Computational Intelligence - May 2013 - 69

results. In this line of thought, if A is a valid
In our approach, every goal produces a wishful
support for its formula, when b c is the context believed by agent ag, we say that the
thought about its achievement, in the form of a weak
(causal) strength conveyed by A is given by
belief. Consequently, a "disliked situation" leads to
SuppStr(A, b c, ag) d @ 0, 1@ .
c
inconsistent beliefs, thus triggering belief revision.
So, if agent ag's believed context is b and
U d BS (b c, ag), the value of CauStr
beliefs and the third focuses on the context's wishful beliefs and
(U, b c, ag) results from combining the values of SuppStr
their opposite counterparts (i.e., disliked beliefs):
(A, b c, ag), for each A in Sups(U, b c, ag).
1) The most important factor is the number of absolute cerWTR does not impose any particular definition for functainties in the base beliefs. Given the meaning of absolute
tion CauStr, however, certain conditions are postulated. For any
certainty, it is only natural that an agent always believes in
formula, U , believed by agent ag, when ag's believed context is
c
all of its absolute certainties. The only situation where we
b , the definition of CauStr should be such that the following
find conceivable not to believe in an absolute certainty is
conditions hold:
if there are other conflicting absolute certainties (an atyp1) If there is a support, in Sups(U, b c, ag) , that conveys a
ical situation). To achieve this behavior, in WTR, we
strength of 1, then CauStr(U, b c, ag) = 1;
ensure that a context with more absolute certainties (than
2) Otherwise, having one more support in Sups(U, b c, ag),
another), among the base beliefs, always has a greater
or having a higher strength of a support in Sups
value of preference.
(U, b c, ag), increases CauStr(U, b c, ag).
2) Apart from certainties, the number and causal strength of
These postulates impose merely intuitive properties, respecthe other (uncertain) base beliefs also influences the preftively: 1) If I have a reason to be absolutely certain that U is
erence of the context. Obviously, the agent prefers beliefs
true, other reasons supporting belief in U will not invalidate
that have a greater degree of certainty over beliefs that
my certainty; 2) If I believe in U (but not with absolute cerhave a lower degree, and prefers to keep a larger number
tainty), having more reasons or stronger reasons to believe in U
of beliefs over keeping a smaller number (according to
increases the level of certainty of my belief in U .
the minimal change principle).
Once again, WTR does not impose any particular defini3) The third factor is likeability, meant to capture the inflution for function SuppStr, however, certain conditions are posence of wishful thinking. More specifically, a context's
tulated. For any formula, U , believed by agent ag, when ag's
likeability is an assessment of the corresponding belief
believed context is b c , any other agent ag l , and any set of
space, in terms of: a) the number and strength of beliefs in
hypotheses a 3 b c, the definition of SuppStr should be such
goal achievements (wishful beliefs), in combination with
that the following conditions hold:
the importance of the corresponding goals, and b) the
1) SuppStr ^ U, ag l , " U , , b c, ag h increases with Cred
number and strength of beliefs in negations of goal
(ag, ag l )
achievements, in combination with the importance of the
2) SuppStr^ U, WT, " U , , b c, ag h increases with the imporcorresponding goals.
tance of the goal with description U, and with wt(ag)
The context preference (or, simply, preference) that an agent, ag,
3) SuppStr ^ U, Der, Y
0 , b c, ag h = 1
attributes to a context, b c , is given by CtxPrf(b c, ag) d R + .
4) SuppStr ^ U, Der, a , b c, ag h remains the same if a has
one more certainty, decreases if a has one more non-cerSince we want the number of certainties, among base beliefs,
(i.e., factor 1. discussed above) to have more weight than all
tainty, and increases if the strength (considering context
c
other factors, we define the preference of a context as that numb \ " U ,, to disregard derivation cycles) of one of the
ber (of certainties), added to a value in @ 0, 1 6 that accounts for
beliefs in a increases.
These postulates impose merely intuitive properties, respecthe remaining factors (i.e., factors 2. and 3. discussed above).This
tively: 1) The more credible I find someone, the stronger I
added value is given by LessSigPrf(b c, ag) d @ 0, 1 6 (Less
believe that person's communications (this is, in fact, how we
Significative Preference). This formulation ensures that having one
defined Cred, in Section IV); 2) If having U as a goal is a reason
more certainty always grants more context preference than any
for me to believe in U, that reason's strength increases with the
other combination of factors.
goal's importance and with how susceptible I am to wishful
Definition 5: Given agent ag and context b c (where b is
thinking (this is in accordance with the meaning of goal imporobtained from b c and ag, as defined in the beginning of Section V),
tance and with the definition of wt, discussed in Section IV);
function CtxPrf is defined as follows:
3) A belief that corresponds to a tautology is obviously a cerCtxPrf (b c, ag) = # {U ! b: CauStr (U, b c, ag) = 1}
tainty; 4) If I derive U, based on a set of believed hypotheses,
the strength of this derivation decreases with the overall uncer+ LessSigPrf (b c, ag).
tainty in that set of hypotheses.
Finally, in WTR, the preference of a context accounts for
We define LessSigPrf(b c, ag) as a mapping, to @ 0, 1 6,
three factors, where the first two focus on the context's base
of LSP (b c, ag) d R Zero preference is mapped to 0.5, positive

May 2013 | IEEE CoMputatIonal IntEllIgEnCE MagazInE

69



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