Should I Stop Thinking About It: A Computational Exploration of Reappraisal Based Emotion Regulation

Abstract

Agent-based simulation of people’s behaviors and minds has become increasingly popular in recent years. It provides a research platform to simulate and compare alternative psychological and social theories, as well as to create virtual characters that can interact with people or among each other to provide pedagogical or entertainment effects. In this paper, we investigate computationally modeling people’s coping behaviors and in particular in relation to depression, in decision-theoretic agents. Recent studies have suggested that depression can result from failed emotion regulation under limited cognitive resources. In this work, we demonstrate how reappraisal can fail under high levels of stress and limited cognitive resources using an agent-based simulation. Further, we explored the effectiveness of reappraisal under different conditions. Our experiments suggest that for people who are more likely to recall positive memories, it is more beneficial to think about the recalled events from multiple perspectives. However, for people who are more likely to recall negative memories, the better strategy is to not evaluate the recalled events against multiple goals.