Computational Intelligence - May 2013 - 76
write "we view it as a general response to all kinds of emotions,
strong and weak, negative and positive" [7, p. 287], this view
does not seem to have been applied, with respect to positive
emotions, to the strategy of wishful thinking, in EMA. More
concretely, wishful thinking is triggered only as a response to a
negative appraisal and, unlike WTR, EMA does not model
active effects of wishful thinking.
Another fundamental distinction is that, while WTR targets
the problem of belief revision, EMA does not: WTR aims to
find a consistent set of beliefs, and denial of a belief implies
removing it from that set of beliefs and maintaining the relationships that exist among the remaining beliefs; In EMA,
inconsistencies are allowed, each belief is associated with some
probability of being true, and denial/wishful thinking consists
of adjusting these probabilities in order to improve a negatively
charged appraisal.
effects are achieved by enabling every goal to produce a tendency to believe in its achievement (a wishful thought); This
way, any information that contradicts the achievement of a goal
(i.e., any undesirable information) gives rise to an inconsistency,
thus triggering belief revision; Wishful thoughts are typically
too weak and, therefore, abandoned or just filtered out, but
exceptions may occur, depending on various factors.
We recall that WTR addresses wishful thinking in terms of
goal satisfaction. Clearly one's desires and preferences cannot all
be reduced to goals. Consequently, WTR does not account for
all forms of wishful thinking, and neither does it account for
the large variety of emotions that influence belief dynamics in
humans. We view this work as one step toward the design of
belief processes that incorporate affective phenomena and are
suitable for human-like autonomous agents.
References
IX. Conclusions
With the aim of addressing belief revision, in the context of
human-like autonomous agents, we have identified the following issues concerning conventional belief revision:
❏ Why should an agent always prefer new information over
its previous beliefs?
❏ How can an agent autonomously generate its own order(s)
among beliefs?
❏ Can human-like preferences, in belief revision, be adequately expressed using an order (or orders) among beliefs?
To address these issues and enable the simulation of affective
preferences, we propose WTR, an approach to an agent's belief
dynamics, with the following properties:
❏ Non-prioritized. New information is not necessarily believed.
❏ Autonomous. Revision is not dependent on the external definition of orders.
❏ Context-oriented. The preferred context is chosen according
to an order (or orders) among contexts, instead of an order
(or orders) among beliefs. As discussed in Section I, this is
necessary because a belief 's resistance to change may
depend on the other beliefs.
❏ Simulates wishful thinking. It simulates passive and active
effects of the wishful thinking phenomenon, within the
scope with respect to goal satisfaction.
As we have shown (see Section VII-B), wishful thinking in
WTR is not merely a bias in the resolution of conflicts among
inconsistent data (passive effects); it can sometimes be the sole
cause for having a belief, or for evoking belief revision when
certain beliefs are undesirable (active effects).
Passive effects are achieved by accounting for the likeability
of beliefs, when measuring the preference of a context. Active
76
IEEE ComputatIonal IntEllIgEnCE magazInE | may 2013
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