[ACT-R-users] Efficient approximation of the Base-Level Learning Equation

[Dan Bothell]

--On Wednesday, February 15, 2006 2:19 PM -0700 Alex Petrov 
<apetrov at alexpetrov.com> wrote:

> Dear ACToRs,
>
> As you know, the base-level equation is one of the pillars of ACT-R's
> success.  It has a serious practical drawback, however -- it consumes a
> lot of memory  and CPU cycles.  The approximate formula published in the
> 1998 book is good  for many purposes but does not capture the transient
> boost after each use of  a chunk. I have developed an improved
> approximation, which does take all  critical properties of the exact
> equation into account. It was used with  great success in the ANCHOR
> model of Petrov & Anderson (2005).  It can be  very useful for large
> simulations, allowing ACT-R to scale up to more  realistic memory sizes
> and more prolonged learning periods.  As far as I know  (though I'm not
> sure), it is already implemented in the current version of  ACT-R.  (Dan,
> can you please advise on that?)
>

Both ACT-R 5 and ACT-R 6 allow the optimized learning parameter to be
set to a number, and when it is a number, it computes the base-level
activation using that many specific references and the approximation
over the lifetime for any others (like the equation you show).

So, yes, it is implemented in the current version and it was also
implemented in the previous version.

Dan