情報処理学会 第74回全国大会講演要旨

Decision making has proposed multiple methods to help the decision maker
in his analysis, by suggesting ways of formalization of the preferences as
well as the assessment of the uncertainties. Although these techniques are
established and proven to be mathematically sound, experience has shown
that in certain situations we tend to avoid the formal approach by acting
intuitively. Especially, when the decision involves a large number of
attributes and outcomes, and where we need to use pragmatic and heuristic
simplifications such as considering only the most important attributes and
omitting the others.

It is in this perspective that we propose our model and its potential
applications as a way to understand how humans handle these problems, for
instance, through heuristics. In this paper, we investigate how heuristics
work in cognition, and we take the example of the cognitive task of
decision making. We propose a study of the cognitive architecture that is
able to facilitate the heuristic process based on principle of maximum
entropy in outcomes elicitation. Our main result is the elaboration of a
heuristic approach based on the maximal entropy principle, and therefore,
showing that the usage of heuristics is related to the entropic solutions
to the given problem. Furthermore, we propose an explanation on how humans
handle problems subject to a high-information-load and characterized with
high uncertainty.