>> I think Ben's text mining approach has one big flaw:  it can only reason 
>> about existing knowledge, but cannot generate new ideas using words / 
>> concepts

There is a substantial amount of literature that claims that *humans* can't 
generate new ideas de novo either -- and that they can only build up "new" 
ideas from existing pieces.

>> Such rewrite rules are very numerous and can be very complex -- for example 
>> rules for auxiliary words and prepositions, etc

The epicycles that the sun performs as it moves around the Earth are also very 
numerous and complex -- until you decide that maybe you should view it as the 
Earth moving around the sun instead.  Read some Pinker -- the rules of language 
tell us *a lot* about the tough-to-discern foundations of human cognition.
  ----- Original Message ----- 
  From: YKY (Yan King Yin) 
  To: agi@v2.listbox.com 
  Sent: Thursday, February 28, 2008 4:37 AM
  Subject: Re: [agi] would anyone want to use a commonsense KB?



  My latest thinking tends to agree with Matt that language and common sense 
are best learnt together.  (Learning langauge "before" common sense is 
impossible / senseless).

  I think Ben's text mining approach has one big flaw:  it can only reason 
about existing knowledge, but cannot generate new ideas using words / concepts. 
 I want to stress that AGI needs to be able to think at the WORD/CONCEPT level. 
 In order to do this, we need some rules that *rewrite* sentences made up of 
words, such that the AGI can reason from one sentence to another.  Such rewrite 
rules are very numerous and can be very complex -- for example rules for 
auxillary words and prepositions, etc.  I'm not even sure that such rules can 
be expressed in FOL easily -- let alone learn them!

  The embodiment approach provides an environment for learning qualitative 
physics, but it's still different from the common sense domain where knowledge 
is often verbally expressed.  In fact, it's not the environment that matters, 
it's the knowledge representation (whether it's expressive enough) and the 
learning algorithm (how sophisticated it is).

  YKY

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