# Quantification of emotions in decision making

arXiv: https://arxiv.org/abs/2203.02217 · HTML: https://mlsanity.com/paper/2203.02217/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 59 references that are in the map.
- First posted on arXiv 4 Mar 2022.

## Builds on (most cited first, 4 of 4)

- [Evolutionary Processes in Quantum Decision Theory](https://mlsanity.com/paper/2006.16763/) (2020)
- [Tossing Quantum Coins and Dice](https://mlsanity.com/paper/2103.17007/) (2021)
- [A Resolution of St. Petersburg Paradox](https://mlsanity.com/paper/2111.14635/) (2021)
- [A Subjective Model of Human Decision Making Based on Quantum Decision Theory](https://mlsanity.com/paper/2101.05851/) (2021)

## Built on by (most cited first, 2 of 2)

- [Quantum Operation of Affective Artificial Intelligence](https://mlsanity.com/paper/2305.08112/) (2023)
- [Discrete Versus Continuous Algorithms in Dynamics of Affective Decision Making](https://mlsanity.com/paper/2309.00357/) (2023)

## Abstract (arXiv)

The problem of quantification of emotions in the choice between alternatives is considered. The alternatives are evaluated in a dual manner. From one side, they are characterized by rational features defining the utility of each alternative. From the other side, the choice is affected by emotions labeling the alternatives as attractive or repulsive, pleasant or unpleasant. A decision maker needs to make a choice taking into account both these features, the utility of alternatives and their attractiveness. The notion of utility is based on rational grounds, while the notion of attractiveness is vague and rather is based on irrational feelings. A general method, allowing for the quantification of the choice combining rational and emotional features is described. Despite that emotions seem to avoid precise quantification, their quantitative evaluation is possible at the aggregate level. The analysis of a series of empirical data demonstrates the efficiency of the approach, including the realistic behavioral problems that cannot be treated by the standard expected utility theory.