Human Emotion Verification by Action Languages via Answer Set Programming

TL;DR

This paper introduces C-MT, an action language based on ASP, to model and verify human emotional state changes through formal transition systems and psychological principles.

Contribution

It extends answer set programming with causal rules and mental state expressions, enabling controlled reasoning about emotional dynamics.

Findings

Formalizes mental states as multi-dimensional configurations

Models valid transitions between mental states using transition constraints

Allows comparison of different emotional change trajectories

Abstract

In this paper, we introduce the action language C-MT (Mind Transition Language). It is built on top of answer set programming (ASP) and transition systems to represent how human mental states evolve in response to sequences of observable actions. Drawing on well-established psychological theories, such as the Appraisal Theory of Emotion, we formalize mental states, such as emotions, as multi-dimensional configurations. With the objective to address the need for controlled agent behaviors and to restrict unwanted mental side-effects of actions, we extend the language with a novel causal rule, forbids to cause, along with expressions specialized for mental state dynamics, which enables the modeling of principles for valid transitions between mental states. These principles of mental change are translated into transition constraints, and properties of invariance, which are rigorously evaluated using transition systems in terms of so-called trajectories. This enables controlled reasoning about the dynamic evolution of human mental states. Furthermore, the framework supports the comparison of different dynamics of change by analyzing trajectories that adhere to different psychological principles. We apply the action language to design models for emotion verification. Under consideration in Theory and Practice of Logic Programming (TPLP).