Modelings decisions in AI:re-thinkning Linda in terms of coherent lower and upper conditional previsions
Chapter
Publication Date:
2020
abstract:
In this paper, the model of coherent upper and lower conditional previsions is proposed to represent preference orderings and
equivalences between random variables that human beings consider consciously or unconsciously when making decisions. To solve the contradiction, Linda’s Problem (i.e., conjunction fallacy) is re-interpreted in terms
of the probabilistic model based on coherent upper and lower conditional
probabilities. Main insights of this mathematical solution for modeling
decisions in AI are evidenced accordingly.
equivalences between random variables that human beings consider consciously or unconsciously when making decisions. To solve the contradiction, Linda’s Problem (i.e., conjunction fallacy) is re-interpreted in terms
of the probabilistic model based on coherent upper and lower conditional
probabilities. Main insights of this mathematical solution for modeling
decisions in AI are evidenced accordingly.
Iris type:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Coherent upper and lower conditional previsions · Linda’s
Problem · Human decision making · Conscious and unconscious
thought
List of contributors:
Doria, S.; Cenci, A.
Book title:
Modeling Decisions for Artificial Intelligence
Published in: