[ACT-R-users] computational basis of act-r

[James Peters]

I was kind of expecting John and/or Chris to jump in here, but they 
haven't.  The statement that ACT-R has not computational similarity to the 
brain is just plain false.  ACT-R does aggregate functions, but its 
development has always been based on neural plausibility.  In fact, one of 
John's "best kept secrets" is the existence of ACT-RN, the neural network 
version of ACT-R.  I believe John, Chris, and I are the only people who 
every developed models in ACT-RN, but those exercises led to modifications 
to ACT-R to help maintain its neural plausibility (e.g., partial 
matching).  The behavior of the models (admittedly small) I build in 
ACT-RN were virtually the same as ACT-R models.  So, saying the ACT-R is 
not neurally plausible, I believe, is just plan wrong.

Jim




Chris Chatham <chatham at m-laboratories.net>
Sent by: act-r-users-admin at act-r.psy.cmu.edu
01/14/03 07:54 AM

 
        To:     act-r-users at act-r.psy.cmu.edu
        cc: 
        Subject:        [ACT-R-users] computational basis of act-r


A couple of days ago, I talked to a researcher at Penn's Institute for 
Research in Cognitive Science who believes ACT-R will be outdated in the 
next couple of years.

He believed that the fundamental method of computation in the brain is 
"oscillation" and that because ACT-R has no computational similarity to 
the 
neurological structure of the brain, it will always be a poor modeling 
architecture.

I asked whether ACT-R might be expanded at the subsymbolic level to 
include 
this type of modeling.  Any thoughts here from the group, or in regards to 

the IRCS researcher's opinion?

-Chris.


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