Maarten Speekenbrink

Adaptive planning in human search

The paper shows humans plan ahead by searching at least 3 steps in a foraging task, using a heuristic called root-sampling that outperforms more complex models.

Structured priors in human forecasting

This study shows that human forecasts are guided by structured priors derived from real-world experience, leading to context-dependent predictions that align with real-world structures.

Active learning reveals underlying decision strategies

This study uses model-based active learning to determine if people use heuristics or full-information strategies in decision-making, finding they follow a weight-based strategy.

A tutorial on Gaussian process regression: Modelling, exploring, and exploiting functions

This tutorial introduces Gaussian process regression as a tool for modeling and exploring unknown functions, with examples and applications in regression, kernel assumptions, and exploration-exploitation scenarios.

Strategic exploration in human adaptive control

This study investigates how humans balance exploration and exploitation in uncertain environments, finding strategic yet conservative exploration behaviors.

Mapping the unknown: The spatially correlated multi-armed bandit

This study introduces a spatially correlated multi-armed bandit task to model how people form beliefs about unexplored payoffs and guide search behavior based on spatial correlations.