Knowledge Representation in Decision Making
Abstract: I discuss how insights from machine learning and data science can be used to build models of decision making with human-like knowledge representations. In addition to specifying the cognitive mechanisms people use to form beliefs and preferences, these models also represent the information on which these mechanisms operate. Subsequently, they are able to deliberate over and respond to a large variety of naturalistic decision problems, and moreover, mimic human responses to these problems. These models shed light on the processes at play in everyday decision making, and illustrate a novel approach to predicting real-world behavior.