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Re: [ontolog-forum] Ontology based conversational interfaces

To: "'[ontolog-forum] '" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: "Rich Cooper" <metasemantics@xxxxxxxxxxxxxxxxxxxxxx>
Date: Wed, 15 Jul 2015 11:55:13 -0700
Message-id: <005701d0bf2f$c952a870$5bf7f950$@com>

A conversational system with flexibility will require an intelligent control system.  The usual linear system x[k+1] := A*x[k]+B*i[k] can be fashioned into the usual control system, but that is less flexible than I would like the conversational system to be. 

 

Here is an adaptation of linear systems to intelligent systems by adding a value judgment (VJ) subsystem to it.  The whole progression from standard linear system to value based system is shown at:

 

https://en.wikipedia.org/wiki/Real-time_Control_System

 

The so called RCS-4 version, the recommended intelligent control system, is described on that link, as summarized in overview here:

 

Value state-variables define what goals are important and what objects or regions should be attended to, attacked, defended, assisted, or otherwise acted upon. Value judgments, or evaluation functions, are an essential part of any form of planning or learning. The application of value judgments to intelligent control systems has been addressed by George Pugh.[16] The structure and function of VJ modules are developed more completely developed in Albus (1991).[2][17]

 

The Pugh reference is to RCS-4 concepts, while there is another Albus reference which includes figure 1 as the architecture overview below:

 

 

That architecture diagram is from:

 

"Outline for a Theory of Intelligence", which is in free PDF below:

ftp://calhau.dca.fee.unicamp.br/pub/docs/ia005/Albus-outline.pdf

 

The value judgment (VJ) module appears to steer the logic behind the Planning and Execution side of the diagram, at the whims of the World Model Database, while the old standby Situation Assessment side figures out what can possibly be thought, while the VJ module appears to figure out which thoughts work best of those available, and the planning and execution model decides what to focus on, schedule and do. 

 

A paper titled "A Value Driven System for Autonomous Information Gathering" is here:

 

http://rbr.cs.umass.edu/papers/GZjiis00.pdf

 

Here is a fast summary of that paper's content:

 

And finally, there needs to be a script of textual utterances, with patterns to be matched against variable bindings.  Each node in the DAG should also have a slot for some function capable of estimating the value of each utterance to each goal, and the duration and cost of each utterance to utter and process. 

 

That is where the DAG comes in, IMHO.  Every statement that is matched would have follow on questions to ask, together with a new set of expected patterns to be matched.  The highest value, lowest cost question designed to elicit an answer previously unknown and undeducable from the current world model would be one way to choose the next question.  

 

But variation helps make the utterances more interesting.  So each node in the conversation DAG should be a possible child of a branching node which has both possible utterances as children, perhaps many more nodes, each with a possible next conversation move. 

 

Reviews of the discourse representation systems (DRS), especially Kamp's should help interested readers (like myself) to wrap some meat around those bones, so here is a reference to Kamp's work I found in PDF form:

 

http://www.ims.uni-stuttgart.de/institut/mitarbeiter/uwe/Papers/DRT.pdf

 

Does anyone have references to a text generation paper they especially like?

 

Sincerely,

Rich Cooper,

Rich Cooper,

 

Chief Technology Officer,

MetaSemantics Corporation

MetaSemantics AT EnglishLogicKernel DOT com

( 9 4 9 ) 5 2 5-5 7 1 2

http://www.EnglishLogicKernel.com

 

-----Original Message-----
From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx [mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of John F Sowa
Sent: Tuesday, July 14, 2015 8:35 PM
To: ontolog-forum@xxxxxxxxxxxxxxxx
Subject: Re: [ontolog-forum] Ontology based conversational interfaces

 

Rich and Tom,

 

1983 was one of the "boom times" in the boom-and-bust cycle of AI.

That's when AI researchers were getting LISP machines and high-end workstations.  There was a lot of optimism about getting truly intelligent systems.  The Cyc project was started in 1984 with a 10-year plan to solve all the problems.

 

RC

> a free pdf about discourse and conversational analysis:

> https://abudira.files.wordpress.com/2012/02/discourse-analysis-by-gill

> ian-brown-george-yule.pdf

 

TJ

> I think it's definitely worth a read, although, being published in

> 1983, most of its value probably lies in documenting the history of

> discourse analysis...

 

That book does a good job of surveying the complex issues about the semantics of natural language and the many, many ways that language is related to context, speakers, presuppositions, etc.

 

And they also show the huge number of reasons why we still do not have computer systems today that can understand natural language.

 

For just one of the many reasons why formal systems for NLP have failed, look at page 80 of that book (if you're using the Adobe reader, it's p. 47):

 

> In this approach, each participant in a discourse has a presupposition

> pool and his pool is added to as the discourse proceeds.  Each

> participant also behaves as if there exists only one presupposition

> pool shared by all participants in the discourse.  Venneman emphasizes

> that this is true in 'a normal, honest discourse'.

 

The last line is a typical method for dismissing all the hard parts.

 

The authors of the book recognize and discuss the many complex issues involved in that assumption.  Unfortunately, what Venneman calls "a normal, honest discourse" rarely, if ever, exists -- I don't believe that the terms 'normal' or 'honest' are appropriate.

 

Unfortunately, the boom years of the 1980s were followed by a typical bust, when people realized that language understanding is much harder than anybody in realized.  I often quote Alan Perlis:

"A year spent working in artificial intelligence is enough to make one believe in God."

 

Those issues are the theme of a talk I presented last year on "Why has AI failed?  And how can it succeed?"

http://www.jfsowa.com/talks/micai.pdf

 

John

 

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