Current Projects
Resource-rational models of belief revision
How do people revise their beliefs given limited cognitive resources and motivations that may compete with representing the truth?
In this work, I use particle filter models that balance the epistemic and instrumental utilities of holding a belief to capture how people revise their beliefs in light of new evidence across a variety of domains, such as causal reasoning, testimonial reasoning, and social learning.
Learning from, and about, others
How does our tendency to learn from others' information change across the lifespan and across different social contexts?
A rich body of work suggests children are surprisingly sophisticated reasoners, but that they nevertheless show substantial change in their reasoning about others' testimony over time. In this work, I use Bayesian computational models to capture developmental changes in children's, adults', and machines' reasoning about others' beliefs and actions, and how these changes are shaped by features of the agents they learn from.
Modelling emergent social phenomena
How do people's beliefs and actions change when they are embedded in social structures that can shape the information they receive, and which change when acted upon?
In this work, I use a variety of agent-based models, such as multi-agent reinforcement learning (MARL) and generative agent-based models (GABMs), to capture how individual behaviour can produce feedback loops that shape the structure of a social group, and subsequently the beliefs of those within it, producing emergent phenomena such as stereotyping and social convention formation.