Well, perhaps you can diagram how you propose to implement it.
I hope you will have a working implementation.
~PM

From: [email protected]
To: [email protected]
Subject: Re: [agi] Goal Selection
Date: Wed, 15 May 2013 17:43:37 -0400








Once again, I work on the level of operations, 
not some immutable "programs".
Level-specific comparison-evaluations convert 
a queue of input patterns into a queue of template patterns, which make-up 
a level.
These patterns have level-specific syntax, 
incremented by corresponding comparison-evaluations from the syntax of input 
patterns. 
Levels "interact" with each other via 
feedforward & feedback.
My whole intro is an attempt to explain how 
this increase in complexity of comparison-evaluations 
*begins*.
It's a 1D sequence, 2D diagram is a wrong 
format for such subject.
I can't explain it better unless you tell me 
what in my intro is not clear to you, Michael.
     




From: Piaget Modeler 
Sent: Wednesday, May 15, 2013 5:14 PM
To: AGI 
Subject: RE: [agi] Goal Selection


Boris, 


What specific programs run to create the levels of structures?  


Can you diagram and label those programs? 
Do the programs interact with one another? 


Kindly advise.


~PM





From: [email protected]
To: [email protected]
Subject: Re: [agi] Goal 
Selection
Date: Wed, 15 May 2013 16:46:20 -0400




 

The "architecture" is incremental: no 
blocks, just levels.
All I have is incremental-complexity 
comparison-evaluation operations, explained in the intro.
Everything else is learned, that's what 
makes it *general*.

 

From: Piaget Modeler 
Sent: Wednesday, May 15, 2013 1:15 PM
To: AGI 

Subject: RE: [agi] Goal Selection


Perhaps architecture diagram would be a more specific term. 


What architecture implements your proposed system.  Can you draw 
it? 


Thanks,


~PM




From: [email protected]
To: [email protected]
Subject: Re: [agi] Goal 
Selection
Date: Wed, 15 May 2013 09:51:48 -0400




Michael,
 
> Do you have a diagram to go along 
with your explanation?
 
Depends what you're looking for. In humans, 
every part of the brain affects motivation & attention.
For GI, the only useful motive is curiosity (a 
drive to maximize predictive correspondence), &
"discrete 
components" are learned patterns, rather than 
built-in "modules".
 
The nearest thing to a diagram that I have is 
grouping levels of search by incremental order of distance
between comparands:
- Comparison of adjacent inputs, 
forming continuous patterns of incremental dimensionality (distance = 1): 

line segments: 1D, blobs: 2D, objects: 
3D, & processes: 4D. This is similar to connected-component 
analysis.
- Cross-comparison across 
a whole queue of inputs, forming discontinuous patterns per 
input.(distance->n).
These patterns are 
fuzzy, & their 
overlap is compensated by selection among inputs to a next level.
- 
Comparison across a hierarchy of short-cuts to higher-level queues, generated 
by 
feedback (distance -> nn)...:
www.cognitivealgorithm.info.





> I'm looking at attention 
rather than motivation.

> For me, attention is the filtering or 
re-prioritization of goals. 
 
Attention is prioritizing areas 
of search, according to the weights assigned by combined motives 
(salience).
Conscious attention is WTA mechanism, 
imposed by our brain-to-body bottleneck: 
http://cognitive-focus.blogspot.com/2012/06/temporal-attention-span-our-dominant.html
This is irrelevant for GI because it 
shouldn't assume any fixed "body". 
What's relevant is distributed 
"unconscious" attention, which is a market-like 
mechanism that allocates 
cognitive resources to the areas of 
search, in proportion to their projected contribution to total
predictive correspondence of one's 
model of the environment. 
 
> In the PAM-P2 system I have an 
intuition that a higher level of selection occurs than is 
explained than by basic action selection.
 
Right, 
this is a selection of "cognitive actions": prioritization of internal search, 
covered above.


> Motivation is handled in PAM-P2 
through the use of homeostatic variables and 
"urges",
> deltas between current and 
target homeostatic variable values. 
 
That's an equivalent of my "instincts", - a supervised 
learning part, irrelevant for GI per se.
 
> My intuition tells me that there should be another, 
higher level of goal selection. (Or, perhaps goal
filtering, not exactly sure). Something that operates 
above action selection that takes into account 
all the possible 
goals the system could have and ensures that the most important at the current 

moment are part of the agenda.
 
Again, you're talking about the same thing from different 
POVs. 
"Goal" is a positive-value-charged state, or its 
internalized representation.
Motivation is what does this value-charging, thus 
determines the priority of 
searching though related internal representations & 
external sources.  
 




From: Piaget Modeler 
Sent: Tuesday, May 14, 2013 5:56 PM
To: AGI 

Subject: RE: [agi] Goal Selection


Hi Boris,  


Thanks for the references.  Do you have a diagram to go along with 
your explanation? 
That would be much appreciated.  A diagram helps the explanatory cloud 
to be decomposed 
into discrete components.


I'm looking at attention rather than motivation.  Motivation is handled in 
PAM-P2 through 
the 
use of homeostatic variables and "urges", 
deltas between current and target homeostatic 
variable 
values.  For me, attention is the filtering or re-prioritization 
of goals.  In the PAM-P2 system I have an 
intuition that a higher level of 
selection occurs than is explained than by basic action selection.


In PAM-P2 there are two action selectors: the Reactor, which matches 
existing solutions 
to sensory stimuli, and the Deliberator which matches existing solutions 
with active situations 
and needs (goals).  Both action 
selectors operate in a case based manner, where "solutions"
are the cases.  Once a solution is 
selected, it may generate subgoals to assist in attaining the
overall solution. 


My intuition tells me that there should be 
another, higher level of goal selection. (Or, perhaps goal
filtering, not exactly sure). Something that 
operates above action selection that takes into account 
all the possible goals the system could have and ensures that 
the most important at the current 
moment are part of the agenda. 
 
 
Your thoughts?


~PM





From: [email protected]
To: [email protected]
Subject: Re: [agi] Goal 
Selection
Date: Tue, 14 May 2013 17:15:51 -0400




You're really trying to understand how human 
motivation works. I already posted this, but in case you missed:
 
Human motivation: developmental 
perspective.


Motivation is all mental 
mechanisms that drive our behavior, in which I include cognitive behavior: 
analysis, introspection, & planning for somatic behavior. 

Values / motives in humans & higher animals can be divided into three 
broad categories, according to the mechanism that formed or selected 
them:

Evolution selects instincts fit for their own propagation, innate but 
subsequently modulated by usage, 
Conditioning value-charges stimuli coincident with previously 
value-loaded stimuli in time or space, 
Cognitive curiosity 
searches / selects for predictive patterns, even if they consist of 
value-free stimuli.

Higher mechanisms accelerate adaptive value 
acquisition by acting on increasingly mediated responses: from immediate 
behavioral reactions to longer-term attention, prediction, & 
planning.
Brain areas that implement these value-acquisition mechanisms 
likely evolved in the same sequence:

Instincts, largely physiological 
& traceable to 4Fs, are encoded mainly in brainstem & 
hypothalamus. 

Conditioning is initiated by 
basal 
ganglia & 
limbic 
system, then extended & generalized by 
neocortex. 
Predictive curiosity is an innate driver of 
neocortex, which is also heavily modulated by lower motives.

This scheme 
is vaguely similar to triune brain 
model, but in my interpretation these substrates 
differ mainly in the mechanism by which they acquire values, rather than in 
resulting & relatively transient motives themselves. These value acquisition 
mechanisms are innate, but their relative strength varies.

Our instincts 
are pretty basic & similar to those of other mammals. An excellent account 
of that level of motivation is Jaak Panksepp‘s “Archaeology of 
Mind: Neuroevolutionary Origins of Human 
Emotions“. The discussion below is 
mostly on conditioning & cognition: increasingly adaptive mechanisms which 
seem to strengthen with our personal 
growth:

 
http://cognitive-focus.blogspot.com/2012/06/motivation-evolution-of-value.html
 





From: Piaget Modeler 
Sent: Tuesday, May 14, 2013 4:17 PM
To: AGI 

Subject: RE: [agi] Goal Selection


Getting Closer: 

Top-down versus bottom up attentional control: a failed 
theoretical dichotomy



http://ems.psy.vu.nl/userpages/theeuwes/Trends_2012_Awh.pdf


The priority map notion is closer to what I was looking for.  
I know that priorities fit in somehow.


~PM








  
  
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