Computational Models of Mentalizing

Humans have a remarkable ability to infer and represent others’ mental states such as their beliefs, goals, desires, intentions, and feelings. In this chapter, we review some of the innovations that have developed in economics, computer science, and cognitive neuroscience in modeling the computations underlying several mentalizing operations. Broadly, this involves building models of how agents infer the mental states of other agents within constrained environments. These models include modules for representing the goals and desires of an agent (e.g., maximize reward, or minimize embarrassment), inferring the mental states of other agents (e.g., beliefs, goals, desires, intentions, and feelings), and integrating these goals and mentalizing computations to produce optimal behavioral policies to navigate the environment. The mathematical operationalization of these constructs provides a general framework that can be validated by behavior and neural recording techniques and extended in the future by contributions from multiple scientific disciplines.