----- Original Message -----
From: "Ben Goertzel" <[EMAIL PROTECTED]>
To: <agi@v2.listbox.com>
Sent: Wednesday, May 31, 2006 8:25 AM
Subject: Re: [agi] Types of Knowledge Representaion and Advantages & Disadvantages?

 

> Well, the main disadvantage of not representing knowledge is that
> doing so makes you completely unintelligent ;-)  [Of course, whether
> or not this is really a disadvantage is a philosophical question, I
> suppose.  It has been said that "ignorance is bliss" ... ]

>

Those that choose this path are not likely to achieve success.

>
> Seriously: Do you mean to suggest that some intelligent systems
> *don't* contain any (even implicit) representation of knowledge?
>

My question was more to the different methodology of knowledge Representations (KR) and Knowledge Base (KB) types of designs and their performance at retrieving facts in respect to the computer time/computer instructions required to retrieve facts and storage requirements.

>
> I have seen this claim made by some advocates of
> self-organizing-systems approaches to building and analyzing
> intelligent systems, but I have always felt it to be a kind of "game
> with words"... (Feel free to argue otherwise, though!)
>

The product configuration baseline should be functionally interwoven with the sophisticated software and

adds many different trade off considerations. (wordy pun)

 

All I am interested in is what works fast and within the limits of resources.  

 

>
> IMO, all intelligent systems represent knowledge internally in some
> sense, and the right question is what methods are best (in what
> senses) for doing so....
>

What methods are best (concerning fast retrieval, low number of computer instructions, low memory requirement) now this can also mean that these facts are somehow zipped/compressed to reduce memory storage requirements.

Maybe someone might know of how much (percent) compression can be achieved to help reduce the KB to some more manageable size, yet again there are some computer instructions/time needed to use this methodology.

>
> For instance, in an attractor neural net, each piece of knowledge is
> stored in a wholly distributed way, interpenetrated with other pieces
> of knowledge.  In a traditional semantic net OTOH, pieces of knowledge
> are stored separately and distinctly without interpenetration.  In
> Novamente's hybrid design there is both a distinct and an
> interpenetrative/holistic aspect to knowledge representation.  The
> advantages and disadvantages of these different KR strategies may be
> subtle to understand...
>
> -- Ben G

>
>
> On 5/30/06, Danny G. Goe <[EMAIL PROTECTED]> wrote:
>>
>>
>> Can someone elaborate on the advantages and disadvantages of Knowledge
>> Representation(KR)?
>>
>> Dan Goe

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