Computational Intelligence - May 2013 - 74
Notice that, while believing in U bt slightly adds to context
preference due to likeability, believing in JU bt adds necessarily
more because it consists of an absolute certainty. As explained in
Section V-B, likeability is one of the aspects that contributes to
the less significative preference (a value in @ 0, 1 6), while an absolute certainty conveys a preference of 1. This is why the preference of {JU bt, U al, U 17} is almost 1 unit above the preference of
{U bt, U al, U 17} . The same phenomenon occurs in all the following scenarios, preventing contexts that contain U bt bt to be
believed (which is natural, since JU bt is an absolute certainty).
Consequently, the believed context is b c = {JU bt, U al, U 17},
and the resulting belief space is BS ( b c, ag) = {JU bt, U al, U 17} .
Let us focus on what changed in the agent's beliefs, in relation to the previous scenario. Now the agent has two new
beliefs: That she does not have a boat and that her mother
boarded flight 17. We look at the certainty (i.e. causal strength)
of these two beliefs, to conclude whether or not they are
beliefs for the purpose of answer:
❏ CauStr (JU bt, b c, ag) = 1. So, Jhave(Boat) is an absolute certainty and, obviously, a belief for the purposes of answer
(since 1 $ 0.2).
❏ CauStr (U bt, b c, ag) = 0.5. So, inFlight(Mother, 17) is a belief
of intermediate strength and a belief for the purposes of
answer (since 0.5 $ 0.2).
So, regarding these two beliefs, the agent answers that she
does not have a boat and that her mother boarded flight 17. In
other words, the agent believes her observation and David's
communication, and the strength of these beliefs is far greater
than that of the belief of having a boat in the previous scenario.
3) Scenario 3
Continuing from the previous scenario, the agent now watches
a news report, announcing that flight number 17 crashed, leaving no survivors. The agent quickly concludes that this information, combined with what David has told her ( U 17 ), imply
that her mother has died. Assume that Reporter is the agent who
communicated the crash, who our agent (ag) finds quite credible, more specifically, Cred(ag, Reporter) = 0.8. We represent
(part of) the news report about the plane crash as:
❏ U cr = 6 (x) inFlight (x, 17) " Jalive(x) .
We consider that the agent's knowledge base contains a derivation support, JU al, Der, {U 17, U cr } , because the agent was
able to conclude that " U 17, U cr , , = FOL JU al .
Now there is a second inconsistency in b 0 , c 0 because U 17
and U cr imply believing in JU al (hence, are inconsistent with U al ).
As a result, there are six candidate contexts, Cand (b 0, c 0, ag) =
{{U bt, U al, U 17}, {U bt, U al, U cr }, {U bt, U 17, U cr }, {JU bt, U al, U 17},
" JU bt, U al, U cr ,, " JU bt, U 17, U cr ,, with the following values of
preference:
❏ CtxPrf ({U bt, U al, U 17}, ag) - 0.775
❏ CtxPrf ({U bt, U al, U cr }, ag) - 0.811
❏ CtxPrf ({U bt, U 17, U cr }, ag) - 0.808
❏ CtxPrf ({JU bt, U al, U 17}, ag) - 1.749
❏ CtxPrf ({JU bt, U al, U cr }, ag) - 1.793
❏ CtxPrf ({JU bt, U 17, U cr }, ag) - 1.790.
74
IEEE ComputatIonal IntEllIgEnCE magazInE | may 2013
Consequently, the believed context is b c = {JU bt, U al, U cr },
and the resulting belief space is BS ( b c, ag) = {JU bt, U al, U cr } .
Notice that the agent does not believe her mother
boarded flight 17 and, instead, believes that her mother is
alive, despite having no evidence to support it (active effects
of wishful thinking). The agent is in denial concerning her
mother's death, mainly due to the very high goal importance
of having her mother alive (0.95) and to the low credibility
of David (who communicated U 17 ). Notice that denial was
achieved simply by rejecting belief in the "weakest link,"
namely David's communication, U 17 (instead of the news
report, U cr , that has a higher causal strength). Note, however,
that the personality of the agent (more concretely, the agent's
wishful thinking coefficient) is also responsible for
this denial.
4) Scenario 4
We now suppose that another agent, Bruno, tells ag that her
mother boarded flight 17. Our agent considers Bruno quite
credible, more specifically, Cred(ag, Bruno) = 0.8.
The candidate contexts are, as expected, the same as those
in Scenario 3, but with different values of preference:
❏ CtxPrf ({U bt, U al, U 17}, ag) - 0.820
❏ CtxPrf ({U bt, U al, U cr }, ag) - 0.811
❏ CtxPrf ({U bt, U 17, U cr }, ag) - 0.833
❏ CtxPrf ({JU bt, U al, U 17}, ag) - 1.804
❏ CtxPrf ({JU bt, U al, U cr }, ag) - 1.793
❏ CtxPrf ({JU bt, U 17, U cr }, ag) - 1.819.
Consequently, the believed context is b c = {JU bt, U 17,
U cr }, and the resulting belief space is BS ( b c, ag) = {JU bt,
U 17, U cr , JU al} .
As explained in Scenario 3, one of the reasons why the
agent was able to be in denial was that David has a low credibility and his communication was the only support for U 17 .
This was the easiest way that the agent could deny her mother's
death, that is, by rejecting the fact that she (her mother)
boarded flight 17. In this scenario, this fact is no longer easy to
reject (the causal strength of U 17 increased from 0.5 to 0.9)
because there is a second agent, Bruno, claiming that it is true
and, moreover, he is considered quite credible. Consequently,
our agent (ag) is no longer in denial, as shown above. If Bruno
would have communicated, for example, U cr instead of U 17 ,
denial would still occur because the agent would still be able to
easily reject U 17 .
5) Scenario 5
Continuing from the previous scenario, we now suppose that
agent Susan tells ag that her (ag's) mother did not board flight
17. The credibility that our agent attributes to Susan is 0.6 (in
other words, Cred(ag, Susan) = 0.6).
Now, the six candidate contexts must take into account
the new hypothesis (JU 17) , hence, Cand(b 0, c 0, ag) =
{{U bt, U al, U 17}, {U bt, U al, JU 17, U cr }, {U bt, U 17, U cr }, {JU bt, U al,
U 17}, {JU bt, U al, JU 17, U cr }, {JU bt, U 17, U cr }} . The preference
for each of these contexts is:
Table of Contents for the Digital Edition of Computational Intelligence - May 2013
Computational Intelligence - May 2013 - Cover1
Computational Intelligence - May 2013 - Cover2
Computational Intelligence - May 2013 - 1
Computational Intelligence - May 2013 - 2
Computational Intelligence - May 2013 - 3
Computational Intelligence - May 2013 - 4
Computational Intelligence - May 2013 - 5
Computational Intelligence - May 2013 - 6
Computational Intelligence - May 2013 - 7
Computational Intelligence - May 2013 - 8
Computational Intelligence - May 2013 - 9
Computational Intelligence - May 2013 - 10
Computational Intelligence - May 2013 - 11
Computational Intelligence - May 2013 - 12
Computational Intelligence - May 2013 - 13
Computational Intelligence - May 2013 - 14
Computational Intelligence - May 2013 - 15
Computational Intelligence - May 2013 - 16
Computational Intelligence - May 2013 - 17
Computational Intelligence - May 2013 - 18
Computational Intelligence - May 2013 - 19
Computational Intelligence - May 2013 - 20
Computational Intelligence - May 2013 - 21
Computational Intelligence - May 2013 - 22
Computational Intelligence - May 2013 - 23
Computational Intelligence - May 2013 - 24
Computational Intelligence - May 2013 - 25
Computational Intelligence - May 2013 - 26
Computational Intelligence - May 2013 - 27
Computational Intelligence - May 2013 - 28
Computational Intelligence - May 2013 - 29
Computational Intelligence - May 2013 - 30
Computational Intelligence - May 2013 - 31
Computational Intelligence - May 2013 - 32
Computational Intelligence - May 2013 - 33
Computational Intelligence - May 2013 - 34
Computational Intelligence - May 2013 - 35
Computational Intelligence - May 2013 - 36
Computational Intelligence - May 2013 - 37
Computational Intelligence - May 2013 - 38
Computational Intelligence - May 2013 - 39
Computational Intelligence - May 2013 - 40
Computational Intelligence - May 2013 - 41
Computational Intelligence - May 2013 - 42
Computational Intelligence - May 2013 - 43
Computational Intelligence - May 2013 - 44
Computational Intelligence - May 2013 - 45
Computational Intelligence - May 2013 - 46
Computational Intelligence - May 2013 - 47
Computational Intelligence - May 2013 - 48
Computational Intelligence - May 2013 - 49
Computational Intelligence - May 2013 - 50
Computational Intelligence - May 2013 - 51
Computational Intelligence - May 2013 - 52
Computational Intelligence - May 2013 - 53
Computational Intelligence - May 2013 - 54
Computational Intelligence - May 2013 - 55
Computational Intelligence - May 2013 - 56
Computational Intelligence - May 2013 - 57
Computational Intelligence - May 2013 - 58
Computational Intelligence - May 2013 - 59
Computational Intelligence - May 2013 - 60
Computational Intelligence - May 2013 - 61
Computational Intelligence - May 2013 - 62
Computational Intelligence - May 2013 - 63
Computational Intelligence - May 2013 - 64
Computational Intelligence - May 2013 - 65
Computational Intelligence - May 2013 - 66
Computational Intelligence - May 2013 - 67
Computational Intelligence - May 2013 - 68
Computational Intelligence - May 2013 - 69
Computational Intelligence - May 2013 - 70
Computational Intelligence - May 2013 - 71
Computational Intelligence - May 2013 - 72
Computational Intelligence - May 2013 - 73
Computational Intelligence - May 2013 - 74
Computational Intelligence - May 2013 - 75
Computational Intelligence - May 2013 - 76
Computational Intelligence - May 2013 - 77
Computational Intelligence - May 2013 - 78
Computational Intelligence - May 2013 - 79
Computational Intelligence - May 2013 - 80
Computational Intelligence - May 2013 - Cover3
Computational Intelligence - May 2013 - Cover4
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202311
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202308
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202305
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202302
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202211
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202208
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202205
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202202
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202111
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202108
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202105
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202102
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202011
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202008
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202005
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_202002
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201911
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201908
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201905
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201902
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201811
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201808
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201805
https://www.nxtbook.com/nxtbooks/ieee/computationalintelligence_201802
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring17
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring16
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring15
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring14
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_summer13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_spring13
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_winter12
https://www.nxtbook.com/nxtbooks/ieee/computational_intelligence_fall12
https://www.nxtbookmedia.com