - occasionally, there is an out of bounds error, should fix

More grand-scale plans:

     - need away of generating a statistical access/response model from real-world data