How do we learn, plan, and make decisions?

The lab seeks to understand how humans learn and plan. We primarily use a reinforcement learning framework to develop algorithmic explanations of human learning and planning. Importantly, we also seek to use this framework to shed light on mechanisms of human anxiety.

I have taken a nontraditional path towards this program of research, and welcome those with diverse interests to join the team. I began in a clinical psychology PhD, moved to a devleopmental neuroscience lab to finish my PhD, and spent the past 5 years in computational cognitive science labs. To do so, I've spent time in Chapel Hill (UNC), London (UCL), Jerusalem (Hebrew University), and now New Haven (Yale).

• Humans adaptively switch between backward and forward prediction

  Planning direction

  Posted on August 19, 2022

  

  

  Leading models of human decision-making assume humans learn forward predictions, from a given state to the outcomes that typically follow it. Here, we show that in many situations decision-making can be made more efficient by relying on backward predictions, from a given outcome to the states that typically precede it. This holds specifically in environments where the number of possible outcomes exceeds the number of... [Read More]

  Tags:

  • Reinforcement learning
  • planning

• Goal mismanagement in reinforcement learning

  Our article in eLife

  Posted on August 17, 2022

  

  

  Human must use a limited amount of resources to plan efficiently over many goals. For example, in a single day, people need to plan when they will organize their homes, and how to pursue longer-term financial and social aspirations. We can ask whether humans prioritize more so goals that involve possible reward or possible punishment. According to evolutionary theory, humans may prioritize goals involving punishment... [Read More]

  Tags:

  • reinforcement learning
  • multi-tasking