I think maybe our disagreement is about how good/useful of an overarching model ACT-R is? It’s definitely not like in physics, where some overarching theories are widely accepted (e.g. the standard model) even by people working on much more narrow topics—and many of the ones that aren’t (e.g. string theory) are still widely known about and commonly taught. The situation in cog sci (in my view, and I think in many people’s views?) is much more that we don’t have an overarching model of the mind in anywhere close to the level of detail/mechanistic specificity that ACT-R posits, and that any such attempt would be premature/foolish/not useful right now.
Makes some sense to me! This is part of why my post’s conclusion said stuff like this doesn’t mean you should believe in ACT-R. But yeah, I also think we have a disagreement somewhere around here.
I was trained in the cognitive architecture tradition, which tends to find this situation unfortunate. I have heard strong opinions, which I respect and generally believe, of the “we just don’t know enough” variety which you also espouse. However, I also buy Allen Newell’s famous argument in “you can’t play 20 questions with nature and win”, where he argues that we may never get there without focusing on that goal. From this perspective, it makes (some) sense to try to track a big picture anyway.
In some sense the grand goal of cognitive architecture is that it should eventually be seen as standard (almost required) for individual works of experimental psychology to contribute to a big picture in some way. Imagine for a moment if every paper had a section relating to ACT-R (or some other overarching model), either pointing out how it fits in (agreeing with and extending the overarching model) or pointing out how it doesn’t (revising the overarching model).
With the current state of things, it’s very unclear (as you highlighted in your original comment) what the status of overarching models like ACT-R even is. Is it an artifact from the 90s which is long-irrelevant? Is it the state of the art big-picture? Nobody knows and few care? Wouldn’t it be better if it were otherwise?
On the other hand, working with cognitive architectures like ACT-R can be frustrating and time consuming. In theory, they could be a time-saving tool (you start with all the power of ACT-R and can move forward from that!). In practice, my personal observation at least is that they add time and reduce other kinds of progress you can make. To caricaturize, a cog arch phd student spends their first 2 years learning the cognitive architecture they’ll work with, while a non-cog-arch cogsci student can hit the ground running instead. (This isn’t totally true of course; I’ve heard people say that most phd students are not really productive for their first year or two of grad school.) So I do not want to gloss over the downsides to a cog arch focus.
One big problem is what I’ll call the “task integration problem”. Let’s say you have 100 research psychologists who each spend a chunk of time doing “X in ACT-R” for many different values of X. Now you have lots of ACT-R models of lots of different cognitive phenomena. Can you mash them all together into one big model which does all 100 things?
I’m not totally sure about ACT-R, but I’ve heard that for most cognitive architectures, the answer is “no”. Despite existing in one cognitive architecture, the individual “X” models are sorta like standalone programs which don’t know how to talk to each other.
This undermines the premise of cog arch as helping us fit everything into one coherent picture. So, this is a hurdle which cog arch would have to get past in order to play the kind of role it wants to play.
Makes some sense to me! This is part of why my post’s conclusion said stuff like this doesn’t mean you should believe in ACT-R. But yeah, I also think we have a disagreement somewhere around here.
I was trained in the cognitive architecture tradition, which tends to find this situation unfortunate. I have heard strong opinions, which I respect and generally believe, of the “we just don’t know enough” variety which you also espouse. However, I also buy Allen Newell’s famous argument in “you can’t play 20 questions with nature and win”, where he argues that we may never get there without focusing on that goal. From this perspective, it makes (some) sense to try to track a big picture anyway.
In some sense the grand goal of cognitive architecture is that it should eventually be seen as standard (almost required) for individual works of experimental psychology to contribute to a big picture in some way. Imagine for a moment if every paper had a section relating to ACT-R (or some other overarching model), either pointing out how it fits in (agreeing with and extending the overarching model) or pointing out how it doesn’t (revising the overarching model).
With the current state of things, it’s very unclear (as you highlighted in your original comment) what the status of overarching models like ACT-R even is. Is it an artifact from the 90s which is long-irrelevant? Is it the state of the art big-picture? Nobody knows and few care? Wouldn’t it be better if it were otherwise?
On the other hand, working with cognitive architectures like ACT-R can be frustrating and time consuming. In theory, they could be a time-saving tool (you start with all the power of ACT-R and can move forward from that!). In practice, my personal observation at least is that they add time and reduce other kinds of progress you can make. To caricaturize, a cog arch phd student spends their first 2 years learning the cognitive architecture they’ll work with, while a non-cog-arch cogsci student can hit the ground running instead. (This isn’t totally true of course; I’ve heard people say that most phd students are not really productive for their first year or two of grad school.) So I do not want to gloss over the downsides to a cog arch focus.
One big problem is what I’ll call the “task integration problem”. Let’s say you have 100 research psychologists who each spend a chunk of time doing “X in ACT-R” for many different values of X. Now you have lots of ACT-R models of lots of different cognitive phenomena. Can you mash them all together into one big model which does all 100 things?
I’m not totally sure about ACT-R, but I’ve heard that for most cognitive architectures, the answer is “no”. Despite existing in one cognitive architecture, the individual “X” models are sorta like standalone programs which don’t know how to talk to each other.
This undermines the premise of cog arch as helping us fit everything into one coherent picture. So, this is a hurdle which cog arch would have to get past in order to play the kind of role it wants to play.