Time allocation and meta-cognition: A computational approach towards the organization of motivation

Abstract

How do people allocate time and effort across tasks? This dissertation takes a computational psychology perspective, and puts forward the theory that motivation solves the meta-cognitive problem of allocating resources to different tasks by computing task priority. Motivation research has previously distinguished between two dissociable components of motivation: directing and energizing. These two components refer to different resources that must be allocated: time and effort. We explore the way humans allocate effort by taking advantage of simple decision making tasks and manipulating either task or background information. We develop a novel method that allows researchers to integrate an array of biometrics that capture how decision processes are modulated. We then extend work from optimal foraging theory to account for human tasks in order to analyze how humans allocate time. We derive various results that match time use behavior across domains. Finally, we apply the structural implications of this theory to make predictions in large scale time use data sets. Humans must often schedule mutually exclusive goals to fulfill mutually exclusive needs, which requires us to allocate time across tasks via a priority computation. Re-framing motivation from a resource allocation perspective, and highlighting the unique problem of time allocation, has implications across human decision making behavior, and we demonstrate its relevance in multiple domains.