Human decision making through an entropic framework

In this paper, new entropy functions are formulated based on an agent's perceived uncertainty that inevitably affects the agent's choice. The role of the decision-maker's (DM's) attitude is emphasized as one of the key determinants of such an entropy function. More specifically, new attitude-based variants of Shannon's, Pal & Pal, and Aggarwal's probabilistic entropies are introduced. The extant fuzzy entropies are also extended to consider the agent's specific attitude. The proposed entropy functions provide a wide range of entropy values with the conventional entropy functions as their special cases. The special cases of the proposed entropies are examined. The wide applicability of the proposed entropy functions in multi criteria decision making is highlighted. A casestudy is included to showcase the usefulness of the proposed entropy functions in the real world.

Automated summary

New entropy functions based on an agent's perceived uncertainty are formulated in this paper, highlighting the role of the decision-maker's attitude. The study introduces new attitude-based variants of probabilistic entropies and extends existing fuzzy entropies to consider the agent's specific attitude. The proposed entropy functions are shown to have wide applicability in multi criteria decision making.