Modeling Task Immersion based on Goal Activation Mechanism

TL;DR

This paper develops a computational model of task immersion based on goal activation, examining how arousal influences task transition difficulty and aligning model behavior with human experiments.

Contribution

It introduces a novel arousal dynamics model within the ACT-R framework, linking arousal levels to task transition challenges and validating it through human experiment simulations.

Findings

Model behavior aligns with human experimental results

High arousal increases difficulty in task switching

Arousal influences overall activation in cognitive processes

Abstract

Immersion in a task is a prerequisite for creativity. However, excessive arousal in a single task has drawbacks, such as overlooking events outside of the task. To examine such a negative aspect, this study constructs a computational model of arousal dynamics where the excessively increased arousal makes the task transition difficult. The model was developed using functions integrated into the cognitive architecture Adaptive Control of Thought-Rational (ACT-R). Under the framework, arousal is treated as a coefficient affecting the overall activation level in the model. In our simulations, we set up two conditions demanding low and high arousal, trying to replicate corresponding human experiments. In each simulation condition, two sets of ACT-R parameters were assumed from the different interpretations of the human experimental settings. The results showed consistency of behavior between humans and models both in the two different simulation settings. This result suggests the validity of our assumptions and has implications of controlling arousal in our daily life.