P. Dayan

Risking your Tail: Modeling Individual Differences in Risk-sensitive Exploration using Bayes Adaptive Markov Decision Processes

This paper models individual differences in risk-sensitive exploration using a Bayes adaptive Markov decision process model applied to animal behavior data.

Dissecting the Complexities of Learning With Infinite Hidden Markov Models

The paper introduces an infinite hidden semi-Markov model to analyze learning curves in mice, finding three major learning stages and behavior changes after rest periods.

Tracking human skill learning with a hierarchical Bayesian sequence model

This paper uses a hierarchical Bayesian sequence model to analyze human skill learning over multiple sessions, finding that participants adaptively adjust their reliance on different sequence depths.

Control over patch encounters changes foraging behaviour

The paper examines how control over site selection during foraging affects decision-making, finding that participants achieved higher reward rates by revisiting fast-replenishing sites and using information about alternative sites.

Subjective Beliefs In, Out, and About Control: A Quantitative Analysis

This study investigates how beliefs about control and chance influence decision-making after task success or failure, finding that internal attributions affect risk-taking and reward orientation.

Modelling avoidance in pathologically anxious humans using reinforcement-learning

This study uses reinforcement-learning models to analyze avoidance behavior in anxious individuals under stress, finding increased reliance on a Pavlovian bias parameter in the anxious group.