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␈↓ α∧␈↓␈↓ u1


␈↓ α∧␈↓α␈↓ ∧QEXPERT SYSTEMS AND COMMON SENSE

␈↓ α∧␈↓α␈↓ ¬
John McCarthy, Stanford University

␈↓ α∧␈↓α␈↓ ¬.Copyright 1983, John McCarthy

␈↓ α∧␈↓␈↓ αTAn␈α␈↓↓expert␈αsystem␈↓␈αis␈αa␈αcomputer␈αprogram␈αintended␈αto␈αembody␈αthe␈αknowledge␈αand␈αability␈αof

␈↓ α∧␈↓an␈α∂expert␈α⊂in␈α∂a␈α∂certain␈α⊂domain.␈α∂ The␈α∂ideas␈α⊂behind␈α∂them␈α∂and␈α⊂many␈α∂examples␈α∂fill␈α⊂the␈α∂artificial

␈↓ α∧␈↓intelligence␈αliterature.␈α Their␈αperformance␈αin␈αtheir␈αspecialized␈αdomains␈αare␈αoften␈α
very␈αimpressive.

␈↓ α∧␈↓Nevertheless,␈α
hardly␈α
any␈α
of␈αthem␈α
have␈α
certain␈α
␈↓↓common␈αsense␈↓␈α
knowledge␈α
and␈α
ability␈α
possessed␈αby

␈↓ α∧␈↓any␈α
non-feeble-minded␈α
human.␈α
 This␈α
lack␈α
makes␈α
them␈α
"brittle".␈α
 By␈α
this␈α
is␈α
meant␈α
that␈α
they␈α
are

␈↓ α∧␈↓difficult␈α
to␈α
extend␈α
beyond␈αthe␈α
scope␈α
originally␈α
contemplated␈αby␈α
their␈α
designers,␈α
and␈α
they␈αusually

␈↓ α∧␈↓don't␈α∂recognize␈α∂their␈α∂own␈α∂limitations.␈α∂ Many␈α∂important␈α∂applications␈α∂will␈α∂require␈α∂common␈α∂sense

␈↓ α∧␈↓abilities.␈α
 The␈α
object␈α∞of␈α
this␈α
lecture␈α
is␈α∞to␈α
describe␈α
common␈α
sense␈α∞abilities␈α
and␈α
the␈α∞problems␈α
that

␈↓ α∧␈↓require them.

␈↓ α∧␈↓␈↓ αTCommon␈α
sense␈α
facts␈αand␈α
methods␈α
are␈αonly␈α
very␈α
partially␈αunderstood␈α
today,␈α
and␈αextending

␈↓ α∧␈↓this understanding is the key problem facing artificial intelligence.

␈↓ α∧␈↓␈↓ αTThis␈αisn't␈αexactly␈αa␈αnew␈αpoint␈αof␈αview.␈α I␈αhave␈αbeen␈αadvocating␈α"Computer␈αPrograms␈αwith

␈↓ α∧␈↓Common␈αSense"␈αsince␈αI␈αwrote␈αa␈αpaper␈αwith␈αthat␈αtitle␈αin␈α1958.␈α Studying␈αcommon␈αsense␈αcapability

␈↓ α∧␈↓has␈α⊂sometimes␈α⊂been␈α⊂popular␈α⊂and␈α⊃sometimes␈α⊂unpopular␈α⊂among␈α⊂AI␈α⊂researchers.␈α⊂ At␈α⊃present␈α⊂it's

␈↓ α∧␈↓popular,␈α⊗perhaps␈α⊗because␈α⊗new␈α⊗AI␈α⊗knowledge␈α∃offers␈α⊗new␈α⊗hope␈α⊗of␈α⊗progress.␈α⊗ Certainly␈α∃AI

␈↓ α∧␈↓researchers␈αtoday␈αknow␈αa␈αlot␈αmore␈αabout␈αwhat␈αcommon␈αsense␈αis␈αthan␈αI␈αknew␈αin␈α1958␈α-␈αor␈αin␈α1969

␈↓ α∧␈↓when␈α∂I␈α∞wrote␈α∂another␈α∞paper␈α∂on␈α∞the␈α∂subject.␈α∞ However,␈α∂expressing␈α∞common␈α∂sense␈α∂knowledge␈α∞in

␈↓ α∧␈↓formal␈α
terms␈α
has␈α
proved␈α
very␈α
difficult,␈α
and␈α
the␈α
number␈α
of␈α
scientists␈α
working␈α
in␈α
the␈α
area␈α
is␈αstill␈α
far

␈↓ α∧␈↓too␈αsmall.␈α Moreover,␈α
there␈αis␈αsubstantial␈α
disagreement␈αabout␈αwhat␈α
common␈αsense␈αabilities␈αare␈α
and

␈↓ α∧␈↓how to program them in computers.

␈↓ α∧␈↓␈↓ αTOne␈α∞of␈α∞the␈α∞best␈α
known␈α∞expert␈α∞systems␈α∞is␈α
MYCIN␈α∞(Shortliffe␈α∞1976;␈α∞Davis,␈α∞Buchanan␈α
and
␈↓ α∧␈↓␈↓ u2


␈↓ α∧␈↓Shortliffe␈α
1977),␈α∞a␈α
program␈α
for␈α∞advising␈α
physicians␈α∞on␈α
treating␈α
bacterial␈α∞infections␈α
of␈α∞the␈α
blood

␈↓ α∧␈↓and␈α∞meningitis.␈α∞ It␈α∞does␈α∞reasonably␈α∞well␈α∞without␈α∞common␈α∞sense,␈α∞provided␈α∞the␈α∞user␈α∞has␈α∞common

␈↓ α∧␈↓sense and understands the program's limitations.

␈↓ α∧␈↓␈↓ αTMYCIN␈αconducts␈αa␈αquestion␈αand␈αanswer␈αdialog.␈α After␈αasking␈αbasic␈αfacts␈αabout␈αthe␈αpatient

␈↓ α∧␈↓such␈α
as␈α
name,␈α
sex␈α
and␈α
age,␈α∞MYCIN␈α
asks␈α
about␈α
suspected␈α
bacterial␈α
organisms,␈α
suspected␈α∞sites␈α
of

␈↓ α∧␈↓infection,␈α∪the␈α∪presence␈α∪of␈α∩specific␈α∪symptoms␈α∪(e.g.␈α∪fever,␈α∩headache)␈α∪relevant␈α∪to␈α∪diagnosis,␈α∩the

␈↓ α∧␈↓outcome␈αof␈αlaboratory␈αtests,␈α
and␈αsome␈αothers.␈α It␈αthen␈α
recommends␈αa␈αcertain␈αcourse␈α
of␈αantibiotics.

␈↓ α∧␈↓While␈α∞the␈α
dialog␈α∞is␈α
in␈α∞English,␈α∞MYCIN␈α
avoids␈α∞having␈α
to␈α∞understand␈α
freely␈α∞written␈α∞English␈α
by

␈↓ α∧␈↓controlling␈α⊂the␈α⊂dialog.␈α⊃ It␈α⊂outputs␈α⊂sentences,␈α⊃but␈α⊂the␈α⊂user␈α⊂types␈α⊃only␈α⊂single␈α⊂words␈α⊃or␈α⊂standard

␈↓ α∧␈↓phrases.␈α Its␈α
major␈αinnovations␈α
over␈αmany␈α
previous␈αexpert␈αsystems␈α
were␈αthat␈α
it␈αuses␈α
measures␈αof

␈↓ α∧␈↓uncertainty␈α⊂(not␈α⊂probabilities)␈α∂for␈α⊂its␈α⊂diagnoses␈α⊂and␈α∂the␈α⊂fact␈α⊂that␈α⊂it␈α∂is␈α⊂prepared␈α⊂to␈α⊂explain␈α∂its

␈↓ α∧␈↓reasoning to the physician, so he can decide whether to accept it.

␈↓ α∧␈↓␈↓ αTOur␈αdiscussion␈αof␈α
MYCIN␈αbegins␈αwith␈αits␈α
ontology.␈α The␈αontology␈αof␈α
a␈αprogram␈αis␈α
the␈αset

␈↓ α∧␈↓of entities that its variables range over.  Essentially this is what it can have information about.

␈↓ α∧␈↓␈↓ αTMYCIN's␈α∞ontology␈α
includes␈α∞bacteria,␈α
symptoms,␈α∞tests,␈α
possible␈α∞sites␈α
of␈α∞infection,␈α
antibiotics

␈↓ α∧␈↓and␈αtreatments.␈α Doctors,␈αhospitals,␈αillness␈αand␈αdeath␈αare␈αabsent.␈α Even␈αpatients␈αare␈αnot␈αreally␈αpart

␈↓ α∧␈↓of␈αthe␈αontology,␈αalthough␈αMYCIN␈αasks␈αfor␈αmany␈αfacts␈αabout␈αthe␈αspecific␈αpatient.␈α This␈αis␈αbecause

␈↓ α∧␈↓patients␈α∞aren't␈α∞values␈α∞of␈α∞variables,␈α∞and␈α∂MYCIN␈α∞never␈α∞compares␈α∞the␈α∞infections␈α∞of␈α∂two␈α∞different

␈↓ α∧␈↓patients.  It would therefore be difficult to modify MYCIN to learn from its experience.

␈↓ α∧␈↓␈↓ αTMYCIN's␈α
program,␈α
written␈α
in␈α
a␈α
general␈α
scheme␈α
called␈α
EMYCIN,␈α
is␈α
a␈α
so-called␈α␈↓↓production

␈↓ α∧␈↓↓system␈↓.␈α A␈αproduction␈αsystem␈αis␈αa␈αcollection␈αof␈αrules,␈αeach␈αof␈αwhich␈αhas␈αtwo␈αparts␈α-␈αa␈αpattern␈αpart

␈↓ α∧␈↓and␈αan␈αaction␈αpart.␈α When␈αa␈αrule␈αis␈αactivated,␈αMYCIN␈αtests␈αwhether␈αthe␈αpattern␈αpart␈αmatches␈α
the

␈↓ α∧␈↓database.␈α If␈αso␈αthis␈αresults␈αin␈αthe␈αvariables␈αin␈αthe␈αpattern␈αbeing␈αmatched␈αto␈αwhatever␈αentities␈αare

␈↓ α∧␈↓required␈αfor␈αthe␈αmatch␈α
of␈αthe␈αdatabase.␈α If␈α
not␈αthe␈αpattern␈αfails␈α
and␈αMYCIN␈αtries␈αanother.␈α If␈α
the
␈↓ α∧␈↓␈↓ u3


␈↓ α∧␈↓match␈αis␈αsuccessful,␈αthen␈αMYCIN␈αperforms␈αthe␈αaction␈αpart␈αof␈αthe␈αpattern␈αusing␈αthe␈αvalues␈αof␈αthe

␈↓ α∧␈↓variables␈α
determined␈αby␈α
the␈α
pattern␈αpart.␈α
 The␈αwhole␈α
process␈α
of␈αquestioning␈α
and␈αrecommending␈α
is

␈↓ α∧␈↓built up out of productions.

␈↓ α∧␈↓␈↓ αTThe␈α∂production␈α⊂formalism␈α∂turned␈α⊂out␈α∂to␈α⊂be␈α∂suitable␈α⊂for␈α∂representing␈α⊂a␈α∂large␈α⊂amount␈α∂of

␈↓ α∧␈↓information␈αabout␈αthe␈αdiagnosis␈α
and␈αtreatment␈αof␈αbacterial␈α
infections.␈α When␈αMYCIN␈αis␈α
used␈αin

␈↓ α∧␈↓its␈αintended␈αmanner␈αit␈αscores␈αbetter␈αthan␈αmedical␈αstudents␈αor␈αinterns␈αor␈αpracticing␈αphysicians␈αand

␈↓ α∧␈↓on␈αa␈αpar␈αwith␈αexperts␈αin␈αbacterial␈αdiseases␈αwhen␈αthe␈αlatter␈αare␈αasked␈αto␈αperform␈αin␈αthe␈αsame␈αway.

␈↓ α∧␈↓However,␈αMYCIN␈αhas␈αnot␈αbeen␈αput␈αinto␈αproduction␈αuse,␈αand␈αthe␈αreasons␈αgiven␈αby␈αexperts␈αin␈αthe

␈↓ α∧␈↓area␈α∂varied␈α∞when␈α∂I␈α∞asked␈α∂whether␈α∞it␈α∂would␈α∞be␈α∂appropriate␈α∞to␈α∂sell␈α∞MYCIN␈α∂cassettes␈α∂to␈α∞doctors

␈↓ α∧␈↓wanting␈αto␈α
put␈αit␈α
on␈αtheir␈α
micro-computers.␈α Some␈α
said␈αit␈αwould␈α
be␈αok␈α
if␈αthere␈α
were␈αa␈α
means␈αof

␈↓ α∧␈↓keeping␈α⊂MYCIN's␈α⊂database␈α⊂current␈α⊂with␈α⊂new␈α⊂discoveries␈α∂in␈α⊂the␈α⊂field,␈α⊂i.e.␈α⊂with␈α⊂new␈α⊂tests,␈α∂new

␈↓ α∧␈↓theories,␈αnew␈αdiagnoses␈αand␈αnew␈αantibiotics.␈α For␈αexample,␈αMYCIN␈αwould␈αhave␈αto␈αbe␈α
told␈αabout

␈↓ α∧␈↓Legionnaire's␈αdisease␈αand␈αthe␈αassociated␈α␈↓↓Legionnella␈↓␈αbacteria␈αwhich␈αbecame␈αunderstood␈αonly␈αafter

␈↓ α∧␈↓MYCIN␈α∃was␈α∃finished.␈α∃ (MYCIN␈α∀is␈α∃very␈α∃stubborn␈α∃about␈α∀new␈α∃bacteria,␈α∃and␈α∃simply␈α∀replies

␈↓ α∧␈↓"unrecognized response")

␈↓ α∧␈↓␈↓ αTOthers␈αsay␈α
that␈αMYCIN␈α
is␈αnot␈α
even␈αclose␈α
to␈αusable␈α
except␈αexperimentally,␈α
because␈αit␈α
doesn't

␈↓ α∧␈↓know␈αits␈αown␈αlimitations.␈α I␈αsuppose␈αthis␈αis␈α
partly␈αa␈αquestion␈αof␈αwhether␈αthe␈αdoctor␈αusing␈α
MYCIN

␈↓ α∧␈↓is␈α∞trusted␈α∂to␈α∞understand␈α∞the␈α∂documentation␈α∞about␈α∞its␈α∂limitations.␈α∞ Programmer's␈α∂always␈α∞develop

␈↓ α∧␈↓the␈α⊂idea␈α⊂that␈α⊂the␈α⊂users␈α⊂of␈α⊂their␈α⊂programs␈α⊂are␈α⊂idiots,␈α⊂so␈α⊂the␈α⊂opinion␈α⊂that␈α⊂doctors␈α⊃aren't␈α⊂smart

␈↓ α∧␈↓enough␈α∂not␈α∞to␈α∂be␈α∂misled␈α∞by␈α∂MYCIN's␈α∂limitations␈α∞may␈α∂be␈α∞at␈α∂least␈α∂partly␈α∞a␈α∂consequence␈α∂of␈α∞this

␈↓ α∧␈↓ideology.

␈↓ α∧␈↓␈↓ αTAn␈αexample␈αof␈αMYCIN␈αnot␈αknowing␈α
its␈αlimitations␈αcan␈αbe␈αexcited␈αby␈αtelling␈α
MYCIN␈αthat

␈↓ α∧␈↓the␈αpatient␈αhas␈α␈↓↓Cholerae␈αvibrio␈↓␈αin␈αhis␈αintestines.␈α MYCIN␈αwill␈αcheerfully␈αrecommend␈αtwo␈αweeks␈αof

␈↓ α∧␈↓tetracycline␈αand␈αnothing␈αelse.␈α Presumably␈αthis␈αwould␈αindeed␈αkill␈αthe␈αbacteria,␈αbut␈αmost␈αlikely␈αthe
␈↓ α∧␈↓␈↓ u4


␈↓ α∧␈↓patient␈α
will␈α
be␈α
dead␈α
of␈α
cholera␈α∞long␈α
before␈α
that.␈α
 However,␈α
the␈α
physician␈α
will␈α∞presumably␈α
know

␈↓ α∧␈↓that the diarrhea has to be treated and look elsewhere for how to do it.

␈↓ α∧␈↓␈↓ αTOn␈α
the␈αother␈α
hand␈α
it␈αmay␈α
be␈α
really␈αtrue␈α
that␈α
some␈αmeasure␈α
of␈α
common␈αsense␈α
is␈αrequired␈α
for

␈↓ α∧␈↓usefulness␈α∞even␈α∞in␈α∞this␈α∂narrow␈α∞domain.␈α∞ We'll␈α∞list␈α∞some␈α∂areas␈α∞of␈α∞common␈α∞sense␈α∂knowledge␈α∞and

␈↓ α∧␈↓reasoning␈α∃ability␈α∃and␈α∃also␈α∀apply␈α∃the␈α∃criteria␈α∃to␈α∀MYCIN␈α∃and␈α∃other␈α∃hypothetical␈α∀programs

␈↓ α∧␈↓operating in MYCIN's domain.

␈↓ α∧␈↓WHAT IS COMMON SENSE?

␈↓ α∧␈↓␈↓ αTUnderstanding␈α⊗common␈α∃sense␈α⊗capability␈α∃is␈α⊗now␈α∃a␈α⊗hot␈α∃area␈α⊗of␈α∃research␈α⊗in␈α∃artificial

␈↓ α∧␈↓intelligence,␈α
but␈α
there␈α
is␈α
not␈α
yet␈α
any␈αconsensus.␈α
 We␈α
will␈α
try␈α
to␈α
divide␈α
common␈α
sense␈αcapability␈α
into

␈↓ α∧␈↓common␈α⊃sense␈α∩knowledge␈α⊃and␈α⊃common␈α∩sense␈α⊃reasoning,␈α∩but␈α⊃even␈α⊃this␈α∩cannot␈α⊃be␈α∩made␈α⊃firm.

␈↓ α∧␈↓Namely,␈αwhat␈αone␈αman␈αbuilds␈αas␈αa␈αreasoning␈αmethod␈αinto␈αhis␈αprogram,␈αanother␈αcan␈αexpress␈αas␈αa

␈↓ α∧␈↓fact␈α
using␈αa␈α
richer␈α
ontology.␈α However,␈α
the␈α
latter␈αcan␈α
have␈αproblems␈α
in␈α
handling␈αin␈α
a␈α
good␈αway

␈↓ α∧␈↓the generality he has introduced.

␈↓ α∧␈↓COMMON SENSE KNOWLEDGE

␈↓ α∧␈↓␈↓ αTWe shall discuss various areas of common sense knowledge.

␈↓ α∧␈↓␈↓ αT1.␈α
The␈α
most␈α
salient␈α
common␈α
sense␈α
knowledge␈α
concerns␈α
situations␈α
that␈α
change␈α
in␈α
time␈α∞as␈α
a

␈↓ α∧␈↓result␈αof␈α
events.␈α The␈α
most␈αimportant␈α
events␈αare␈α
actions,␈αand␈α
for␈αa␈α
program␈αto␈α
plan␈αintelligently,␈α
it

␈↓ α∧␈↓must be able to determine the effects of its own actions.

␈↓ α∧␈↓␈↓ αTConsider␈α⊂the␈α∂MYCIN␈α⊂domain␈α∂as␈α⊂an␈α∂example.␈α⊂ The␈α∂situation␈α⊂with␈α∂which␈α⊂MYCIN␈α∂deals

␈↓ α∧␈↓includes␈αthe␈α
doctor,␈αthe␈αpatient␈α
and␈αthe␈αillness.␈α
 Since␈αMYCIN's␈αactions␈α
are␈αadvice␈αto␈α
the␈αdoctor,

␈↓ α∧␈↓full␈α
planning␈α∞would␈α
have␈α
to␈α∞include␈α
information␈α
about␈α∞the␈α
effects␈α
of␈α∞MYCIN's␈α
output␈α∞on␈α
what

␈↓ α∧␈↓the␈αdoctor␈αwill␈αdo.␈α Since␈αMYCIN␈αdoesn't␈αknow␈αabout␈αthe␈αdoctor,␈αit␈αmight␈αplan␈αthe␈αeffects␈αof␈αthe

␈↓ α∧␈↓course␈α∀of␈α∪treatment␈α∀on␈α∪the␈α∀patient.␈α∪ However,␈α∀it␈α∪doesn't␈α∀do␈α∪this␈α∀either.␈α∪ Its␈α∀rules␈α∀give␈α∪the

␈↓ α∧␈↓recommended␈α
treatment␈α
as␈α
a␈αfunction␈α
of␈α
the␈α
information␈αelicited␈α
about␈α
the␈α
patient,␈α
but␈αMYCIN
␈↓ α∧␈↓␈↓ u5


␈↓ α∧␈↓makes␈α⊂no␈α∂prognosis␈α⊂of␈α∂the␈α⊂effects␈α∂of␈α⊂the␈α∂treatment.␈α⊂ Of␈α∂course,␈α⊂the␈α∂doctors␈α⊂who␈α⊂provided␈α∂the

␈↓ α∧␈↓information built into MYCIN considered the effects of the treatments.

␈↓ α∧␈↓␈↓ αTIgnoring␈α⊂prognosis␈α∂is␈α⊂possible␈α∂because␈α⊂of␈α⊂the␈α∂specific␈α⊂narrow␈α∂domain␈α⊂in␈α⊂which␈α∂MYCIN

␈↓ α∧␈↓operates.␈α
 Suppose,␈α
for␈α∞example,␈α
a␈α
certain␈α∞antibiotic␈α
had␈α
the␈α∞precondition␈α
for␈α
its␈α∞usefulness␈α
that

␈↓ α∧␈↓the␈α
patient␈α∞not␈α
have␈α
a␈α∞fever.␈α
 Then␈α
MYCIN␈α∞might␈α
have␈α
to␈α∞make␈α
a␈α
plan␈α∞for␈α
getting␈α
rid␈α∞of␈α
the

␈↓ α∧␈↓patient's␈α
fever␈α
and␈α
verifying␈α
that␈α∞it␈α
was␈α
gone␈α
as␈α
a␈α
part␈α∞of␈α
the␈α
plan␈α
for␈α
using␈α
the␈α∞antibiotic.␈α
 In

␈↓ α∧␈↓other␈α
domains,␈α
expert␈α
systems␈αand␈α
other␈α
AI␈α
programs␈α
have␈αto␈α
make␈α
plans,␈α
but␈α
MYCIN␈αdoesn't.

␈↓ α∧␈↓Perhaps␈αif␈αI␈αknew␈αmore␈αabout␈αbacterial␈αdiseases,␈αI␈αwould␈αconclude␈αthat␈αtheir␈αtreatment␈αsometimes

␈↓ α∧␈↓really does require planning and that lack of planning ability limits MYCIN's utility.

␈↓ α∧␈↓␈↓ αTThe␈α⊃fact␈α⊃that␈α⊃MYCIN␈α⊃doesn't␈α⊃give␈α⊂a␈α⊃prognosis␈α⊃is␈α⊃certainly␈α⊃a␈α⊃limitation.␈α⊃ For␈α⊂example,

␈↓ α∧␈↓MYCIN␈αcannot␈αbe␈αasked␈αon␈αbehalf␈αof␈αthe␈αpatient␈αor␈αthe␈αadministration␈αof␈αthe␈αhospital␈αwhen␈αthe

␈↓ α∧␈↓patient␈αis␈αlikely␈αto␈αbe␈αready␈αto␈αgo␈αhome.␈α The␈αdoctor␈αwho␈αuses␈αMYCIN␈αmust␈αdo␈αthat␈αpart␈αof␈αthe

␈↓ α∧␈↓work␈α
himself.␈α
 Moreover,␈α
MYCIN␈α
cannot␈α
answer␈α
a␈α
question␈α
about␈α
a␈α
hypothetical␈α∞treatment,␈α
e.g.

␈↓ α∧␈↓"What␈αwill␈αhappen␈αif␈αI␈αgive␈αthis␈αpatient␈αpenicillin?"␈αor␈αeven␈α"What␈αbad␈αthings␈αmight␈αhappen␈αif␈αI

␈↓ α∧␈↓give this patient penicillin?".

␈↓ α∧␈↓␈↓ αT2.␈α⊂Various␈α⊂formalisms␈α⊂are␈α⊂used␈α⊂in␈α⊂artificial␈α⊂intelligence␈α⊂for␈α⊂representing␈α⊂facts␈α⊂about␈α⊂the

␈↓ α∧␈↓effects␈αof␈αactions␈αand␈αother␈αevents.␈α However,␈αall␈αsystems␈αthat␈αI␈αknow␈αabout␈αgive␈αthe␈αeffects␈αof␈αan

␈↓ α∧␈↓event␈α⊂in␈α⊂a␈α⊂situation␈α⊂by␈α⊂describing␈α⊂a␈α⊂new␈α∂situation␈α⊂that␈α⊂results␈α⊂from␈α⊂the␈α⊂event.␈α⊂ This␈α⊂is␈α∂often

␈↓ α∧␈↓enough,␈αbut␈αit␈αdoesn't␈αcover␈αthe␈αimportant␈αcase␈αof␈αconcurrent␈αevents␈αand␈αactions.␈α For␈αexample,␈αif

␈↓ α∧␈↓a␈α⊃patient␈α⊃has␈α∩cholera,␈α⊃while␈α⊃the␈α⊃antibiotic␈α∩is␈α⊃killing␈α⊃the␈α⊃cholera␈α∩bacteria,␈α⊃the␈α⊃damage␈α∩to␈α⊃his

␈↓ α∧␈↓intestines␈α⊂is␈α∂causing␈α⊂loss␈α∂of␈α⊂fluids␈α∂that␈α⊂are␈α⊂likely␈α∂to␈α⊂be␈α∂fatal.␈α⊂ Inventing␈α∂a␈α⊂formalism␈α⊂that␈α∂will

␈↓ α∧␈↓conveniently␈α∀express␈α∀people's␈α∪common␈α∀sense␈α∀knowledge␈α∀about␈α∪concurrent␈α∀events␈α∀is␈α∀a␈α∪major

␈↓ α∧␈↓unsolved problem of AI.

␈↓ α∧␈↓␈↓ αT3.␈α∞The␈α∞world␈α∞is␈α∞extended␈α
in␈α∞space␈α∞and␈α∞is␈α∞occupied␈α
by␈α∞objects␈α∞that␈α∞change␈α∞their␈α
positions
␈↓ α∧␈↓␈↓ u6


␈↓ α∧␈↓and␈α∂are␈α∂sometimes␈α⊂created␈α∂and␈α∂destroyed.␈α⊂ The␈α∂common␈α∂sense␈α∂facts␈α⊂about␈α∂this␈α∂are␈α⊂difficult␈α∂to

␈↓ α∧␈↓express␈α∪but␈α∩are␈α∪probably␈α∩not␈α∪important␈α∩in␈α∪the␈α∩MYCIN␈α∪example.␈α∩ A␈α∪major␈α∩difficulty␈α∪is␈α∩in

␈↓ α∧␈↓handling␈α
the␈αkind␈α
of␈αpartial␈α
knowledge␈αpeople␈α
ordinarily␈αhave.␈α
 I␈αcan␈α
see␈αpart␈α
of␈αthe␈α
front␈α
of␈αa

␈↓ α∧␈↓person␈αin␈α
the␈αaudience,␈αand␈α
my␈αidea␈α
of␈αhis␈αshape␈α
uses␈αthis␈αinformation␈α
to␈αapproximate␈α
his␈αtotal

␈↓ α∧␈↓shape.␈α∞ Thus␈α∂I␈α∞don't␈α∂expect␈α∞him␈α∞to␈α∂stick␈α∞out␈α∂two␈α∞feet␈α∂in␈α∞back␈α∞even␈α∂though␈α∞I␈α∂can't␈α∞see␈α∂that␈α∞he

␈↓ α∧␈↓doesn't.␈α
 However,␈α
my␈αidea␈α
of␈α
the␈α
shape␈αof␈α
his␈α
back␈α
is␈αless␈α
definite␈α
than␈α
that␈αof␈α
the␈α
parts␈α
I␈αcan

␈↓ α∧␈↓see.

␈↓ α∧␈↓␈↓ αT4.␈α∩The␈α∩ability␈α∩to␈α∪represent␈α∩and␈α∩use␈α∩knowledge␈α∪about␈α∩knowledge␈α∩is␈α∩often␈α∪required␈α∩for

␈↓ α∧␈↓intelligent␈α
behavior.␈α∞ What␈α
airline␈α∞flights␈α
there␈α
are␈α∞to␈α
Singapore␈α∞is␈α
recorded␈α
in␈α∞the␈α
issue␈α∞of␈α
the

␈↓ α∧␈↓International␈α
Airline␈α
Guide␈αcurrent␈α
for␈α
the␈αproposed␈α
flight␈α
day.␈α
 Travel␈αagents␈α
know␈α
how␈αto␈α
book

␈↓ α∧␈↓airline␈αflights␈αand␈αcan␈αcompute␈αwhat␈αthey␈αcost.␈α An␈αadvanced␈αMYCIN␈αmight␈αneed␈αto␈αreason␈αthat

␈↓ α∧␈↓Dr. Smith knows about cholera, because he is a specialist in tropical medicine.

␈↓ α∧␈↓␈↓ αT5.␈αA␈αprogram␈αthat␈αmust␈αco-operate␈αor␈αcompete␈αwith␈αpeople␈αor␈αother␈αprograms␈αmust␈αbe␈αable

␈↓ α∧␈↓to␈α∞represent␈α∂information␈α∞about␈α∞their␈α∂knowledge,␈α∞beliefs,␈α∞goals,␈α∂likes␈α∞and␈α∞dislikes,␈α∂intentions␈α∞and

␈↓ α∧␈↓abilities.␈α⊂ An␈α⊂advanced␈α⊂MYCIN␈α⊂might␈α⊂need␈α⊂to␈α⊂know␈α⊂that␈α⊂a␈α⊂patient␈α⊂won't␈α⊂take␈α⊂a␈α⊂bad␈α∂tasting

␈↓ α∧␈↓medicine unless he is convinced of its necessity.

␈↓ α∧␈↓␈↓ αT6.␈α∩Common␈α∪sense␈α∩includes␈α∪much␈α∩knowledge␈α∩whose␈α∪domain␈α∩overlaps␈α∪that␈α∩of␈α∪the␈α∩exact

␈↓ α∧␈↓sciences␈α∂but␈α∞differs␈α∂from␈α∂it␈α∞epistemologically.␈α∂ For␈α∂example,␈α∞if␈α∂I␈α∞spill␈α∂the␈α∂glass␈α∞of␈α∂water␈α∂on␈α∞the

␈↓ α∧␈↓podium,␈αeveryone␈α
knows␈αthat␈αthe␈α
glass␈αwill␈αbreak␈α
and␈αthe␈αwater␈α
will␈αspill.␈α Everyone␈α
knows␈αthat

␈↓ α∧␈↓this␈α
will␈α
take␈α
a␈α
fraction␈α
of␈α
a␈α
second␈α
and␈α
that␈α
the␈α
water␈α
will␈α
not␈α
splash␈α
even␈α
ten␈α
feet.␈α However,

␈↓ α∧␈↓this␈α∞information␈α∞is␈α∂not␈α∞obtained␈α∞by␈α∞using␈α∂the␈α∞formula␈α∞for␈α∞a␈α∂falling␈α∞body␈α∞or␈α∂the␈α∞Navier-Stokes

␈↓ α∧␈↓equations␈αgoverning␈αfluid␈αflow.␈α We␈αdon't␈αhave␈αthe␈α
input␈αdata␈αfor␈αthe␈αequations,␈αmost␈αof␈αus␈α
don't

␈↓ α∧␈↓know␈α
them,␈α
and␈αwe␈α
couldn't␈α
integrate␈αthem␈α
fast␈α
enough␈α
to␈αdecide␈α
whether␈α
to␈αjump␈α
out␈α
of␈αthe␈α
way.

␈↓ α∧␈↓This␈α⊃common␈α⊃sense␈α⊃physics␈α⊃is␈α⊃contiguous␈α⊃with␈α⊃scientific␈α⊃physics.␈α⊃ In␈α⊃fact␈α⊃scientific␈α∩physics␈α⊃is
␈↓ α∧␈↓␈↓ u7


␈↓ α∧␈↓imbedded␈α∂in␈α∂common␈α∂sense␈α∂physics,␈α∂because␈α∂it␈α∂is␈α∂common␈α∂sense␈α∂physics␈α∂that␈α∂tells␈α∂us␈α⊂what␈α∂the

␈↓ α∧␈↓equation

␈↓ α∧␈↓␈↓ αT␈↓↓s = 1/2 g t␈↓∧2␈↓

␈↓ α∧␈↓means.␈α If␈αMYCIN␈α
were␈αextended␈αto␈αbe␈α
a␈αrobot␈αphysician␈αit␈α
would␈αhave␈αto␈αknow␈α
common␈αsense

␈↓ α∧␈↓physics and maybe also some scientific physics.

␈↓ α∧␈↓␈↓ αTIt␈α
is␈α
doubtful␈α∞that␈α
the␈α
facts␈α
of␈α∞the␈α
common␈α
sense␈α
world␈α∞can␈α
be␈α
represented␈α∞adequately␈α
by

␈↓ α∧␈↓production␈αrules.␈α Consider␈αthe␈αfact␈αthat␈αwhen␈αtwo␈αobjects␈αcollide␈αthey␈αoften␈αmake␈αa␈α
noise.␈α This

␈↓ α∧␈↓fact␈α
can␈α
be␈α
used␈α
to␈α
make␈αa␈α
noise,␈α
to␈α
avoid␈α
making␈α
a␈α
noise,␈αto␈α
explain␈α
a␈α
noise␈α
or␈α
to␈α
explain␈αthe

␈↓ α∧␈↓absence␈α⊃of␈α∩a␈α⊃noise.␈α∩ It␈α⊃can␈α∩also␈α⊃be␈α∩used␈α⊃in␈α∩specific␈α⊃situations␈α∩involving␈α⊃a␈α∩noise␈α⊃but␈α∩also␈α⊃to

␈↓ α∧␈↓understand␈α∞general␈α∞phenomena,␈α
e.g.␈α∞should␈α∞an␈α∞intruder␈α
step␈α∞on␈α∞the␈α∞gravel,␈α
the␈α∞dog␈α∞will␈α∞hear␈α
it

␈↓ α∧␈↓and␈αbark.␈α A␈αproduction␈αrule␈αembodies␈αa␈αfact␈α
only␈αas␈αpart␈αof␈αa␈αspecific␈αprocedure.␈α Typically␈α
they

␈↓ α∧␈↓match␈αfacts␈α
about␈αspecific␈α
objects,␈αe.g.␈α
a␈αspecific␈αbacterium,␈α
against␈αa␈α
general␈αrule␈α
and␈αget␈α
a␈αnew

␈↓ α∧␈↓fact about those objects.

␈↓ α∧␈↓␈↓ αTMuch␈α
present␈αAI␈α
research␈α
concerns␈αhow␈α
to␈αrepresent␈α
facts␈α
in␈αways␈α
that␈αpermit␈α
them␈α
to␈αbe

␈↓ α∧␈↓used for a wide variety of purposes.

␈↓ α∧␈↓COMMON SENSE REASONING

␈↓ α∧␈↓␈↓ αTOur␈α∂ability␈α∞to␈α∂use␈α∞common␈α∂sense␈α∞knowledge␈α∂depends␈α∞on␈α∂being␈α∞able␈α∂to␈α∞do␈α∂common␈α∞sense

␈↓ α∧␈↓reasoning.

␈↓ α∧␈↓␈↓ αTMuch␈αartificial␈αintelligence␈αinference␈αis␈αnot␈αdesigned␈αto␈αuse␈αdirectly␈αthe␈αrules␈αof␈αinference␈α
of

␈↓ α∧␈↓any␈α
of␈α
the␈α∞well␈α
known␈α
systems␈α
of␈α∞mathematical␈α
logic.␈α
 There␈α
is␈α∞often␈α
no␈α
clear␈α
separation␈α∞in␈α
the

␈↓ α∧␈↓program␈α∀between␈α∀determining␈α∪what␈α∀inferences␈α∀are␈α∪correct␈α∀and␈α∀the␈α∪strategy␈α∀for␈α∀finding␈α∪the

␈↓ α∧␈↓inferences␈α∀required␈α∀to␈α∀solve␈α∀the␈α∀problem␈α∀at␈α∀hand.␈α∀ Nevertheless,␈α∀the␈α∀logical␈α∀system␈α∪usually

␈↓ α∧␈↓corresponds␈αto␈αa␈αsubset␈αof␈αfirst␈αorder␈αlogic.␈α
 Systems␈αprovide␈αfor␈αinferring␈αa␈αfact␈αabout␈αone␈αor␈α
two

␈↓ α∧␈↓particular␈α∂objects␈α∞from␈α∂other␈α∞facts␈α∂about␈α∞these␈α∂objects␈α∞and␈α∂a␈α∞general␈α∂rule␈α∂containing␈α∞variables.

␈↓ α∧␈↓Most expert systems, including MYCIN, never infer general statements, i.e. quantified formulas.
␈↓ α∧␈↓␈↓ u8


␈↓ α∧␈↓␈↓ αTHuman␈αreasoning␈αalso␈α
involves␈αobtaining␈αfacts␈αby␈α
observation␈αof␈αthe␈αworld,␈α
and␈αcomputer

␈↓ α∧␈↓programs␈α
also␈α
do␈α
this.␈α
 Robert␈α
Filman␈α
did␈α
an␈α
interesting␈α
thesis␈α
on␈α
observation␈α
in␈α
a␈α
chess␈α
world

␈↓ α∧␈↓where␈α⊃many␈α∩facts␈α⊃that␈α∩could␈α⊃be␈α∩obtained␈α⊃by␈α⊃deduction␈α∩are␈α⊃in␈α∩fact␈α⊃obtained␈α∩by␈α⊃observation.

␈↓ α∧␈↓MYCIN's␈α∃doesn't␈α⊗require␈α∃this,␈α⊗but␈α∃our␈α∃hypothetical␈α⊗robot␈α∃physician␈α⊗would␈α∃have␈α⊗to␈α∃draw

␈↓ α∧␈↓conclusions from a patient's appearance, and computer vision is not ready for it.

␈↓ α∧␈↓␈↓ αTAn␈αimportant␈αnew␈αdevelopment␈αin␈αAI␈α(since␈αthe␈αmiddle␈α1970s)␈αis␈αthe␈αformalization␈αof␈αnon-

␈↓ α∧␈↓monotonic reasoning.

␈↓ α∧␈↓␈↓ αTDeductive␈αreasoning␈αin␈αmathematical␈αlogic␈αhas␈αthe␈αfollowing␈αproperty␈α-␈αcalled␈αmonotonicity

␈↓ α∧␈↓by␈α⊃analogy␈α⊂with␈α⊃similar␈α⊃mathematical␈α⊂concepts.␈α⊃ Suppose␈α⊂we␈α⊃have␈α⊃a␈α⊂set␈α⊃of␈α⊃assumptions␈α⊂from

␈↓ α∧␈↓which␈α∞follow␈α∞certain␈α∞conclusions.␈α∞ Now␈α∞suppose␈α∞we␈α∞add␈α∞additional␈α∞assumptions.␈α∞ There␈α∞may␈α∞be

␈↓ α∧␈↓some␈α∩new␈α∪conclusions,␈α∩but␈α∩every␈α∪sentence␈α∩that␈α∪was␈α∩a␈α∩deductive␈α∪consequence␈α∩of␈α∪the␈α∩original

␈↓ α∧␈↓hypotheses is still a consequence of the enlarged set.

␈↓ α∧␈↓␈↓ αTOrdinary␈αhuman␈α
reasoning␈αdoes␈αnot␈α
share␈αthis␈α
monotonicity␈αproperty.␈α If␈α
you␈αknow␈α
that␈αI

␈↓ α∧␈↓have␈αa␈αcar,␈αyou␈αmay␈αconclude␈αthat␈αit␈αis␈αa␈αgood␈αidea␈αto␈αask␈αme␈αfor␈αa␈αride.␈α If␈αyou␈αthen␈αlearn␈αthat

␈↓ α∧␈↓my␈αcar␈αis␈αbeing␈αfixed␈α(which␈αdoes␈αnot␈αcontradict␈αwhat␈αyou␈αknew␈αbefore),␈αyou␈αno␈α
longer␈αconclude

␈↓ α∧␈↓that␈α
you␈α
can␈α
get␈α∞a␈α
ride.␈α
 If␈α
you␈α∞now␈α
learn␈α
that␈α
the␈α∞car␈α
will␈α
be␈α
out␈α∞in␈α
half␈α
an␈α
hour␈α∞you␈α
reverse

␈↓ α∧␈↓yourself again.

␈↓ α∧␈↓␈↓ αTSeveral␈α
artificial␈α
intelligence␈αresearchers,␈α
for␈α
example␈αMarvin␈α
Minsky␈α
(1974)␈α
have␈αpointed

␈↓ α∧␈↓out␈α∞that␈α∞intelligent␈α
computer␈α∞programs␈α∞will␈α∞have␈α
to␈α∞reason␈α∞non-monotonically.␈α∞ Some␈α
concluded

␈↓ α∧␈↓that therefore logic is not an appropriate formalism.

␈↓ α∧␈↓␈↓ αTHowever,␈α∞it␈α
has␈α∞turned␈α
out␈α∞that␈α
deduction␈α∞in␈α
mathematical␈α∞logic␈α
can␈α∞be␈α∞supplemented␈α
by

␈↓ α∧␈↓additional␈αmodes␈αof␈αnon-monotonic␈αreasoning,␈αwhich␈αare␈αjust␈αas␈αformal␈αas␈αdeduction␈αand␈αjust␈αas

␈↓ α∧␈↓susceptible␈α∀to␈α∪mathematical␈α∀study␈α∀and␈α∪computer␈α∀implementation.␈α∀ Formalized␈α∪non-monotonic

␈↓ α∧␈↓reasoning␈α⊃turns␈α⊂out␈α⊃to␈α⊃give␈α⊂certain␈α⊃rules␈α⊂of␈α⊃conjecture␈α⊃rather␈α⊂than␈α⊃rules␈α⊂of␈α⊃inference␈α⊃-␈α⊂their
␈↓ α∧␈↓␈↓ u9


␈↓ α∧␈↓conclusion␈α∞are␈α∞appropriate,␈α∞but␈α∞may␈α∞be␈α∂disconfirmed␈α∞when␈α∞more␈α∞facts␈α∞are␈α∞obtained.␈α∂ One␈α∞such

␈↓ α∧␈↓method is ␈↓↓circumscription␈↓, described in (McCarthy 1980).

␈↓ α∧␈↓␈↓ αTA␈α
mathematical␈α∞description␈α
of␈α
circumscription␈α∞is␈α
beyond␈α∞the␈α
scope␈α
of␈α∞this␈α
lecture,␈α∞but␈α
the

␈↓ α∧␈↓general␈αidea␈αis␈αstraightforward.␈α
 We␈αhave␈αa␈αproperty␈αapplicable␈α
to␈αobjects␈αor␈αa␈αrelation␈α
applicable

␈↓ α∧␈↓to␈α∂pairs␈α∂or␈α⊂triplets,␈α∂etc.␈α∂of␈α∂objects.␈α⊂ This␈α∂property␈α∂or␈α∂relation␈α⊂is␈α∂constrained␈α∂by␈α⊂some␈α∂sentences

␈↓ α∧␈↓taken␈αas␈αassumptions,␈αbut␈αthere␈αis␈αstill␈αsome␈αfreedom␈αleft.␈α Circumscription␈αfurther␈α
constrains␈αthe

␈↓ α∧␈↓property or relation by requiring it to be true of a minimal set of objects.

␈↓ α∧␈↓␈↓ αTAs␈α∩an␈α∩example,␈α∩consider␈α∩representing␈α∩the␈α∪facts␈α∩about␈α∩whether␈α∩an␈α∩object␈α∩can␈α∩fly␈α∪in␈α∩a

␈↓ α∧␈↓database␈α∩of␈α∩common␈α∩sense␈α∩knowledge.␈α∩ We␈α⊃could␈α∩try␈α∩to␈α∩provide␈α∩axioms␈α∩that␈α∩will␈α⊃determine

␈↓ α∧␈↓whether␈α~each␈α~kind␈α→of␈α~object␈α~can␈α~fly,␈α→but␈α~this␈α~would␈α→make␈α~the␈α~database␈α~very␈α→large.

␈↓ α∧␈↓Circumscription␈α∂allows␈α∂us␈α∂to␈α∂express␈α∂the␈α⊂assumption␈α∂that␈α∂only␈α∂those␈α∂objects␈α∂can␈α∂fly␈α⊂for␈α∂which

␈↓ α∧␈↓there␈α⊂is␈α⊃a␈α⊂positive␈α⊃statement␈α⊂about␈α⊂it.␈α⊃ Thus␈α⊂there␈α⊃will␈α⊂be␈α⊂positive␈α⊃statements␈α⊂that␈α⊃birds␈α⊂and

␈↓ α∧␈↓airplanes␈αcan␈αfly␈α
and␈αno␈αstatement␈α
that␈αcamels␈αcan␈α
fly.␈α Since␈αwe␈α
don't␈αinclude␈αnegative␈α
statements

␈↓ α∧␈↓in␈α⊂the␈α⊂database,␈α⊃we␈α⊂could␈α⊂provide␈α⊂for␈α⊃flying␈α⊂camels,␈α⊂if␈α⊂there␈α⊃were␈α⊂any,␈α⊂by␈α⊃adding␈α⊂statements

␈↓ α∧␈↓without␈αremoving␈αexisting␈αstatements.␈α This␈αmuch␈αis␈αoften␈αdone␈αby␈αa␈αsimpler␈αmethod␈α-␈αthe␈α␈↓↓closed

␈↓ α∧␈↓↓world␈αassumption␈↓␈αdiscussed␈αby␈αRaymond␈αReiter.␈α However,␈αwe␈αalso␈αhave␈αexceptions␈αto␈αthe␈α
general

␈↓ α∧␈↓statement␈α∂that␈α∂birds␈α⊂can␈α∂fly.␈α∂ For␈α⊂example,␈α∂penguins,␈α∂ostriches␈α⊂and␈α∂birds␈α∂with␈α⊂certain␈α∂feathers

␈↓ α∧␈↓removed␈α∀can't␈α∃fly.␈α∀ Moreover,␈α∃more␈α∀exceptions␈α∃may␈α∀be␈α∃found␈α∀and␈α∃even␈α∀exceptions␈α∃to␈α∀the

␈↓ α∧␈↓exceptions.␈α∃ Circumscription␈α⊗allows␈α∃us␈α∃to␈α⊗make␈α∃the␈α∃known␈α⊗exceptions␈α∃and␈α∃to␈α⊗provide␈α∃for

␈↓ α∧␈↓additional exceptions to be added later - again without changing existing statements.

␈↓ α∧␈↓␈↓ αTNon-monotonic␈α
reasoning␈αalso␈α
seems␈α
to␈αbe␈α
involved␈α
in␈αhuman␈α
communication.␈α
 Suppose␈αI

␈↓ α∧␈↓hire␈α∞you␈α∂to␈α∞build␈α∞me␈α∂a␈α∞bird␈α∂cage,␈α∞and␈α∞you␈α∂build␈α∞it␈α∞without␈α∂a␈α∞top,␈α∂and␈α∞I␈α∞refuse␈α∂to␈α∞pay␈α∂on␈α∞the

␈↓ α∧␈↓grounds␈α
that␈α
my␈α
bird␈α
might␈α
fly␈α
away.␈α
 A␈α
judge␈α
will␈α
side␈α
with␈α
me.␈α
 On␈α
the␈α
other␈α∞hand␈α
suppose

␈↓ α∧␈↓you␈αbuild␈αit␈αwith␈αa␈αtop,␈αand␈αI␈αrefuse␈αto␈αpay␈αfull␈αprice␈αon␈αthe␈αgrounds␈αthat␈αmy␈αbird␈αis␈αa␈αpenguin,
␈↓ α∧␈↓␈↓ f10


␈↓ α∧␈↓and␈αthe␈αtop␈αis␈αa␈αwaste.␈α Unless␈αI␈αtold␈αyou␈αthat␈αmy␈αbird␈αcouldn't␈αfly,␈αthe␈αjudge␈αwill␈αside␈αwith␈αyou.

␈↓ α∧␈↓We␈αcan␈α
therefore␈αregard␈αit␈α
as␈αa␈α
communication␈αconvention␈αthat␈α
if␈αa␈α
bird␈αcan␈αfly␈α
the␈αfact␈αneed␈α
not

␈↓ α∧␈↓be mentioned, but if the bird can't fly and it is relevant, then the fact must be mentioned.
␈↓ α∧␈↓␈↓ f11


␈↓ α∧␈↓References:

␈↓ α∧␈↓␈↓αDavis,␈α⊗Randall;␈α∃Buchanan,␈α⊗Bruce;␈α⊗and␈α∃Shortliffe,␈α⊗Edward␈α⊗(1977)␈↓:␈α∃"Production␈α⊗Rules␈α⊗as␈α∃a
␈↓ α∧␈↓Representation␈α
for␈α
a␈αKnowledge-Based␈α
Consultation␈α
Program,"␈α␈↓↓Artificial␈α
Intelligence␈↓,␈α
Volume␈α8,
␈↓ α∧␈↓Number 1, February.

␈↓ α∧␈↓␈↓αMcCarthy,␈α↔John␈α↔(1960)␈↓:␈α↔"Programs␈α↔with␈α↔Common␈α↔Sense,"␈α↔Proceedings␈α↔of␈α↔the␈α↔Teddington
␈↓ α∧␈↓Conference on the Mechanization of Thought Processes, Her Majesty's Stationery Office, London.

␈↓ α∧␈↓␈↓αMcCarthy,␈α∂John␈α∂and␈α∞P.J.␈α∂Hayes␈α∂(1969)␈↓:␈α∞"Some␈α∂Philosophical␈α∂Problems␈α∞from␈α∂the␈α∂Standpoint␈α∞of
␈↓ α∧␈↓Artificial␈α
Intelligence",␈α∞in␈α
D.␈α
Michie␈α∞(ed),␈α
␈↓↓Machine␈α
Intelligence␈α∞4␈↓,␈α
American␈α
Elsevier,␈α∞New␈α
York,
␈↓ α∧␈↓NY.

␈↓ α∧␈↓␈↓αMcCarthy,␈α⊃John␈α⊃(1980)␈↓:␈α⊃"Circumscription␈α∩-␈α⊃A␈α⊃Form␈α⊃of␈α⊃Non-Monotonic␈α∩Reasoning",␈α⊃␈↓↓Artificial
␈↓ α∧␈↓↓Intelligence␈↓, Volume 13, Numbers 1,2, April.

␈↓ α∧␈↓␈↓αMinsky, Marvin (1974)␈↓: "A Framework for Representing Knowledge", ␈↓↓M.I.T. AI Memo 252␈↓.

␈↓ α∧␈↓␈↓αShortliffe,␈α_Edward␈α↔H.␈α_(1976)␈↓:␈α_Computer-Based␈α↔Medical␈α_Consultations:␈α_MYCIN,␈α↔American
␈↓ α∧␈↓Elsevier, New York, NY.