Mathematical Models for Decision-Making
Thursday, June 17 at 04:15am (PDT)Thursday, June 17 at 12:15pm (BST)Thursday, June 17 08:15pm (KST)
Nicholas Barendregt (University of Colorado Boulder, United States), Jonathan Rubin (University of Pittsburgh, United States)
To make effective decisions in real-world settings, an organism must accurately infer the nature of its environment from noisy observations and efficiently commit to a choice. As environments become more complex, so must the internal models and computations that subserve this process. Analyzing the mechanisms underlying decision-making is crucial to understanding individual and collective behaviors and has applications in psychology, economics, and medicine. Decision processes have been investigated from many perspectives, ranging from studies focusing on small groups of neurons to observations of organismal behaviors. In this minisymposium, we highlight these different approaches to modeling decision-making mathematically. The series will focus on connecting theory with empirical observations and will include speakers that specialize in model development, analysis, and validation using experimental data.