[B-brains] tying optimizations to methods

[Hesam Samimi]

I've been experimenting with defining optimizations for goal methods  
and action methods.

For goal methods, we would like optimizations to dynamically tell us  
which actions to explore.
For action methods, we would like optimizations to dynamically tell  
us which method arguments to explore.

I've done an implementation that seems to be a nice way to do this,  
without requiring you to modify your action and goal methods.
This is simply attaching methods to the original method via prenamed  
arguments:

      #actionName_argTypes
      #actionName_optimizations
      #goalName_optimizations

The solver object knows about these keywords, and applies the  
optimization for the method if the object under study understands
the messages above. All objects can return false on messages not  
understood, so if solver gets a false from messages above, it
knows the method has not defined optimizations.

E.g.

      " original action method "
     Allocator assign: reg var: var [ ... ]

     " returns arg types of method above
     Allocator assign: a var: b _argTypes: c [ ^Array with: Register  
with: Variable ]

      " returns optimizations for method above: returns a constraint  
on arguments
     Allocator assign: a var: b _optimization: c [ ^reg = R1 or:  
[ reg = R2] ]

     " original goal method "
     Allocator allocationDone [ ^unallocatedVars size = 0 ]

     " optimization for goal above "
    Allocator allocation_optimizations
    [
       " if pred true, explore  #assign:var:  method, if not explore  
#split:to: method..."
       ^( Array with: ( ( self canAllocate: (unallocatedVars first) )
                        ifTrue: [ #assign:var: ] ifFalse:  
[ #split:to: ] ) )
    ]

I'm using this scheme to handle optimizations in the register  
allocation by puzzle solving program:
http://www.cs.ucla.edu/~hesam/idst/object/examples/john/allocator.st


Regards,
Hesam