 Anne G. E. Collins

Anne G. E. Collins studies learning, decision making and executive function using behavioural experiments and computational models. With Robert C. Wilson, she coauthored a 2019 methods paper explaining how to build, simulate, fit and test models of behavior.^[ref]

An illustrative reinforcement learning rule updates a prediction $Q$ after outcome $r$ by $Q_{\mathrm{new}}=Q+\alpha (r-Q)$, where $\alpha$ is a learning rate. Starting at $Q=0.5$ with $r=1$, $\alpha =0.2$ gives $Q_{\mathrm{new}}=0.6$, whereas $\alpha =0.8$ gives $0.9$. This arithmetic shows what a model parameter does; it does not establish that an experimental participant uses that exact rule.

The joint paper emphasizes testing models through computer simulation and parameter recovery, so a fitted parameter is interpreted in light of what the task can actually identify.^[ref]

Institutional research profile: vcresearch.berkeley.edu/faculty/anne-collins .