Conference heron::euro_swas_ai

82.0. "[Model Based Diagnosis]" by HERON::ROACH (TANSTAAFL !) Mon Feb 27 1989 09:59

                  I N T E R O F F I C E   M E M O R A N D U M

                                        Date:     23-Feb-1989 11:24am CET
                                        From:     WEYMOUTH
                                                  WEYMOUTH@DROO@MRGATE@DELOS@VBO
                                        Dept:      
                                        Tel No:    

TO:  ROACH@A1NSTC


Subject: [Model Based Diagnosis]


Newsgroups: comp.ai
Path: decwrl!sun!pitstop!sundc!seismo!uunet!mcvax!hp4nl!swivax!ameen
Subject: Model Based Diagnosis
Posted: 21 Feb 89 11:27:15 GMT
Organization: SWI, UvA, Amsterdam
 
I'm interested in work concerning *model based* diagnosis in technical
domains (electrical or mechanical). Especially *complex* systems (mostly
*dynamic* in behavior) where appropriate abstract modeling should encounter
this complexity.
In particular, ideas/systems that reason about *multiple models* of the 
same device under diagnosis these include such issues as:
 
o criteria for dynamic choosing of the current "best" model.
  (could be symptom directed).
 
o criteria for determining that assumptions supporting the current 
  considered model are no longer valid (e.g. diagnosis failed or 
  inadequately discriminatory) and hence a different set of assumptions
  (implying a different model) should be tried. (One simple example is 
  Davis' "bridge fault").
 
o non-monotonic reasoning about suspect components (a measure of belief
  that a certain suspect is indeed a culprit and further investigation
  in it's sub-components is worthwhile, it may indeed appear that this
  is not the case). 
 
o dealing with feedback loops among suspect components.
 
o test cost considerations in suggesting test probes (other than just
  probability of failure like in DeKleer & Williams).
 
Also heuristics to achieve the above mentioned goals and associative
knowledge for diagnosis of "hard to model" components.
 
	A former work dealt with modeling the same device on different levels
of behavioral abstractions (e.g. behavior of a chip output could be
depicted in terms like: "pulse_train_generated", "frequency", "pulse_width" 
etc..) and each layer was built automatically from the level(s) underneath.
	Diagnosis, then,  dealt with the highest abstract level which still
provided a discrepancy. At certain levels a more refined level had
to be considered. Each level (according to it's coarseness) possibly
abstracted underlying structure).
But the non-monotonic reasoning and explicit criteria for choosing
the right level and the diversity of models concerning structure was
lacking.
 
Any ideas or references are appreciated, e-connection concerning model-based 
diagnosis is as well welcomed. Please e-mail to the e-address below.
 
-- 	Ameen Abu-Hanna. ([email protected]).
	SPIN Project
	Social Science Informatics; University of Amsterdam
	Herengracht 196
	Amsterdam 1016
	The Netherlands.