These may be relevant 
Owen,   Analogy for Automated ReasoningMartin,  A Computational Model of 
Metaphor InterpretationFrench,  The Subtlety of Sameness 
~PM

> From: johnr...@polyplexic.com
> To: a...@listbox.com
> Subject: RE: [agi] Abstract Creativity
> Date: Sun, 29 Dec 2013 10:14:19 -0500
> 
> OK, here is another way an abstract creativity would work. I call it
> abstract because it is a creativity that operates amongst many domains.
> 
> The world is full of correlative structure. A simple example is a circle.
> It's everywhere. A more complex example could be a chunk of BNF, a
> contextually free correlative structure. Another correlative structure would
> be "symmetry". Many of the omnipresent structures can be cataloged into a
> database. This is essentially a type of common sense knowledgebase.
> 
> Then, creativity is the act of injecting and modelling correlative structure
> domain specific, estimating computational expense effect in and after
> integration, and choosing amongst with confidence. Being more creative would
> essentially mean using more complex, less applicable, and more estimative
> correlative structure successfully. This is very simple at a highly
> conceptional level. Note that correlative structure might be new in a
> specific instance and might be derived recently from observation. In this
> model it is very close to what intelligence is, even to where it is a
> component of intelligence. Also it does inherently include
> counterfactuality. And even though it includes "analogy" it is not bound by
> the cognitive concept of what that is. I find it annoying when people say -
> oh that's just analogy or "analogical reasoning" and then it gets
> pigeonholed into that circle. This might be some form of analogical
> reasoning this is implementable for a specific model of AGI.
> 
> John
> 
> -----Original Message-----
> From: Jim Bromer [mailto:jimbro...@gmail.com] 
> Sent: Friday, December 27, 2013 11:16 PM
> To: AGI
> Subject: Re: [agi] Abstract Creativity
> 
> The view that an insight is a system based on observations and a lot of
> creative explanations is a little problematic.
> 
> But, just because a part of an insight is imaginative does not mean that it
> is not a rational bridge in the insight (of course).
> 
> So when we can come up with a creative explanation to fill in a gap of an
> insight we would like to make the explanation utilize some observations of
> effects in a way as to provide the explanation with more structure. So it is
> not just an observation correlation but an rational explanation that
> correlates with some effective observation points.  Observation points are
> often used in definitions and the rational explanations needed to fill in
> the gaps are often based explanations for similar kinds of things.
> 
> For example:
> A programming language is based mostly on using a context-free grammar.
> (Some of the observation points here are the programmer's recall of first
> realizing that he is using syntactic grammars to write
> programs.)
> 
> So a computer program that is designed to learn can be said to be using a
> syntactic grammar.  Even if an AI program that is designed to learn a
> natural language grammar through trial and error does not start with a base
> of a natural language grammar, it still cannot be said to use no grammar at
> all. It is using a computational grammar of some sort even if the programmer
> does not consciously think of it in that way. (Here, for example, the
> programmer might recall his recognition that computer programs are
> inputting, rearranging  and outputting strings of individual values that are
> similar to or are characters in a syntactic string.
> 
> A computer could learn a very simple context-free grammar through trial and
> error alone.  (We have all seen programs that were able to 'learn' something
> incrementally and most of us are familiar with reinforcement methods so this
> does not require a lot of fantasizing to arrive at the conclusion that this
> may be feasible.  And when you realize that what I am talking about is that
> simple context free grammars only have to be treated as worded input
> 'commands' -that are followed at least some of the time- then this looks
> very feasible. In fact, it seems so feasible that almost any experienced
> programmer who has some sense of what I am talking about could try it.)
> 
> Finally, the acquired (not pre-programmed) simple context-free grammars
> (using words) could be used to teach the AI program some simple natural
> language structure that use context-sensitive and other natural language
> grammars. (This is the conjecture which seems feasible if you accept the
> other steps.  But this step absolutely requires experimentation to confirm.
> The skeptics try to point out that learning to use natural language requires
> some fundamental knowledge of what the words represent but that is what can
> be taught when the program is learning to react to simple worded commands
> and later higher level explanations.) (There were few observation points in
> this last part but it is really the rearrangement of familiar definitions
> that are serving as rational bridges over the spans that the incredulous
> skeptics of the conjecture object to.  So even though no one has observed an
> AI/AGI program that can do this, it really does make sense.  If there is a
> problem then, it probably must be due to the complexity of the knowledge
> that would be required to make this an effective AGI paradigm.
> 
> 
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