4 papers
Flexibility without foresight: the predictive limitations of mixture models
Stephane Hess, Sander van Cranenburgh
Models allowing for random heterogeneity, such as mixed logit and latent class, are generally observed to obtain superior model fit and yield detailed insights into unobserved pref…
Delphos: A reinforcement learning framework for assisting discrete choice model specification
Gabriel Nova, Stephane Hess, Sander van Cranenburgh
We introduce Delphos, a deep reinforcement learning framework for assisting the discrete choice model specification process. Delphos aims to support the modeller by providing autom…
Understanding the decision-making process of choice modellers
Gabriel Nova, Sander van Cranenburgh, Stephane Hess
Discrete Choice Modelling serves as a robust framework for modelling human choice behaviour across various disciplines. Building a choice model is a semi structured research proces…
A utility-based spatial analysis of residential street-level conditions; A case study of Rotterdam
Sander van Cranenburgh, Francisco Garrido-Valenzuela
Residential location choices are traditionally modelled using factors related to accessibility and socioeconomic environments, neglecting the importance of local street-level condi…