Document Type : Research
Authors
1
Associate Professor, Science schools; School of Mathematics, Statistics and Computer Science, University of Tehran, Tehran, Iran
2
Graduate of Humanities Department of Philosophy and Logic , Tarbiat Modares University, Tehran, Iran
3
Professor at the Faculty of Humanities Department of Philosophy and Logic , Tarbiat Modares University, Tehran, Iran
10.30465/lsj.2025.53190.1513
Abstract
Counterfactual emotions, such as envy and regret, play a foundational role in shaping human behavior, influencing moral judgment, and guiding social interaction. Because they arise from the comparison between actual states and imagined alternative scenarios, these emotions serve as powerful cognitive mechanisms that motivate individuals to reassess their decisions, modify their actions, and anticipate future consequences. Consequently, they are of substantial importance to the advancement of research in artificial intelligence and multi-agent systems, where modeling human-like affective reasoning remains a central challenge. In this article, we formalize the counterfactual emotions of envy and regret using the Counterfactual Emotions (CFE) framework [2]. Furthermore, we examine their intensity through quantitative constructs such as the “degree of importance,” “degree of inadequacy,” and “degree of counterfactual avoidability” introduced in [1]. This study provides a theoretical and computational foundation for developing intelligent agents capable of understanding, representing, and adapting to the complex emotional and ethical dimensions of human interaction.
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