How Modeling Methods for Fuzzy Cognitive Mapping Can Benefit from Psychology Research

Fuzzy Cognitive Maps (FCMs) are aggregate-level simulation models that represent concepts as nodes, capturing relationships via weighted edges, and apply an inference mechanism to update the nodes' values until a desired effect is achieved. FCMs are increasingly combined with other techniques. Agent-Based Models (ABMs) use FCMs to represent the 'mind' of each agent, which governs (and is influenced by) interactions with other agents or the environment. A question continues to elude simulationists: what should be the building blocks for such simulations? FCMs can now be optimized using machine learning and quantitative data, which means that an agent's mind can be automatically modified to closely align with an evidence base. However, there are multiple ways in which an FCM can be transformed: which transformations correctly capture how individuals change their mind? In this paper, we explore these questions using psychology research, thus leveraging knowledge on human behaviors to inform social simulations.