[ACT-R-users] to Elaborate last message

Wed Apr 24 11:03:03 EDT 2013

My intuition says that partial-matching wouldn't be necessary if spreading activation was used "in place of" similarity, but so far we've just matched data involving explicit similarity ratings, not retrievals.

Laura

On Apr 24, 2013, at 10:57 AM, "Ball, Jerry T Civ USAF AFMC 711 HPW/RHAC" <Jerry.Ball at wpafb.af.mil> wrote:

> We also get the effect of partial matching in the word recognition component
> of our language analysis model by spreading activation from letters and
> trigrams in the perceptual input to words in declarative memory which have
> slots for the letters and trigrams. 
> 
> The problem with partial matching in ACT-R is that when it is turned on, all
> DM chunks are candidates for retrieval. There is not even a chunk type
> constraint. With 58,000 word chunks in our mental lexicon, the amount of
> computation to retrieve a word is prohibitive when partial matching is on.
> Our word retrieval mechanism is constrained to at least match on a word
> chunk type with a matching first letter (as a computational compromise),
> which limits the amount of computation.
> 
> The theoretically interesting question is whether or not partial matching is
> needed given spreading activation...
> 
> Jerry
> 
> P.S. I hope someone will correct my comments about ACT-R, if they are
> incorrect
> 
> -----Original Message-----
> From: Lynne Reder [mailto:reder at cmu.edu] 
> Sent: Wednesday, April 24, 2013 10:35 AM
> To: Laura Hiatt
> Cc: Ball, Jerry T Civ USAF AFMC 711 HPW/RHAC; Kelley, Troy D CIV (US);
> ACT-R-users at act-r.psy.cmu.edu
> Subject: to Elaborate last message
> 
> there is no need for similarity values bc I only try to model similarity
> when I have manipulated the features explicitly in the experiment (e.g.,
> font and fan of font, or the operator).  So the overlap in features is
> objectively determined.  I'm sure it is not adequate for most of what one
> needs to do however so I inhibited writing for the last week, but my guard
> is down...
> 
> On Apr 24, 2013, at 10:32 AM, Lynne Reder wrote:
> 
>> I have a tiny model based on earlier versions of ACT (no production
> system, just nodes and spreading activation).  Many of the assumptions are
> the same as the declarative side of ACT-R but some aren't, either by
> accident (I used what I thought was in the system) or design.  In any case I
> have been modeling partial matching for years.  The way it works in SAC is
> that if the component features are activated/primed, they spread activation
> to associated nodes.  If enough of the features are primed, it can get
> sufficient activation to get the wrong node over threshold.  We have modeled
> this in Feeling of Knowing tasks (where we swapped operators), in
> recognition tasks where the unique font of the probe word matches a studied
> word and the person FAs, etc.  
>> 
>> If anyone is curious I can point you to the work (some is in the process
> of being written up for an invited chapter).
>> 
>> Cheers,
>> Lynne
>> 
>> On Apr 24, 2013, at 10:24 AM, Laura Hiatt wrote:
>> 
>>> Thanks for the great feedback, everyone!  We have a new ACT-R-based
> approach to similarity that we are developing here, based on base-level /
> spreading activation values as the model runs (paper at CogSci this sumer);
> I am looking to test it in a variety of situations (such as blending).  
>>> 
>>> Thanks again,
>>> Laura
>>> 
>>> 
>>> On Apr 23, 2013, at 9:11 AM, "Ball, Jerry T Civ USAF AFMC 711 HPW/RHAC"
> <Jerry.Ball at wpafb.af.mil> wrote:
>>> 
>>>> Laura,
>>>> 
>>>> Troy's comment reminds me that Raluca Bidiu used LSA to set 
>>>> similarity values in her research on "the Moses illusion". Here's a
> paper:
>>>> 
>>>> Budiu, R. & Anderson, J. R. (2004). Interpretation-Based Processing: 
>>>> A Unified Theory of Semantic Sentence Processing. Cognitive Science 28,
> 1-44.
>>>> 
>>>> The paper is available on the ACT-R web site under "Language Processing:
>>>> Analogy and Metaphor".
>>>> 
>>>> Jerry
>>>> 
>>>> -----Original Message-----
>>>> From: act-r-users-bounces at act-r.psy.cmu.edu
>>>> [mailto:act-r-users-bounces at act-r.psy.cmu.edu] On Behalf Of Kelley, 
>>>> Troy D CIV (US)
>>>> Sent: Tuesday, April 23, 2013 8:35 AM
>>>> To: Magill, Laura M CIV (US); ACT-R-users at act-r.psy.cmu.edu
>>>> Subject: Re: [ACT-R-users] similarity in partial-matching/blending
>>>> 
>>>> Laura,
>>>> 
>>>> "Dynamically during runs" sounds interesting.  I have also been 
>>>> thinking that using something like Latent Semantic Analysis (LSA) or 
>>>> the similarity values in ConceptNet might be a useful way of setting the
> initial values.
>>>> 
>>>> Troy D. Kelley
>>>> RDRL-HRS-E
>>>> Cognitive Robotics and Modeling Team Leader Human Research and 
>>>> Engineering Directorate U.S. Army Research Laboratory Aberdeen, MD 
>>>> 21005 Phone
>>>> 410-278-5869 or 410-278-6748 Note my new email address:
>>>> troy.d.kelley6.civ at mail.mil
>>>> 
>>>> 
>>>> 
>>>> On 4/22/13 10:27 AM, "Laura Hiatt" <laura.hiatt at nrl.navy.mil> wrote:
>>>> 
>>>>> Hi All,
>>>>> 
>>>>> I am looking for pointers to papers or work on 
>>>>> partial-matching/blending that utilizes similarity values between 
>>>>> chunks.  Much of what I have read using these mechanisms relies on
>>>> numerical values (like blending utility values).
>>>>> Lately we have been working on studying similarity between chunks, 
>>>>> and how we can calculate it dynamically during model runs; I would 
>>>>> love to be able to compare what we've come up with to some other 
>>>>> approaches to
>>>> similarity.
>>>>> 
>>>>> Thanks,
>>>>> Laura
>>>>> 
>>>>> 
>>>>> _______________________________________________
>>>>> ACT-R-users mailing list
>>>>> ACT-R-users at act-r.psy.cmu.edu
>>>>> https://mailman.srv.cs.cmu.edu/mailman/listinfo/act-r-users
>>>> 
>>>> Troy D. Kelley
>>>> RDRL-HRS-E
>>>> Cognitive Robotics and Modeling Team Leader Human Research and 
>>>> Engineering Directorate U.S. Army Research Laboratory Aberdeen, MD 
>>>> 21005 Phone
>>>> 410-278-5869 or 410-278-6748 Note my new email address:
>>>> troy.d.kelley6.civ at mail.mil
>>>> 
>>>> 
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>>> 
>>> 
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>> 
>> 
> 