Analysis of Computational Models to Describe Individual Decision-Making Process

Abstract

Understanding the human decision-making process and evaluating the quality of these decisions has been the focus of many researchers. Previously, we proposed a computational, cognitive framework called the Double Transition Model (DTM) to study human decision-making processes. We applied it to simulate a couple of scenarios developed through a naval warfare simulation game called Steel Ocean. This framework concentrated on the cognitive process of an individual’s decision-making process and capturing his cognitive style. One of the key functionalities of this framework has been to provide a reward distribution indicating the quality of decisions made under certain conditions. In this paper, we present a rigorous investigation of our models capturing individual characteristics with respect to decision-making style and the reward distributions. In particular, our models explored the following questions: 1) whether individual models are different from each other like human beings are; 2) whether these models exhibit particular decision-making styles; and 3) whether these models can capture different situations as human beings do. We evaluated the capability of our models capturing these individuals’ characteristics by comparing multiple DTMs against each other, each built from a couple of individuals under various circumstances. We confirmed that individual characteristics could be captured in the DTMs. Furthermore, we compared individuals’ trajectories (i.e., a sequence of decisions) identified by multiple DTMs in addition to their associated neighbors to verify that decision-making process in various social conditions could be described with DTMs. Our empirical study was conducted on two sets of real-world data: Supervisory Control Operations User Testbed (SCOUT) and the naval warfare simulation game (Steel Ocean).