According to the in-house Cycorp jargon, deep inference begins at approximately 
four backchain steps in a deductive inference.  As most here know, there is an 
exponential fanout in the number of separate inference paths with each 
backchain step, given a large candidate rule set and a large set of facts.

One or two backchain steps can usually be accomplished in seconds by Cyc.  Deep 
inference, let's say six backchain steps, may require hours if it completes at 
all.   Cyc is designed to make the best use of the time allocated for answering 
a query, and the iterative deepening stategy was proposed as a query 
configuration alternative.   It is possible that Cycorp uses it now - I no 
longer have access to its source code.
 
Although I agree that a resolution based refutation proof may be more efficient 
for answering a yes/no query, I think, as did Cycorp, that effort is better 
spent on a single inference engine that operates in a constructive manner, like 
an ordinary SQL query engine, but with heuristic rule application included.

-Steve


Stephen L. Reed 
Artificial Intelligence Researcher
http://texai.org/blog
http://texai.org
3008 Oak Crest Ave.
Austin, Texas, USA 78704
512.791.7860

----- Original Message ----
From: YKY (Yan King Yin) <[EMAIL PROTECTED]>
To: [email protected]
Sent: Tuesday, February 19, 2008 7:41:06 AM
Subject: Re: [agi] would anyone want to use a commonsense KB?

[snip]Thanks a lot for the info.  These are very important speed-up strategies. 
 I have not yet studied this aspect in detail.
  
 Can you explain what you mean by "deep inference"?
  
 I think resolution theorem proving provides a way to answer yes/no queries in 
a KB.  I take it as a starting point, and try to think of ways to speed it up 
and to expand its abilities (answering what/where/when/who/how queries).
   
 YKY
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