Portrait de Harley Wiltzer

Harley Wiltzer

Doctorat - McGill
Superviseur⋅e principal⋅e
David Meger
Co-supervisor
Marc Gendron-Bellemare
Sujets de recherche
Apprentissage par renforcement
Modèles probabilistes
Systèmes dynamiques
Site web
Google Scholar
GitHub

Publications

Distributional Hamilton-Jacobi-Bellman Equations for Continuous-Time Reinforcement Learning
Harley Wiltzer
David Meger
Bellemare Marc-Emmanuel
Continuous-time reinforcement learning offers an appealing formalism for describing control problems in which the passage of time is not nat… (voir plus)urally divided into discrete increments. Here we consider the problem of predicting the distribution of returns obtained by an agent interacting in a continuous-time, stochastic environment. Accurate return predictions have proven useful for determining optimal policies for risk-sensitive control, learning state representations, multiagent coordination, and more. We begin by establishing the distributional analogue of the Hamilton-Jacobi-Bellman (HJB) equation for Itô diffusions and the broader class of Feller-Dynkin processes. We then specialize this equation to the setting in which the return distribution is approximated by
2022-06-27
Proceedings of the 39th International Conference on Machine Learning (publié)
doi.org
proceedings.mlr.press